title: The Role of Life Cycle and Migration in Selection for Offspring Variance

abstract:
  For two genotypes that have the same mean number of offspring but differ in
the variance in offspring number, natural selection will favor the genotype
with lower variance. The concept of fitness becomes cloudy under these
conditions because the outcome of evolution is not deterministic. However, the
effect of variance in offspring number on the fixation probability of mutant
strategies has been calculated under several scenarios with the general
conclusion that variance in offspring number reduces fitness but only in
proportion to the inverse of the population size (Gillespie 1974, Proulx 2000).
This relationship becomes more complicated under a metapopulation scenario
where the "effective" population size depends on migration rate, population
structure, and life cycle. We show that under hard selection and weak migration
fitness in a metapopulation composed of equal sized demes is determined by deme
size. Conversely, for high migration rates and hard selection the effective
fitness depends on the total size of the metapopulation. Interestingly, under
soft selection there is no effect of migration or neighboring population
structure on effective fitness, and fitness depends only on deme size. We use
individual based simulations in developed in Shpak (2005) to validate our
analytical approximations and investigate deviations of our assumption of equal
deme size.


title:
Weak pairwise correlations imply strongly correlated network states in a
  neural population

abstract:
  Biological networks have so many possible states that exhaustive sampling is
impossible. Successful analysis thus depends on simplifying hypotheses, but
experiments on many systems hint that complicated, higher order interactions
among large groups of elements play an important role. In the vertebrate
retina, we show that weak correlations between pairs of neurons coexist with
strongly collective behavior in the responses of ten or more neurons.
Surprisingly, we find that this collective behavior is described quantitatively
by models that capture the observed pairwise correlations but assume no higher
order interactions. These maximum entropy models are equivalent to Ising
models, and predict that larger networks are completely dominated by
correlation effects. This suggests that the neural code has associative or
error-correcting properties, and we provide preliminary evidence for such
behavior. As a first test for the generality of these ideas, we show that
similar results are obtained from networks of cultured cortical neurons.


title:
Dynamics of networking agents competing for high centrality and low
  degree

abstract:
  We model a system of networking agents that seek to optimize their centrality
in the network while keeping their cost, the number of connections they are
participating in, low. Unlike other game-theory based models for network
evolution, the success of the agents is related only to their position in the
network. The agents use strategies based on local information to improve their
chance of success. Both the evolution of strategies and network structure are
investigated. We find a dramatic time evolution with cascades of strategy
change accompanied by a change in network structure. On average the network
self-organizes to a state close to the transition between a fragmented state
and a state with a giant component. Furthermore, with increasing system size
both the average degree and the level of fragmentation decreases. We also
observe that the network keeps on actively evolving, although it does not have
to, thus suggesting a Red Queen-like situation where agents have to keep on
networking and responding to the moves of the others in order to stay
successful.


title: Distribution networks and the optimal form of the kidney and lung

abstract:
  A model is proposed to minimize the total volume of the main distribution
networks of fluids in organs such as the kidney and the lung. A consequence of
the minimization analysis is that the optimal overall form of the organs is a
modified ellipsoid. The variational procedure implementing this minimization is
similar to the traditional isoperimetric theorems of geometry.


title: Modeling stochastic gene expression under repression

abstract:
  Intrinsic transcriptional noise induced by operator fluctuations is
investigated with a simple spin like stochastic model. The effects of
transcriptional fluctuations in protein synthesis is probed by coupling
transcription and translation by an amplificative interaction. In the presence
of repression a new term contributes to the noise which depends on the rate of
mRNA production. If the switching time is small compared with the mRNA life
time the noise is also small. In general the dumping of protein production by a
repressive agent occurs linearly but the fluctuations can show a maxima at
intermediate repression. The discrepancy between the switching time, the mRNA
degradation and protein degradation is crucial for the repressive control in
translation without large fluctuations. The noise profiles obtained here are in
quantitative agreement with recent experiments.


title: Bacterial self-organisation and computation

abstract:
  In this article we highlight chemotaxis (cellular movement) as a rich source
of potential engineering applications and computational models, highlighting
current research and possible future work. We first give a brief description of
the biological mechanism, before describing recent work on modelling it in
silico. We then propose a methodology for extending existing models and their
possible application as a fundamental tool in engineering cellular pattern
formation. We discuss possible engineering applications of human-defined cell
patterns, as well as the potential for using abstract models of chemotaxis for
generalised computation, before concluding with a brief discussion of future
challenges and opportunities in this field.


title: Collective dynamics of molecular motors pulling on fluid membranes

abstract:
  The collective dynamics of $N$ weakly coupled processive molecular motors are
considered theoretically. We show, using a discrete lattice model, that the
velocity-force curves strongly depend on the effective dynamic interactions
between motors and differ significantly from a simple mean field prediction.
They become essentially independent of $N$ if it is large enough. For strongly
biased motors such as kinesin this occurs if $N\gtrsim 5$. The study of a
two-state model shows that the existence of internal states can induce
effective interactions.


title: Parametric inference of recombination in HIV genomes

abstract:
  Recombination is an important event in the evolution of HIV. It affects the
global spread of the pandemic as well as evolutionary escape from host immune
response and from drug therapy within single patients. Comprehensive
computational methods are needed for detecting recombinant sequences in large
databases, and for inferring the parental sequences.
  We present a hidden Markov model to annotate a query sequence as a
recombinant of a given set of aligned sequences. Parametric inference is used
to determine all optimal annotations for all parameters of the model. We show
that the inferred annotations recover most features of established hand-curated
annotations. Thus, parametric analysis of the hidden Markov model is feasible
for HIV full-length genomes, and it improves the detection and annotation of
recombinant forms.
  All computational results, reference alignments, and C++ source code are
available at http://bio.math.berkeley.edu/recombination/.


title:
Diversity in Free Energy Landscape of Proteins with the Same Native
  Topology

abstract:
  In order to elucidate the role of the native state topology and the stability
of subdomains in protein folding, we investigate free energy landscape of human
lysozyme, which is composed of two subdomains, by Monte Carlo simulations. A
realistic lattice model with Go-like interaction is used. We take the relative
interaction strength (stability, in other word) of two subdomains as a variable
parameter and study the folding process. A variety of folding process is
observed and we obtained a phase diagram of folding in terms of temperature and
the relative stability. Experimentally-observed diversity in folding process of
c-type lysozimes is thus understood as a consequence of the difference in the
relative stability of subdomains.


title:
Attentional modulation of firing rate and synchrony in a model cortical
  network

abstract:
  When attention is directed into the receptive field of a V4 neuron, its
contrast response curve is shifted to lower contrast values (Reynolds et al,
2000, Neuron 26:703). Attention also increases the coherence between neurons
responding to the same stimulus (Fries et al, 2001, Science 291:1560). We
studied how the firing rate and synchrony of a densely interconnected cortical
network varied with contrast and how they were modulated by attention. We found
that an increased driving current to the excitatory neurons increased the
overall firing rate of the network, whereas variation of the driving current to
inhibitory neurons modulated the synchrony of the network. We explain the
synchrony modulation in terms of a locking phenomenon during which the ratio of
excitatory to inhibitory firing rates is approximately constant for a range of
driving current values. We explored the hypothesis that contrast is represented
primarily as a drive to the excitatory neurons, whereas attention corresponds
to a reduction in driving current to the inhibitory neurons. Using this
hypothesis, the model reproduces the following experimental observations: (1)
the firing rate of the excitatory neurons increases with contrast; (2) for high
contrast stimuli, the firing rate saturates and the network synchronizes; (3)
attention shifts the contrast response curve to lower contrast values; (4)
attention leads to stronger synchronization that starts at a lower value of the
contrast compared with the attend-away condition. In addition, it predicts that
attention increases the delay between the inhibitory and excitatory synchronous
volleys produced by the network, allowing the stimulus to recruit more
downstream neurons.


title:
Mathematical modeling of anti-tumor virus therapy: Regimes with complete
  recovery within the framework of deterministic models

abstract:
  A complete parametric analysis of dynamic regimes of a conceptual model of
anti-tumor virus therapy is presented. The role and limitations of mass-action
kinetics are discussed. A functional response, which is a function of the ratio
of uninfected to infected tumor cells, is proposed to describe the spread of
the virus infection in the tumor. One of the main mathematical features of
ratio-dependent models is that the origin is a complicated equilibrium point
whose characteristics crucially determine the main properties of the model. It
is shown that, in a certain area of parameter values, the trajectories of the
model form a family of homoclinics to the origin (so-called elliptic sector).
Biologically, this means that both infected and uninfected tumor cells can be
eliminated with time, and complete recovery is possible as a result of the
virus therapy within the framework of deterministic models


title:
Co-transport-induced instability of membrane voltage in tip-growing
  cells

abstract:
  A salient feature of stationary patterns in tip-growing cells is the key role
played by the symports and antiports, membrane proteins that translocate two
ionic species at the same time. It is shown that these co-transporters
destabilize generically the membrane voltage if the two translocated ions
diffuse differently and carry a charge of opposite (same) sign for symports
(antiports). Orders of magnitude obtained for the time and lengthscale are in
agreement with experiments. A weakly nonlinear analysis characterizes the
bifurcation.


title:
GIS-aided simulation of spatial distribution of some pollutants at
  "Stolby" state reservation

abstract:
  Reserved territories seem to be best reference sites of wildnature, where the
long-term observations are carried out. Simulation model of spatially
distributed processes of contamination of the state reservation is developed,
and the dynamics of some pollutants is studied. An issue of the generalized
evaluation of an ecological system status is discussed.


title:
The energy cost of protein messages lead to a new protein information
  law

abstract:
  By considering the energy cost of messages carried by proteins as
proportional to their information content we found experimental proof that
proteins from all living organisms tend to have their estimated semantic
content of information per unit mass, statistically, close to a constant. Thus,
in the message carried by proteins -to achieve minimum energy waste- the rate
of information content per unit mass tends to be optimized in living organisms.
The experimental evidence of this new information law resembles a marathon
where highly optimized proteins correspond to advanced runners followed by a
main bunch and the stragglers -lowly optimized proteins. Our results suggest
the existence of a continuous optimization process that living organisms had to
face, in which a compromise between biological functionality, economic
feasibility and the survival requirements is established.


title: A hypothesis on the selective advantage for sleep

abstract:
  In this note, we present a hypothesis for the emergence of the phenomenon of
sleep in organisms with sufficiently developed central nervous systems. We
argue that sleep emerges because individual neurons must periodically enter a
resting state and perform various ``garbage collection'' activities. Because
the proper functioning of the central nervous system is dependent on the
interconnections amongst a large collection of individual neurons, it becomes
optimal, from the standpoint of the organism, for these garbage collection
activities to occur simultaneously. We present analogies with complex
structures in modern economies to make our case, although we emphasize that our
hypothesis is purely speculative at this time. Although the ``garbage
collection'' hypothesis has been previously advanced, we believe that our
speculation is useful because it illustrates the power of a general paradigm
for understanding the emergence of collective behavior in agent-built systems.


title:
A Physical Model for the Condensation and Decondensation of Eukaryotic
  Chromosomes

abstract:
  During the eukaryotic cell cycle, chromatin undergoes several conformational
changes, which are believed to play key roles in gene expression regulation
during interphase, and in genome replication and division during mitosis. In
this paper, we propose a scenario for chromatin structural reorganization
during mitosis, which bridges all the different scales involved in chromatin
architecture, from nucleosomes to chromatin loops. We build a model for
chromatin, based on available data, taking into account both physical and
topological constraints DNA has to deal with. Our results suggest that the
mitotic chromosome condensation/decondensation process is induced by a
structural change at the level of the nucleosome itself.


title:
Cloning, expression and purification of the general stress protein Yhbo
  from Escherichia coli

abstract:
  We cloned, expressed and purified the Escherichia coli yhbO gene product,
which is homolog to the Bacillus subtilis general stress protein 18 (the yfkM
gene product), the Pyrococcus furiosus intracellular protease PfpI, and the
human Parkinson disease protein DJ-1. The gene coding for YhbO was generated by
amplifying the yhbO gene from E. coli by polymerase chain reaction. It was
inserted in the expression plasmid pET-21a, under the transcriptional control
of the bacteriophage T7 promoter and lac operator. A BL21(DE3) E. coli strain
transformed with the YhbO-expression vector pET-21a-yhbO, accumulates large
amounts of a soluble protein of 20 kDa in SDS-PAGE that matches the expected
YhbO molecular weight. YhbO was purified to homogeneity by HPLC DEAE ion
exchange chromatography and hydroxylapatite chromatography and its identity was
confirmed by N-terminal sequencing and mass spectrometry analysis. The native
protein exists in monomeric, trimeric and hexameric forms.


title:
What thermodynamic features characterize good and bad folders? Results
  from a simplified off-lattice protein model

abstract:
  The thermodynamics of the small SH3 protein domain is studied by means of a
simplified model where each bead-like amino acid interacts with the others
through a contact potential controlled by a 20x20 random matrix. Good folding
sequences, characterized by a low native energy, display three main
thermodynamical phases, namely a coil-like phase, an unfolded globule and a
folded phase (plus other two phases, namely frozen and random coil, populated
only at extremes temperatures). Interestingly, the unfolded globule has some
regions already structured. Poorly designed sequences, on the other hand,
display a wide transition from the random coil to a frozen state. The
comparison with the analytic theory of heteropolymers is discussed.


title:
Effect of Predators of Juvenile Rodents on the Spread of the Hantavirus
  Epidemic

abstract:
  Effects of predators of juvenile mice on the spread of the Hantavirus are
analyzed in the context of a recently proposed model. Two critical values of
the predation probability are identified. When the smaller of them is exceeded,
the hantavirus infection vanishes without extinguishing the mice population.
When the larger is exceeded, the entire mice population vanishes. These results
suggest the possibility of control of the spread of the epidemic by introducing
predators in areas of mice colonies in a suitable way so that such control does
not kill all the mice but lowers the epidemic spread.


title:
Egocentric Path Integration Models and their Application to Desert
  Arthropods

abstract:
  Path integration enables desert arthropods to find back to their nest on the
shortest track from any position. To perform path integration successfully,
speeds and turning angles along the preceding outbound path have to be measured
continuously and combined to determine an internal {\em global vector} leading
back home at any time. A number of experiments have given an idea how
arthropods might use allothetic or idiothetic signals to perceive their
orientation and moving speed. We systematically review the four possible model
descriptions of mathematically precise path integration, whereby we favour and
elaborate the hitherto not used variant of egocentric cartesian coordinates.
Its simple and intuitive structure is demonstrated in comparison to the other
models. Measuring two speeds, the forward moving speed and the angular turning
rate, and implementing them into a linear system of differential equations
provides the necessary information during outbound route, reorientation process
and return path. In addition, we propose several possible types of systematic
errors that can cause deviations from the correct homeward course. Deviations
have been observed for several species of desert arthropods in different
experiments, but their origin is still under debate. Using our egocentric path
integration model we propose simple error indices depending on path geometry
that will allow future experiments to rule out or corroborate certain error
types.


title:
The WHO surveillance threshold and the emergence of drug-resistant HIV
  strains in Botswana

abstract:
  Background: Approximately 40% of adults in Botswana are HIV-infected. The
Botswana antiretroviral program began in 2002 and currently treats 34,000
patients with a goal of treating 85,000 patients (~30% of HIV-infected adults)
by 2009. We predict the evolution of drug-resistant strains of HIV that may
emerge as a consequence of this treatment program. We discuss the implications
of our results for the World Health Organization's (WHO's) proposed
surveillance system for detecting drug-resistant strains of HIV in Africa.
Methods: We use a mathematical model of the emergence of drug resistance. We
incorporate demographic and treatment data to make specific predictions as to
when the WHO surveillance threshold is likely to be exceeded. Results: Our
results show - even if rates of acquired resistance are high, but the
drug-resistant strains that evolve are only half as transmissible as wild-type
strains - that transmission of drug-resistant strains will remain low (< 5% by
2009) and are unlikely to exceed the WHO's surveillance threshold. However,our
results show that transmission of drug-resistant strains in Botswana could
increase to ~15% by 2009 if resistant strains are as transmissible as wild-type
strains. Conclusion: The WHO's surveillance system is designed to detect
transmitted resistance that exceeds a threshold level of 5%. Whether this
system will detect drug-resistant strains in Botswana by 2009 will depend upon
the transmissibility of the strains that emerge. Our results imply that it
could be many years before the WHO detects transmitted resistance in other
sub-Saharan African countries with less ambitious treatment programs than
Botswana.


title:
Explicit factorization of external coordinates in constrained
  Statistical Mechanics models

abstract:
  If a macromolecule is described by curvilinear coordinates or rigid
constraints are imposed, the equilibrium probability density that must be
sampled in Monte Carlo simulations includes the determinants of different
mass-metric tensors. In this work, we explicitly write the determinant of the
mass-metric tensor G and of the reduced mass-metric tensor g, for any molecule,
general internal coordinates and arbitrary constraints, as a product of two
functions; one depending only on the external coordinates that describe the
overall translation and rotation of the system, and the other only on the
internal coordinates. This work extends previous results in the literature,
proving with full generality that one may integrate out the external
coordinates and perform Monte Carlo simulations in the internal conformational
space of macromolecules. In addition, we give a general mathematical argument
showing that the factorization is a consequence of the symmetries of the metric
tensors involved. Finally, the determinant of the mass-metric tensor G is
computed explicitly in a set of curvilinear coordinates specially well-suited
for general branched molecules.


title: Contextual Emergence of Mental States from Neurodynamics

abstract:
  The emergence of mental states from neural states by partitioning the neural
phase space is analyzed in terms of symbolic dynamics. Well-defined mental
states provide contexts inducing a criterion of structural stability for the
neurodynamics that can be implemented by particular partitions. This leads to
distinguished subshifts of finite type that are either cyclic or irreducible.
Cyclic shifts correspond to asymptotically stable fixed points or limit tori
whereas irreducible shifts are obtained from generating partitions of mixing
hyperbolic systems. These stability criteria are applied to the discussion of
neural correlates of consiousness, to the definition of macroscopic neural
states, and to aspects of the symbol grounding problem. In particular, it is
shown that compatible mental descriptions, topologically equivalent to the
neurodynamical description, emerge if the partition of the neural phase space
is generating. If this is not the case, mental descriptions are incompatible or
complementary. Consequences of this result for an integration or unification of
cognitive science or psychology, respectively, will be indicated.


title: An irreversible growth model for virus capsid assembly

abstract:
  We model the spontaneous assembly of a capsid (a virus's closed outer shell)
from many copies of identical units, using entirely irreversible steps and only
information local to the growing edge. Our model is formulated in terms of (i)
an elastic Hamiltonian with stretching and bending stiffness and a spontaneous
curvature, and (ii) a set of rate constants for addition of new units or bonds.
An ensemble of highly irregular capsids is generated, unlike the well-known
icosahedrally symmetric viruses, but (we argue) plausible as a way to model the
irregular capsids of retroviruses such as HIV. We found that (i) the
probability of successful capsid completion decays exponentially with capsid
size; (ii) capsid size depends strongly on spontaneous curvature and weakly on
the ratio of the bending and stretching elastic stiffnesses of the shell; (iii)
the degree of localization of Gaussian curvature (a measure of facetedness)
depends heavily on the ratio of elastic stiffnesses.


title: Inferring the in vivo looping properties of DNA

abstract:
  The free energy of looping DNA by proteins and protein complexes determines
to what extent distal DNA sites can affect each other. We inferred its in vivo
value through a combined computational-experimental approach for different
lengths of the loop and found that, in addition to the intrinsic periodicity of
the DNA double helix, the free energy has an oscillatory component with about
half the helical period. Moreover, the oscillations have such an amplitude that
the effects of regulatory molecules become strongly dependent on their precise
DNA positioning and yet easily tunable by their cooperative interactions. These
unexpected results can confer to the physical properties of DNA a more
prominent role at shaping the properties of gene regulation than previously
thought.

categories: q-bio.BM cond-mat.soft physics.bio-ph q-bio.QM q-bio.SC


title: Epidemic dynamics on an adaptive network

abstract:
  Many real world networks are characterized by adaptive changes in their
topology depending on the dynamic state of their nodes. Here we study epidemic
dynamics in an adaptive network, where susceptibles are able to avoid contact
with infected by rewiring their network connections. We demonstrate that
adaptive rewiring has profound consequences for the emerging network structure,
giving rise to assortative degree correlation and a separation into two loosely
connected sub-compartments. This leads to dynamics such as oscillations,
hysteresis and 1st order transitions. We describe the system in terms of a
simple model using a pair-approximation and present a full local bifurcation
analysis. Our results indicate that the interplay between dynamics and topology
can have important consequences for the spreading of infectious diseases and
related applications.


title: Finding mesoscopic communities in sparse networks

abstract:
  We suggest a fast method to find possibly overlapping network communities of
a desired size and link density. Our method is a natural generalization of the
finite-$T$ superparamegnetic Potts clustering introduced by Blatt, Wiseman, and
Domany (Phys. Rev. Lett. v.76, 3251 (1996) and the recently suggested by
Reichard and Bornholdt (Phys. Rev. Lett. v.93, 21870 (2004)) annealing of Potts
model with global antiferromagnetic term. Similarly to both preceding works,
the proposed generalization is based on ordering of ferromagnetic Potts model;
the novelty of the proposed approach lies in the adjustable dependence of the
antiferromagnetic term on the population of each Potts state, which
interpolates between the two previously considered cases. This adjustability
allows to empirically tune the algorithm to detect the maximum number of
communities of the given size and link density. We illustrate the method by
detecting protein complexes in high-throughput protein binding networks.


title:
Phase Transitions and Spatio-Temporal Fluctuations in Stochastic Lattice
  Lotka-Volterra Models

abstract:
  We study the general properties of stochastic two-species models for
predator-prey competition and coexistence with Lotka-Volterra type interactions
defined on a $d$-dimensional lattice. Introducing spatial degrees of freedom
and allowing for stochastic fluctuations generically invalidates the classical,
deterministic mean-field picture. Already within mean-field theory, however,
spatial constraints, modeling locally limited resources, lead to the emergence
of a continuous active-to-absorbing state phase transition. Field-theoretic
arguments, supported by Monte Carlo simulation results, indicate that this
transition, which represents an extinction threshold for the predator
population, is governed by the directed percolation universality class. In the
active state, where predators and prey coexist, the classical center
singularities with associated population cycles are replaced by either nodes or
foci. In the vicinity of the stable nodes, the system is characterized by
essentially stationary localized clusters of predators in a sea of prey. Near
the stable foci, however, the stochastic lattice Lotka-Volterra system displays
complex, correlated spatio-temporal patterns of competing activity fronts.
Correspondingly, the population densities in our numerical simulations turn out
to oscillate irregularly in time, with amplitudes that tend to zero in the
thermodynamic limit. Yet in finite systems these oscillatory fluctuations are
quite persistent, and their features are determined by the intrinsic
interaction rates rather than the initial conditions. We emphasize the
robustness of this scenario with respect to various model perturbations.

categories: q-bio.PE cond-mat.stat-mech nlin.AO q-bio.QM


title: Ambiguous model learning made unambiguous with 1/f priors

abstract:
  What happens to the optimal interpretation of noisy data when there exists
more than one equally plausible interpretation of the data? In a Bayesian
model-learning framework the answer depends on the prior expectations of the
dynamics of the model parameter that is to be inferred from the data. Local
time constraints on the priors are insufficient to pick one interpretation over
another. On the other hand, nonlocal time constraints, induced by a $1/f$ noise
spectrum of the priors, is shown to permit learning of a specific model
parameter even when there are infinitely many equally plausible interpretations
of the data. This transition is inferred by a remarkable mapping of the model
estimation problem to a dissipative physical system, allowing the use of
powerful statistical mechanical methods to uncover the transition from
indeterminate to determinate model learning.


title:
Exact results for noise power spectra in linear biochemical reaction
  networks

abstract:
  We present a simple method for determining the exact noise power spectra in
linear chemical reaction networks. We apply the method to networks which are
representative of biochemical processes such as gene expression and signal
detection. Our results clarify how noise is transmitted by signal detection
motifs, and indicate how to coarse-grain networks by the elimination of fast
reactions.


title: Abelian Finite Group of DNA Genomic Sequences

abstract:
  The Z_64-algebra of the genetic code and DNA sequences of length N was
recently stated. In order to beat the limits of this structure such as the
impossibility of non-coding region analysis in genomes and the impossibility of
the insertions and deletions analysis (indel mutations), we have develop a
cycle group structure over the of extended base triplets of DNA X_1X_2X_3, X_i
belong to {O, A, C, G, U}, where the letter O denote the base omission
(deletion) in the codon. The obtained group is isomorphic to the abelian
5-group Z_125 of integer module 125. Next, it is defined the abelian finite
group S over a set of DNA alignment sequences of length N. The group S could be
represented as the direct sum of homocyclic groups: 2-group and 5-group. In
particular, DNA subsequences without indel mutation could be considered
building block of genes represented by homocyclic 2-groups (described in the
previous Z_64-algebra). While those DNA subsequences affected by indel
mutations are described by means of homocyclic 5-groups. This representation
suggests identify genome block structures by way of a regular grammar capable
of recognize it. In addition, this novel structure allows us a general analysis
of the mutational pathways follow by genes and isofunctional genome regions by
means of the automorphism group on S.


title:
Non-meanfield deterministic limits in chemical reaction kinetics far
  from equilibrium

abstract:
  A general mechanism is proposed by which small intrinsic fluctuations in a
system far from equilibrium can result in nearly deterministic dynamical
behaviors which are markedly distinct from those realized in the meanfield
limit. The mechanism is demonstrated for the kinetic Monte-Carlo version of the
Schnakenberg reaction where we identified a scaling limit in which the global
deterministic bifurcation picture is fundamentally altered by fluctuations.
Numerical simulations of the model are found to be in quantitative agreement
with theoretical predictions.


title:
Short and Long-Term Dynamics of Childhood Diseases on Dynamic
  Small-World Networks

abstract:
  We have performed individual-based lattice simulations of SIR and SEIR
dynamics to investigate both the short and long-term dynamics of childhood
epidemics. In our model, infection takes place through a combination of local
and long-range contacts, in practice generating a dynamic small-world network.
Sustained oscillations emerge with a period much larger than the duration of
infection. We found that the network topology has a strong impact on the
amplitude of oscillations and in the level of persistence. Diseases do not
spread very effectively through local contacts. This can be seen by measuring
an {\em effective} transmission rate $\beta_{\mbox {\scriptsize eff}}$ as well
as the basic reproductive rate $R_0$. These quantities are lower in the
small-world network than in an homogeneously mixed population, whereas the
average age at infection is higher.


title: The importance of selection rate in the evolution of cooperation

abstract:
  How cooperation emerges in human societies is still a puzzle. Evolutionary
game theory has been the standard framework to address this issue. In most
models, every individual plays with all others, and then reproduce and die
according to what they earn. This amounts to assuming that selection takes
place at a slow pace with respect to the interaction time scale. We show that,
quite generally, if selection speeds up, the evolution outcome changes
dramatically. Thus, in games such as Harmony, where cooperation is the only
equilibrium and the only rational outcome, rapid selection leads to dominance
of defectors. Similar non trivial phenomena arise in other binary games and
even in more complicated settings such as the Ultimatum game. We conclude that
the rate of selection is a key element to understand and model the emergence of
cooperation, and one that has so far been overlooked.

categories: q-bio.PE cond-mat.stat-mech nlin.AO physics.soc-ph q-bio.QM


title: Uniqueness of steady states for a certain chemical reaction

abstract:
  Samoilov, Plyasunov, and Arkin provide an example of a chemical reaction
whose full stochastic (Master Equation) model exhibits bistable behavior, but
for which the deterministic (mean field) version has a unique steady state at
least for special parameter values. In this short note, we provide a proof of
uniqueness valid for all possible parameter values.


title:
A new series of polyhedra as blueprints for viral capsids in the family
  of Papovaviridae

abstract:
  In a seminal paper Caspar and Klug established a theory that provides a
family of polyhedra as blueprints for the structural organisation of viral
capsids. In particular, they encode the locations of the proteins in the shells
that encapsulate, and hence provide protection for, the viral genome. Despite
of its huge success and numerous applications in virology experimental results
have provided evidence for the fact that the theory is too restrictive to
describe all known viruses. Especially, the family of Papovaviridae, which
contains cancer-causing viruses, falls out of the scope of this theory.
  In a recent paper we have shown that certain members of the family of
Papovaviridae can be described via tilings. In this paper, we develop a
comprehensive mathematical framework for the derivation of all surface
structures of viral particles in this family. We show that this formalism fixes
the structure and relative sizes of all particles collectively so that there
exists only one scaling factor that relates the sizes of all particles with
their biological counterparts.
  The series of polyhedra derived here complements the Caspar-Klug family of
polyhedra. It is the first mathematical result that provides a common
organisational principle for different types of viral particles in the family
of Papovaviridae and paves the way for an understanding of Papovaviridae
polymorphism. Moreover, it provides crucial input for the construction of
assembly models.


title: Two-state dynamics for replicating two-strand systems

abstract:
  We propose a formalism for describing two-strand systems of a DNA type by
means of soliton von Neumann equations, and illustrate how it works on a simple
example exactly solvably by a Darboux transformation. The main idea behind the
construction is the link between solutions of von Neumann equations and
entangled states of systems consisting of two subsystems evolving in time in
opposite directions. Such a time evolution has analogies in realistic DNA where
the polymerazes move on leading and lagging strands in opposite directions.


title: Cooperativity, sensitivity and noise in biochemical signaling

abstract:
  Cooperative interactions among the binding of multiple signaling molecules is
a common mechanism for enhancing the sensitivity of biological signaling
systems. It is widely assumed that this increase in sensitivity of the mean
response implies the ability to detect smaller signals. We show that, quite
generally, there is a component of the noise in such systems that can be traced
to the random arrival of the signaling molecules at their receptor sites, and
this diffusive noise is not reduced by cooperativity. Cooperativity makes it
easier for real systems to reach this physical limit, but cannot reduce the
limit itself.


title:
Regularization Strategies for Hyperplane Classifiers: Application to
  Cancer Classification with Gene Expression Data

abstract:
  Linear discrimination, from the point of view of numerical linear algebra,
can be treated as solving an ill-posed system of linear equations. In order to
generate a solution that is robust in the presence of noise, these problems
require regularization. Here, we examine the ill-posedness involved in the
linear discrimination of cancer gene expression data with respect to outcome
and tumor subclasses. We show that a filter factor representation, based upon
Singular Value Decomposition, yields insight into the numerical ill-posedness
of the hyperplane-based separation when applied to gene expression data. We
also show that this representation yields useful diagnostic tools for guiding
the selection of classifier parameters, thus leading to improved performance.


title: Designing the Dynamics of Spiking Neural Networks

abstract:
  Precise timing of spikes and temporal locking are key elements of neural
computation. Here we demonstrate how even strongly heterogeneous, deterministic
neural networks with delayed interactions and complex topology can exhibit
periodic patterns of spikes that are precisely timed. We develop an analytical
method to find the set of all networks exhibiting a predefined pattern
dynamics. Such patterns may be arbitrarily long and of complicated temporal
structure. We point out that the same pattern can exist in very different
networks and have different stability properties.


title:
A Model of the Roles of Essential Kinases in the Induction and
  Expression of Late Long-Term Potentiation

abstract:
  The induction of late long-term potentiation (L-LTP) involves complex
interactions among second messenger cascades. To gain insights into these
interactions, a mathematical model was developed for L-LTP induction in the CA1
region of the hippocampus. The differential equation-based model represents
actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II
(CAMKII) in the vicinity of the synapse, and activation of transcription by CaM
kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic
weight. Simulations suggest that steep, supralinear stimulus-response
relationships between stimuli (elevations in [Ca2+]) and kinase activation are
essential for translating brief stimuli into long-lasting gene activation and
synaptic weight increases. Convergence of multiple kinase activities to induce
L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply
with the number of tetanic electrical stimuli. The model simulates tetanic,
theta-burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to
synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of
MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to
delineate mechanisms underlying L-LTP induction and expression. For example,
the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to
inhibit ERK activation. The model also appears useful to clarify similarities
and differences between hippocampal L-LTP and long-term synaptic strengthening
in other systems.


title:
Frequency and Viability of Diploid and Haploid Males Offsprings of Mated
  Females of Solitary Endoparasitoid (DIADROMUS Pulchellus) (Ichneumonidae)

abstract:
  Sex determination in the order Hymenoptera is based on arrhenotoky,
hymenopteran males are usually haploid and females diploid. Males of the
Ichneumonidae Diadromus pulchellus, solitary endoparasitoid of A. assectella
pupae are normally haploid, but diploid males are present in a natural
population and can be obtained in a experimental population. The future of an
ovocyte laid by mated females of the solitary endoparasitoid Diadromus
pulchellus was characterised by 6 probabilities related to the sex and the
development of the ovocyte. The probabilities of fertilisation of female
ovocyte (k1) or non-fertilisation (k3) showed that an inseminated female
functioned as a unmated female for half of the time (since k1= 0.492 and k3 =
0.455) with the probability of fertilisation of male ovocyte (k2 = 0.053).The
survival probabilities of each type of ovocyte showed that an ovocyte had a
high probability of developing up to the adult stage, although the difference
between the calculated sex ratios at laying (males / females = 1.032) and at
emergence (0.90) revealed a slight reduction in the number of haploid sons. The
probabilities of fertilisation and of viability of all the ovocytes laid by
each of the 33 mated females were analysed by an ascending hierarchical
classification of Euclidean distances and by an analysis of their principal
components. The 33 mothers were distributed into 4 distinct sub-groups
characterised by a sex ratio varying from an exclusive presence of females to
an exclusive presence of males. Our hypothesis was that this distribution in 4
sub-sets could not simply result from the random nature of the sample.


title: Surprises in approximating Levenshtein distances

abstract:
  The Levenshtein distance is an important tool for the comparison of symbolic
sequences, with many appearances in genome research, linguistics and other
areas. For efficient applications, an approximation by a distance of smaller
computational complexity is highly desirable. However, our comparison of the
Levenshtein with a generic dictionary-based distance indicates their
statistical independence. This suggests that a simplification along this line
might not be possible without restricting the class of sequences. Several other
probabilistic properties are briefly discussed, emphasizing various questions
that deserve further investigation.


title: Waveform sample method of excitable sensory neuron

abstract:
  We present a new interpretation for encoding information of the period of
input signals into spike-trains in individual sensory neuronal systems. The
spike-train could be described as the waveform sample of the input signal which
locks sample points to wave crests with randomness. Based on simulations of the
Hodgkin-Huxley (HH) neuron responding to periodic inputs, we demonstrate that
the random sampling is a proper encoding method in medium frequency region
since power spectra of the reconstructed spike-trains are identical to that of
neural signals.


title: Sleep as the solution to an optimization problem

abstract:
  This paper develops a highly simplified model with which to analyze the
phenomenon of sleep. Motivated by Crick's suggestion that sleep is the brain's
way of ``taking out the trash,'' a suggestion that is supported by emerging
evidence, we consider the problem of the filling and emptying of a tank. At any
given time, the tank may take in external resource, or fill, if resource is
available at that time, or it may empty. The filling phases correspond to
information input from the environment, or input of some material in general,
while the emptying phases correspond to the processing of the resource. Given a
resource-availablility profile over some time interval $ T $, we develop a
canonical algorithm for determining the fill-empty profile that produces the
maximum quantity of processed resource at the end of the time interval. From
this algorithm, it readily follows that for a periodically oscillating
resource-availability profile, the optimal fill-empty strategy is given by a
fill period when resource is available, followed by an empty period when
resource is not. This cycling behavior is analogous to the wake-sleep cycles in
organismal life, where the generally nocturnal sleep phase is a period where
the information collected from the day's activities may be processed. The sleep
cycle is then a mechanism for the organism to process a maximal amount of
information over a daily cycle. Our model can exhibit phenomena analogous to
``microsleeps,'' and other behavior associated with breakdown in sleep
patterns.


title:
Adhesion between cells, diffusion of growth factors, and elasticity of
  the AER produce the paddle shape of the chick limb

abstract: This paper has been withdrawn


title:
Quantification and Correction of Systematic Errors Due to Detector
  Time-Averaging in Single-Molecule Tracking Experiments

abstract:
  Single-molecule tracking is a powerful way to look at the dynamic
organization of plasma membranes. However, there are some limitations to its
use. For example, it was recently observed, using numerical simulation, that
time-averaging effects inherent to the exposure time of detectors are likely to
bias the apparent motion of molecules confined in microdomains. Here, we solve
this apparently limiting issue analytically. We explore this phenomenon by
calculating its effects on the observed diffusion coefficients and domain
sizes. We demonstrate that the real parameters can be easily recovered from the
measured apparent ones. Interestingly, we find that single-molecule tracking
can be used to explore events occurring at a timescale smaller than the
exposure time.


title:
Glial activation in white matter following ischemia in the neonatal P7
  rat brain

abstract:
  This study examines cell death and proliferation in the white matter after
neonatal stroke. In post-natal day 7 injured rat, there was a marked reduction
in myelin basic protein (MBP) immunostaining mainly corresponding to numerous
pyknotic immature oligodendrocytes and TUNEL-positive astrocytes in the
ipsilateral external capsule. In contrast, a substantial restoration of MBP, as
indicated by the MBP ratio of left-toright, occurred in the cingulum at 48
(1.27 +- 0.12) and 72 (1.30 +- 0.18, p<0.05) hours of recovery as compared to
age-matched controls (1.03 +- 0.14). Ki-67 immunostaining revealed a first peak
of newly-generated cells in the dorsolateral hippocampal subventricular zone
and cingulum at 72 hours after reperfusion. Double immunofluorescence revealed
that most of the Ki-67-positive cells were astrocytes at 48 hours and NG2
pre-oligodendrocytes at 72 hours of recovery. Microglia infiltration occurs
over several days in the cingulum and a huge quantity of macrophages reached
the subcortical white matter where they engulfed immature oligodendrocytes. The
overall results suggest that the persistent activation of microglia involves a
chronic component of immunoinflammation, which overwhelms repair processes and
contributes to cystic growth in the developing brain.


title:
Universal core modules govern the dynamics of cellular regulatory
  networks

abstract: This paper contains some immature results. It have been withdrawn.


title:
Effect of channel block on the spiking activity of excitable membranes
  in a stochastic Hodgkin-Huxley model

abstract:
  The influence of intrinsic channel noise on the spontaneous spiking activity
of poisoned excitable membrane patches is studied by use of a stochastic
generalization of the Hodgkin-Huxley model. Internal noise stemming from the
stochastic dynamics of individual ion channels is known to affect the
collective properties of the whole ion channel cluster. For example, there
exists an optimal size of the membrane patch for which the internal noise alone
causes a regular spontaneous generation of action potentials. In addition to
varying the size of ion channel clusters, living organisms may adapt the
densities of ion channels in order to optimally regulate the spontaneous
spiking activity. The influence of channel block on the excitability of a
membrane patch of certain size is twofold: First, a variation of ion channel
densities primarily yields a change of the conductance level. Second, a
down-regulation of working ion channels always increases the channel noise.
While the former effect dominates in the case of sodium channel block resulting
in a reduced spiking activity, the latter enhances the generation of
spontaneous action potentials in the case of a tailored potassium channel
blocking. Moreover, by blocking some portion of either potassium or sodium ion
channels, it is possible to either increase or to decrease the regularity of
the spike train.


title:
Biophysical analysis of electric current mediated nucleoprotein
  inactivation process

abstract:
  Motivation: Its well known the use of electric current in the cleaning of
viral diseases in plants instead a deep knowledge of this phenomenas
theoretical basis is not yet available. The description of the real causes of
nucleoprotein inactivation, will contribute to the optimization of further
experiments in order to obtain more and more efficient cleaning methodologies
for starting material supplies of vegetal species micropropagation process. The
dissipated energy as heat will depend on the specific treatment applied and on
the physical properties of the vegetal tissue and viral nucleoprotein. Results:
A hyperbolic dependence between the absorbance output values, obtained during a
diagnostic micro-ELISA experiment, and the electrical power (in watts) applied
to each explant was found. The former, demonstrate the cleaning process nature
is essentially the effect over viral nucleoprotein denaturation, by means of
the heat, to which they were exposed in the thermal bath that the vegetal
tissue constitutes. Our results are consistent with mathematical developed from
theoretical frame of harmonic oscillators in which molecular machine (viral
nucleoproteins) are redefined.


title: A dichotomy for a class of cyclic delay systems

abstract:
  Two complementary analyses of a cyclic negative feedback system with delay
are considered in this paper. The first analysis applies the work by Sontag,
Angeli, Enciso and others regarding monotone control systems under negative
feedback, and it implies the global attractiveness towards an equilibrium for
arbitrary delays. The second one concerns the existence of a Hopf bifurcation
on the delay parameter, and it implies the existence of nonconstant periodic
solutions for special delay values. A key idea is the use of the Schwarzian
derivative, and its application for the study of Michaelis-Menten
nonlinearities. The positive feedback case is also addressed.


title:
Pure multiplicative stochastic resonance of anti-tumor model with
  seasonal modulability

abstract:
  The effects of pure multiplicative noise on stochastic resonance in an
anti-tumor system modulated by a seasonal external field are investigated by
using theoretical analyses of the generalized potential and numerical
simulations. For optimally selected values of the multiplicative noise
intensity quasi-symmetry of two potential minima and stochastic resonance are
observed. Theoretical results and numerical simulations are in good
quantitative agreement.


title:
Force Modulating Dynamic Disorder: Physical Theory of Catch-slip bond
  Transitions in Receptor-Ligand Forced Dissociation Experiments

abstract:
  Recently experiments showed that some adhesive receptor-ligand complexes
increase their lifetimes when they are stretched by mechanical force, while the
force increase beyond some thresholds their lifetimes decrease. Several
specific chemical kinetic models have been developed to explain the intriguing
transitions from the "catch-bonds" to the "slip-bonds". In this work we suggest
that the counterintuitive forced dissociation of the complexes is a typical
rate process with dynamic disorder. An uniform one-dimension force modulating
Agmon-Hopfield model is used to quantitatively describe the transitions
observed in the single bond P-selctin glycoprotein ligand
1(PSGL-1)$-$P-selectin forced dissociation experiments, which were respectively
carried out on the constant force [Marshall, {\it et al.}, (2003) Nature {\bf
423}, 190-193] and the force steady- or jump-ramp [Evans {\it et al.}, (2004)
Proc. Natl. Acad. Sci. USA {\bf 98}, 11281-11286] modes. Our calculation shows
that the novel catch-slip bond transition arises from a competition of the two
components of external applied force along the dissociation reaction coordinate
and the complex conformational coordinate: the former accelerates the
dissociation by lowering the height of the energy barrier between the bound and
free states (slip), while the later stabilizes the complex by dragging the
system to the higher barrier height (catch).


title:
Protein folding dynamics via quantification of kinematic energy
  landscape

abstract:
  We study folding dynamics of protein-like sequences on square lattice using
physical move set that exhausts all possible conformational changes. By
analytically solving the master equation, we follow the time-dependent
probabilities of occupancy of all 802,075 conformations of 16-mers over
7-orders of time span. We find that (i) folding rates of these protein-like
sequences of same length can differ by 4-orders of magnitude, (ii) folding
rates of sequences of the same conformation can differ by a factor of 190, and
(iii) parameters of the native structures, designability, and thermodynamic
properties are weak predictors of the folding rates, rather, basin analysis of
the kinematic energy landscape defined by the moves can provide excellent
account of the observed folding rates.

categories: q-bio.BM cond-mat.soft cond-mat.stat-mech physics.bio-ph physics.chem-ph


title:
Estimation of Amino Acid Residue Substitution Rates at Local Spatial
  Regions and Application in Protein Function Inference: A Bayesian Monte Carlo
  Approach

abstract:
  The amino acid sequences of proteins provide rich information for inferring
distant phylogenetic relationships and for predicting protein functions.
Estimating the rate matrix of residue substitutions from amino acid sequences
is also important because the rate matrix can be used to develop scoring
matrices for sequence alignment. Here we use a continuous time Markov process
to model the substitution rates of residues and develop a Bayesian Markov chain
Monte Carlo method for rate estimation. We validate our method using simulated
artificial protein sequences. Because different local regions such as binding
surfaces and the protein interior core experience different selection pressures
due to functional or stability constraints, we use our method to estimate the
substitution rates of local regions. Our results show that the substitution
rates are very different for residues in the buried core and residues on the
solvent exposed surfaces. In addition, the rest of the proteins on the binding
surfaces also have very different substitution rates from residues. Based on
these findings, we further develop a method for protein function prediction by
surface matching using scoring matrices derived from estimated substitution
rates for residues located on the binding surfaces. We show with examples that
our method is effective in identifying functionally related proteins that have
overall low sequence identity, a task known to be very challenging.


title:
Computation of protein geometry and its applications: Packing and
  function prediction

abstract:
  This chapter discusses geometric models of biomolecules and geometric
constructs, including the union of ball model, the weigthed Voronoi diagram,
the weighted Delaunay triangulation, and the alpha shapes. These geometric
constructs enable fast and analytical computaton of shapes of biomoleculres
(including features such as voids and pockets) and metric properties (such as
area and volume). The algorithms of Delaunay triangulation, computation of
voids and pockets, as well volume/area computation are also described. In
addition, applications in packing analysis of protein structures and protein
function prediction are also discussed.


title: Does Cancer Growth Depend on Surface Extension?

abstract:
  We argue that volumetric growth dynamics of a solid cancer depend on the
tumor system's overall surface extension. While this at first may seem evident,
to our knowledge, so far no theoretical argument has been presented explaining
this relationship explicitly. In here, we therefore develop a conceptual
framework based on the universal scaling law and then support our conjecture
through evaluation with experimental data.


title:
Embryonic Pattern Scaling Achieved by Oppositely Directed Morphogen
  Gradients

abstract:
  Morphogens are proteins, often produced in a localised region, whose
concentrations spatially demarcate regions of differing gene expression in
developing embryos. The boundaries of expression must be set accurately and in
proportion to the size of the one-dimensional developing field; this cannot be
accomplished by a single gradient. Here, we show how a pair of morphogens
produced at opposite ends of a developing field can solve the pattern-scaling
problem. In the most promising scenario, the morphogens effectively interact
according to the annihilation reaction $A+B\to\emptyset$ and the switch occurs
according to the absolute concentration of $A$ or $B$. In this case embryonic
markers across the entire developing field scale approximately with system
size; this cannot be achieved with a pair of non-interacting gradients that
combinatorially regulate downstream genes. This scaling occurs in a window of
developing-field sizes centred at a few times the morphogen decay length.


title:
Effects of Noise on Ecological Invasion Processes:
  Bacteriophage-mediated Competition in Bacteria

abstract:
  Pathogen-mediated competition, through which an invasive species carrying and
transmitting a pathogen can be a superior competitor to a more vulnerable
resident species, is one of the principle driving forces influencing
biodiversity in nature. Using an experimental system of bacteriophage-mediated
competition in bacterial populations and a deterministic model, we have shown
in [Joo et al 2005] that the competitive advantage conferred by the phage
depends only on the relative phage pathology and is independent of the initial
phage concentration and other phage and host parameters such as the
infection-causing contact rate, the spontaneous and infection-induced lysis
rates, and the phage burst size. Here we investigate the effects of stochastic
fluctuations on bacterial invasion facilitated by bacteriophage, and examine
the validity of the deterministic approach. We use both numerical and
analytical methods of stochastic processes to identify the source of noise and
assess its magnitude. We show that the conclusions obtained from the
deterministic model are robust against stochastic fluctuations, yet deviations
become prominently large when the phage are more pathological to the invading
bacterial strain.


title:
Scale-free foraging by primates emerges from their interaction with a
  complex environment

abstract:
  Scale-free foraging patterns are widespread among animals. These may be the
outcome of an optimal searching strategy to find scarce randomly distributed
resources, but a less explored alternative is that this behaviour may result
from the interaction of foraging animals with a particular distribution of
resources. We introduce a simple foraging model where individuals follow mental
maps and choose their displacements according to a maximum efficiency
criterion, in a spatially disordered environment containing many trees with a
heterogeneous size distribution. We show that a particular tree size frequency
distribution induces non-Gaussian movement patterns with multiple spatial
scales (L\'evy walks). These results are consistent with tree size variation
and Spider monkey (Ateles geoffroyi) foraging patterns. We discuss the
consequences that our results may have for the patterns of seed dispersal by
foraging primates.


title:
Towards an understanding of lineage specification in hematopoietic stem
  cells: A mathematical model for the interaction of transcription factors
  GATA-1 and PU.1

abstract:
  In addition to their self-renewal capabilities, hematopoietic stem cells
guarantee the continuous supply of fully differentiated, functional cells of
various types in the peripheral blood. The process which controls
differentiation into the different lineages of the hematopoietic system
(erythroid, myeloid, lymphoid) is referred to as lineage specification. It
requires a potentially multi-step decision sequence which determines the fate
of the cells and their successors. It is generally accepted that lineage
specification is regulated by a complex system of interacting transcription
factors. However, the underlying principles controlling this regulation are
currently unknown.
  Here, we propose a simple quantitative model describing the interaction of
two transcription factors. This model is motivated by experimental observations
on the transcription factors GATA-1 and PU.1, both known to act as key
regulators and potential antagonists in the erythroid vs. myeloid
differentiation processes of hematopoietic progenitor cells. We demonstrate the
ability of the model to account for the observed switching behavior of a
transition from a state of low expression of both factors (undifferentiated
state) to the dominance of one factor (differentiated state). Depending on the
parameter choice, the model predicts two different possibilities to explain the
experimentally suggested, stem cell characterizing priming state of low level
co-expression. Whereas increasing transcription rates are sufficient to induce
differentiation in one scenario, an additional system perturbation (by
stochastic fluctuations or directed impulses) of transcription factor levels is
required in the other case.


title: Knowledge-based energy functions for computational studies of proteins

abstract:
  This chapter discusses theoretical framework and methods for developing
knowledge-based potential functions essential for protein structure prediction,
protein-protein interaction, and protein sequence design. We discuss in some
details about the Miyazawa-Jernigan contact statistical potential,
distance-dependent statistical potentials, as well as geometric statistical
potentials. We also describe a geometric model for developing both linear and
non-linear potential functions by optimization. Applications of knowledge-based
potential functions in protein-decoy discrimination, in protein-protein
interactions, and in protein design are then described. Several issues of
knowledge-based potential functions are finally discussed.


title:
Interstrand pairing patterns in $\beta$-barrel membrane proteins: the
  positive-outside rule, aromatic rescue, and strand registration prediction

abstract:
  $\beta$-barrel membrane proteins are found in the outer membrane of
gram-negative bacteria, mitochondria, and chloroplasts. We have developed
probabilistic models to quantify propensities of residues for different spatial
locations and for interstrand pairwise contact interactions involving strong
H-bonds, side-chain interactions, and weak H-bonds. The propensity values and
p-values measuring statistical significance are calculated exactly by
analytical formulae we have developed. Contrary to the ``positive-inside'' rule
for helical membrane proteins, $\beta$-barrel membrane proteins follow a
significant albeit weaker ``positive-outside'' rule, in that the basic residues
Arg and Lys are disproportionately favored in the extracellular cap region and
disfavored in the periplasmic cap region. Different residue pairs prefer strong
backbone H-bonded interstrand pairings (e.g. Gly-Aromatic) or non-H-bonded
pairings (e.g. Aromatic-Aromatic). In addition, Tyr and Phe participate in
aromatic rescue by shielding Gly from polar environments. These propensities
can be used to predict the registration of strand pairs, an important task for
the structure prediction of $\beta$-barrel membrane proteins. Our accuracy of
44% is considerably better than random (7%) and other studies. Our results
imply several experiments that can help to elucidate the mechanisms of in vitro
and in vivo folding of $\beta$-barrel membrane proteins. See supplementary
material after the bibliography for detailed techniques.


title:
Gradient learning in spiking neural networks by dynamic perturbation of
  conductances

abstract:
  We present a method of estimating the gradient of an objective function with
respect to the synaptic weights of a spiking neural network. The method works
by measuring the fluctuations in the objective function in response to dynamic
perturbation of the membrane conductances of the neurons. It is compatible with
recurrent networks of conductance-based model neurons with dynamic synapses.
The method can be interpreted as a biologically plausible synaptic learning
rule, if the dynamic perturbations are generated by a special class of
``empiric'' synapses driven by random spike trains from an external source.


title:
Empirical Potential Function for Simplified Protein Models: Combining
  Contact and Local Sequence-Structure Descriptors

abstract:
  An effective potential function is critical for protein structure prediction
and folding simulation. Simplified protein models such as those requiring only
$C_\alpha$ or backbone atoms are attractive because they enable efficient
search of the conformational space. We show residue specific reduced discrete
state models can represent the backbone conformations of proteins with small
RMSD values. However, no potential functions exist that are designed for such
simplified protein models. In this study, we develop optimal potential
functions by combining contact interaction descriptors and local
sequence-structure descriptors. The form of the potential function is a
weighted linear sum of all descriptors, and the optimal weight coefficients are
obtained through optimization using both native and decoy structures. The
performance of the potential function in test of discriminating native protein
structures from decoys is evaluated using several benchmark decoy sets. Our
potential function requiring only backbone atoms or $C_\alpha$ atoms have
comparable or better performance than several residue-based potential functions
that require additional coordinates of side chain centers or coordinates of all
side chain atoms. By reducing the residue alphabets down to size 5 for local
structure-sequence relationship, the performance of the potential function can
be further improved. Our results also suggest that local sequence-structure
correlation may play important role in reducing the entropic cost of protein
folding.


title: Magnetic Susceptibility: Solutions, Emulsions, and Cells

abstract:
  Differences in magnetic susceptibility between various compartments in
heterogeneous samples can introduce unanticipated complications to NMR spectra.
On the other hand, an understanding of these effects at the level of the
underlying physical principles has led to the development of several
experimental techniques that provide data on cellular function that are unique
to NMR spectroscopy. To illustrate some key features of susceptibility effects
we present, among a more general overview, results obtained with red blood
cells and a recently described model system involving diethyl phthalate in
water. This substance forms a relatively stable emulsion in water and yet it
has a significant solubility of 5 mmol/L at room temperature; thus, the NMR
spectrum has twice as many resonances as would be expected for a simple
solution. What determines the relative intensities of the two families of peaks
and can their frequencies be manipulated experimentally in a predictable way?
The theory used to interpret the NMR spectra from the model system and cells
was first developed in the context of electrostatics nearly a century ago, and
yet some of its underlying assumptions now warrant closer scrutiny. While this
insight is used in a practical way in this article, the accompanying article
deals with the mathematics and physics behind this new analysis.


title: Evolutionary dynamics on degree-heterogeneous graphs

abstract:
  The evolution of two species with different fitness is investigated on
degree-heterogeneous graphs. The population evolves either by one individual
dying and being replaced by the offspring of a random neighbor (voter model
(VM) dynamics) or by an individual giving birth to an offspring that takes over
a random neighbor node (invasion process (IP) dynamics). The fixation
probability for one species to take over a population of N individuals depends
crucially on the dynamics and on the local environment. Starting with a single
fitter mutant at a node of degree k, the fixation probability is proportional
to k for VM dynamics and to 1/k for IP dynamics.


title:
Fuzzy Cognitive Maps Of Local People Impacted By Dam Construction: Their
  Demands Regarding Resettlement

abstract:
  Fuzzy cognitive mapping was used to understand the wants and desires of local
people before resettlement. Variables that the affected people think will
increase their welfare during and after dam construction were determined.
Simulations were done with their cumulative social cognitive map to determine
which policy options would most increase their welfare. The construction of
roads, job opportunities, advance payment of condemnation value, and schools
are central variables that had the most effect on increasing people's income
and welfare. The synergistic effects of variables demonstrated that the
implementation of different policies not only add cumulatively to the people's
welfare but also have an increased effect.


title: Perceptions of Complex Systems Are Governed by Power Laws

abstract:
  Many networks in natural and human-made systems exhibit scale-free properties
and are small worlds. Now we show that people's understanding of complex
systems in their cognitive maps also follow a scale-free topology. People focus
on a few attributes, relating these with many other things in the system. Many
more attributes have very few connections. People use relatively short
explanations to describe events; their cognitive map is a small world with less
than six degrees of separation. These findings may help us to better understand
people's perceptions, especially when it comes to decision-making, conflict
resolution, politics and management.


title:
Time-dependent perturbation theory for vibrational energy relaxation and
  dephasing in peptides and proteins

abstract:
  Without invoking the Markov approximation, we derive formulas for vibrational
energy relaxation (VER) and dephasing for an anharmonic system oscillator using
a time-dependent perturbation theory. The system-bath Hamiltonian contains more
than the third order coupling terms since we take a normal mode picture as a
zeroth order approximation. When we invoke the Markov approximation, our theory
reduces to the Maradudin-Fein formula which is used to describe VER properties
of glass and proteins. When the system anharmonicity and the renormalization
effect due to the environment vanishes, our formulas reduce to those derived by
Mikami and Okazaki invoking the path-integral influence functional method [J.
Chem. Phys. 121 (2004) 10052]. We apply our formulas to VER of the amide I mode
of a small amino-acide like molecule, N-methylacetamide, in heavy water.


title: A Comparative Analysis of Influenza Vaccination Programs

abstract:
  The threat of avian influenza and the 2004-2005 influenza vaccine supply
shortage in the United States has sparked a debate about optimal vaccination
strategies to reduce the burden of morbidity and mortality caused by the
influenza virus. We present a comparative analysis of two classes of suggested
vaccination strategies: mortality-based strategies that target high risk
populations and morbidity-based that target high prevalence populations.
Applying the methods of contact network epidemiology to a model of disease
transmission in a large urban population, we evaluate the efficacy of these
strategies across a wide range of viral transmission rates and for two
different age-specific mortality distributions. We find that the optimal
strategy depends critically on the viral transmission level (reproductive rate)
of the virus: morbidity-based strategies outperform mortality-based strategies
for moderately transmissible strains, while the reverse is true for highly
transmissible strains. These results hold for a range of mortality rates
reported for prior influenza epidemics and pandemics. Furthermore, we show that
vaccination delays and multiple introductions of disease into the community
have a more detrimental impact on morbidity-based strategies than
mortality-based strategies. If public health officials have reasonable
estimates of the viral transmission rate and the frequency of new introductions
into the community prior to an outbreak, then these methods can guide the
design of optimal vaccination priorities. When such information is unreliable
or not available, as is often the case, this study recommends mortality-based
vaccination priorities.


title: Extinction in genetic bit-string model with sexual recombination

abstract:
  We have analyzed the relations between the mutational pressure, recombination
and selection pressure in the bit-string model with sexual reproduction. For
specific sets of these parameters we have found three phase transitions with
one phase where populations can survive. In this phase, recombination enhances
the survival probability. Even if recombination is associated, to some extent,
with additional mutations it could be advantageous to reproduction, indicating
that the frequencies of recombinations and recombination-associated mutations
can self-organize in Nature. Partitioning the diploid genome into pairs of
chromosomes independently assorted during gamete production enables
recombinations between groups of genes without the risk of mutations and is
also advantageous for the strategy of sexual reproduction.


title: Optimal Dynamical Range of Excitable Networks at Criticality

abstract:
  A recurrent idea in the study of complex systems is that optimal information
processing is to be found near bifurcation points or phase transitions.
However, this heuristic hypothesis has few (if any) concrete realizations where
a standard and biologically relevant quantity is optimized at criticality. Here
we give a clear example of such a phenomenon: a network of excitable elements
has its sensitivity and dynamic range maximized at the critical point of a
non-equilibrium phase transition. Our results are compatible with the essential
role of gap junctions in olfactory glomeruli and retinal ganglionar cell
output. Synchronization and global oscillations also appear in the network
dynamics. We propose that the main functional role of electrical coupling is to
provide an enhancement of dynamic range, therefore allowing the coding of
information spanning several orders of magnitude. The mechanism could provide a
microscopic neural basis for psychophysical laws.

categories: q-bio.NC cond-mat.dis-nn nlin.CG physics.bio-ph


title: Quantifying the information transmitted in a single stimulus

abstract:
  Shannon mutual information provides a measure of how much information is, on
average, contained in a set of neural activities about a set of stimuli. It has
been extensively used to study neural coding in different brain areas. To apply
a similar approach to investigate single stimulus encoding, we need to
introduce a quantity specific for a single stimulus. This quantity has been
defined in literature by four different measures, but none of them satisfies
the same intuitive properties (non-negativity, additivity), that characterize
mutual information. We present here a detailed analysis of the different
meanings and properties of these four definitions. We show that all these
measures satisfy, at least, a weaker additivity condition, i.e. limited to the
response set. This allows us to use them for analysing correlated coding, as we
illustrate in a toy-example from hippocampal place cells.


title: Food-chain competition influences gene's size

abstract:
  We have analysed an effect of the Bak-Sneppen predator-prey food-chain
self-organization on nucleotide content of evolving species. In our model,
genomes of the species under consideration have been represented by their
nucleotide genomic fraction and we have applied two-parameter Kimura model of
substitutions to include the changes of the fraction in time. The initial
nucleotide fraction and substitution rates were decided with the help of random
number generator. Deviation of the genomic nucleotide fraction from its
equilibrium value was playing the role of the fitness parameter, $B$, in
Bak-Sneppen model. Our finding is, that the higher is the value of the
threshold fitness, during the evolution course, the more frequent are large
fluctuations in number of species with strongly differentiated nucleotide
content; and it is more often the case that the oldest species, which survive
the food-chain competition, might have specific nucleotide fraction making
possible generating long genes


title:
Mechanochemical coupling of kinesin studied with the neck linker swing
  model

abstract:
  We have proposed the neck linker swing model to investigate the mechanism of
mechanochemical coupling of kinesin. The Michaelis-Menten-like curve for
velocity vs ATP concentration at different loads has been obtained, which is in
agreement with experiments. We have predicted that Michaelis constant doesn't
increase monotonically and an elastic instability will happen with increasing
of applied force.


title: The Activity Reaction Core and Plasticity of Metabolic Networks

abstract:
  Understanding the system level adaptive changes taking place in an organism
in response to variations in the environment is a key issue of contemporary
biology. Current modeling approaches such as the constraint-based flux balance
analyses (FBA) have proved highly successful in analyzing the capabilities of
cellular metabolism, including its capacity to predict deletion phenotypes, the
ability to calculate the relative flux values of metabolic reactions and the
properties of alternate optimal growth states. Here, we use FBA to thoroughly
assess the activity of the Escherichia coli, Helicobacter pylori, and
Saccharomyces cerevisiae metabolism in 30,000 diverse simulated environments.
We identify a set of metabolic reactions forming a connected metabolic core
that carry non-zero fluxes under all growth conditions, and whose flux
variations are highly correlated. Furthermore, we find that the enzymes
catalyzing the core reactions display a considerably higher fraction of
phenotypic essentiality and evolutionary conservation than those catalyzing
non-core reactions. Cellular metabolism is characterized by a large number of
species-specific conditionally-active reactions organized around an
evolutionary conserved always active metabolic core. Finally, we find that most
current antibiotics interfering with the bacterial metabolism target the core
enzymes, indicating that our findings may have important implications for
antimicrobial drug target discovery.

categories: q-bio.MN cond-mat.dis-nn q-bio.CB q-bio.QM


title:
Quantum mechanical calculation of the effects of stiff and rigid
  constraints in the conformational equilibrium of the Alanine dipeptide

abstract:
  If constraints are imposed on a macromolecule, two inequivalent classical
models may be used: the stiff and the rigid one. This work studies the effects
of such constraints on the Conformational Equilibrium Distribution (CED) of the
model dipeptide HCO-L-Ala-NH2 without any simplifying assumption. We use ab
initio Quantum Mechanics calculations including electron correlation at the MP2
level to describe the system, and we measure the conformational dependence of
all the correcting terms to the naive CED based in the Potential Energy Surface
(PES) that appear when the constraints are considered. These terms are related
to mass-metric tensors determinants and also occur in the Fixman's compensating
potential. We show that some of the corrections are non-negligible if one is
interested in the whole Ramachandran space. On the other hand, if only the
energetically lower region, containing the principal secondary structure
elements, is assumed to be relevant, then, all correcting terms may be
neglected up to peptides of considerable length. This is the first time, as far
as we know, that the analysis of the conformational dependence of these
correcting terms is performed in a relevant biomolecule with a realistic
potential energy function.


title: Forced-unfolding and force-quench refolding of RNA hairpins

abstract:
  Using coarse-grained model we have explored forced-unfolding of RNA hairpin
as a function of $f_S$ and the loading rate ($r_f$). The simulations and
theoretical analysis have been done without and with the handles that are
explicitly modeled by semiflexible polymer chains. The mechanisms and time
scales for denaturation by temperature jump and mechanical unfolding are vastly
different. The directed perturbation of the native state by $f_S$ results in a
sequential unfolding of the hairpin starting from their ends whereas thermal
denaturation occurs stochastically. From the dependence of the unfolding rates
on $r_f$ and $f_S$ we show that the position of the unfolding transition state
(TS) is not a constant but moves dramatically as either $r_f$ or $f_S$ is
changed. The TS movements are interpreted by adopting the Hammond postulate for
forced-unfolding. Forced-unfolding simulations of RNA, with handles attached to
the two ends, show that the value of the unfolding force increases (especially
at high pulling speeds) as the length of the handles increases. The pathways
for refolding of RNA from stretched initial conformation, upon quenching $f_S$
to the quench force $f_Q$, are highly heterogeneous. The refolding times, upon
force quench, are at least an order of magnitude greater than those obtained by
temperature quench. The long $f_Q$-dependent refolding times starting from
fully stretched states are analyzed using a model that accounts for the
microscopic steps in the rate limiting step which involves the trans to gauche
transitions of the dihedral angles in the GAAA tetraloop. The simulations with
explicit molecular model for the handles show that the dynamics of force-quench
refolding is strongly dependent on the interplay of their contour length and
the persistence length, and the RNA persistence length.


title: Hierarchy of events in protein folding: beyond the Go model

abstract:
  Simplified Go models, where only native contacts interact favorably, have
proven useful to characterize some aspects of the folding of small proteins.
The success of these models is limited by the fact that all residues interact
in the same way, so that the folding features of a protein are determined only
by the geometry of its native conformation. We present an extended version of a
C-alpha based Go model where different residues interact with different
energies. The model is used to calculate the thermodynamics of three small
proteins (Protein G, SrcSH3 and CI2) and the effect of mutations on the
wildtype sequence. The model allows to investigate some of the most
controversial areas in protein folding such as its earliest stages, a subject
which has lately received particular attention. The picture which emerges for
the three proteins under study is that of a hierarchical process, where local
elementary structures (LES) (not necessarily coincident with elements of
secondary structure) are formed at the early stages of the folding and drive
the protein, through the transition state and the postcritical folding nucleus
(FN), resulting from the docking of the LES, to the native conformation.


title:
Thresholds, long delays and stability from generalized allosteric effect
  in protein networks

abstract:
  Post-transductional modifications tune the functions of proteins and regulate
the collective dynamics of biochemical networks that determine how cells
respond to environmental signals. For example, protein phosphorylation and
nitrosylation are well-known to play a pivotal role in the intracellular
transduction of activation and death signals. A protein can have multiple sites
where chemical groups can reversibly attach in processes such as
phosphorylation or nitrosylation. A microscopic description of these processes
must take into account the intrinsic probabilistic nature of the underlying
reactions. We apply combinatorial considerations to standard enzyme kinetics
and in this way we extend to the dynamic regime a simplified version of the
traditional models on the allosteric regulation of protein functions. We link a
generic modification chain to a downstream Michaelis-Menten enzymatic reaction
and we demonstrate numerically that this accounts both for thresholds and long
time delays in the conversion of the substrate by the enzyme. The proposed
mechanism is stable and robust and the higher the number of modification sites,
the greater the stability. We show that a high number of modification sites
converts a fast reaction into a slow process, and the slowing down depends on
the number of sites and may span many orders of magnitude; in this way
multisite modification of proteins stands out as a general mechanism that
allows the transfer of information from the very short time scales of enzyme
reactions (milliseconds) to the long time scale of cell response (hours).


title:
Substructural cooperativity and parallel versus sequential events during
  protein unfolding

abstract:
  According to the 'old view', proteins fold along well-defined sequential
pathways, whereas the 'new view' sees protein folding as a highly parallel
stochastic process on funnel-shaped energy landscapes. We have analyzed
parallel and sequential processes on a large number of Molecular Dynamics
unfolding trajectories of the protein CI2 at high temperatures. Using rigorous
statistical measures, we quantify the degree of sequentiality on two structural
levels. The unfolding process is highly parallel on the microstructural level
of individual contacts. On a coarser, macrostructural level of contact
clusters, characteristic parallel and sequential events emerge. These
characteristic events can be understood from loop-closure dependencies between
the contact clusters. A correlation analysis of the unfolding times of the
contacts reveals a high degree of substructural cooperativity within the
contact clusters.


title:
A simple measure of native-state topology and chain connectivity
  predicts the folding rates of two-state proteins with and without crosslinks

abstract:
  The folding rates of two-state proteins have been found to correlate with
simple measures of native-state topology. The most prominent among these
measures is the relative contact order (CO), which is the average CO or
'localness' of all contacts in the native protein structure, divided by the
chain length. Here, we test whether such measures can be generalized to capture
the effect of chain crosslinks on the folding rate. Crosslinks change the chain
connectivity and therefore also the localness of some of the the native
contacts. These changes in localness can be taken into account by the
graph-theoretical concept of effective contact order (ECO). The relative ECO,
however, the natural extension of the relative CO for proteins with crosslinks,
overestimates the changes in the folding rates caused by crosslinks. We suggest
here a novel measure of native-state topology, the relative logCO, and its
natural extension, the relative logECO. The relative logCO is the average value
for the logarithm of the CO of all contacts, divided by the logarithm of the
chain length. The relative log(E)CO reproduces the folding rates of a set of 26
two-state proteins without crosslinks with essentially the same high
correlation coefficient as the relative CO. In addition, it also captures the
folding rates of 8 two-state proteins with crosslinks.


title: Taxis Equations for Amoeboid Cells

abstract:
  The classical macroscopic chemotaxis equations have previously been derived
from an individual-based description of the tactic response of cells that use a
"run-and-tumble" strategy in response to environmental cues. Here we derive
macroscopic equations for the more complex type of behavioral response
characteristic of crawling cells, which detect a signal, extract directional
information from a scalar concentration field, and change their motile behavior
accordingly. We present several models of increasing complexity for which the
derivation of population-level equations is possible, and we show how
experimentally-measured statistics can be obtained from the transport equation
formalism. We also show that amoeboid cells that do not adapt to constant
signals can still aggregate in steady gradients, but not in response to
periodic waves. This is in contrast to the case of cells that use a
"run-and-tumble" strategy, where adaptation is essential.


title: Thermal unfolding of proteins

abstract:
  Thermal unfolding of proteins is compared to folding and mechanical
stretching in a simple topology-based dynamical model. We define the unfolding
time and demonstrate its low-temperature divergence. Below a characteristic
temperature, contacts break at separate time scales and unfolding proceeds
approximately in a way reverse to folding. Features in these scenarios agree
with experiments and atomic simulations on titin.


title: Exploitation dynamics of fish stocks

abstract:
  I address the question of the fluctuations in fishery landings. Using the
fishery statistics time-series collected by the Food and Agriculture
Organization of the United Nations since the early 1950s, I here analyze
fishing activities and find two scaling features of capture fisheries
production: (i) the standard deviation of growth rate of the domestically
landed catches decays as a power-law function of country landings with an
exponent of value 0.15; (ii) the average number of fishers in a country scales
to the 0.7 power of country landings. I show how these socio-ecological
patterns may be related, yielding a scaling relation between these exponents.
The predicted scaling relation implies that the width of the annual per capita
growth-rate distribution scales to the 0.2 power of country landings, i.e.
annual fluctuations in per capita landed catches increase with increased per
capita catches in highly producing countries. Beside the scaling behavior, I
report that fluctuations in the annual domestic landings have increased in the
last 30 years, while the mean of the annual growth rate declined significantly
after 1972.


title:
Statistical Properties of the Interbeat Interval Cascade in Human
  Subjects

abstract:
  Statistical properties of interbeat intervals cascade are evaluated by
considering the joint probability distribution $P(\Delta x_2,\tau_2;\Delta
x_1,\tau_1)$ for two interbeat increments $\Delta x_1$ and $\Delta x_2$ of
different time scales $\tau_1$ and $\tau_2$. We present evidence that the
conditional probability distribution $P(\Delta x_2,\tau_2|\Delta x_1,\tau_1)$
may obey a Chapman-Kolmogorov equation. The corresponding Kramers-Moyal (KM)
coefficients are evaluated. It is shown that while the first and second KM
coefficients, i.e., the drift and diffusion coefficients, take on well-defined
and significant values, the higher-order coefficients in the KM expansion are
very small. As a result, the joint probability distributions of the increments
in the interbeat intervals obey a Fokker-Planck equation. The method provides a
novel technique for distinguishing the two classes of subjects in terms of the
drift and diffusion coefficients, which behave differently for two classes of
the subjects, namely, healthy subjects and those with congestive heart failure.


title:
New Computational Approaches to Analysis of Interbeat Intervals in Human
  Subjects

abstract:
  We investigate the Markov nature, Cascade of information from large time
scale to small scale and extended self similarity properties of the beat to
beat fluctuations of healthy subjects as well as those with congestive heart
failure. To check the Markov nature, we use a novel inverse method that
utilizes a set of data to construct a simple equation that governs the
stochastic process for which the data have been measured, hence enabling us to
reconstruct the stochastic process. The inverse method provides a novel
technique for distinguishing the two classes of subjects in terms of a drift
and a diffusion coefficients which behave completely differently for the two
classes of subjects.To investigate the cascade of information from large to
small time scales we also analyze the statistical properties of interbeat
intervals cascade by considering the joint probability distribution for two
interbeat increments. As a result, the joint probability distributions of the
increments in the interbeat intervals obey a Fokker-Planck equation. Finally we
analyze the extended self-similarity (ESS) in the beat-to-beat fluctuations in
the heart rates of healthy and congestive heart failure subjects.The proposed
methods provide the novel techniques for distinguishing the two classes of
subjects in terms of the drift and diffusion coefficients, intermittency
exponents which behave differently for two classes of the subjects, namely,
healthy subjects and those with congestive heart failure.


title: Structural Kinetic Modeling of Metabolic Networks

abstract:
  To develop and investigate detailed mathematical models of cellular metabolic
processes is one of the primary challenges in systems biology. However, despite
considerable advance in the topological analysis of metabolic networks,
explicit kinetic modeling based on differential equations is still often
severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and
their associated parameter values. Here we propose a method that aims to give a
detailed and quantitative account of the dynamical capabilities of metabolic
systems, without requiring any explicit information about the particular
functional form of the rate equations. Our approach is based on constructing a
local linear model at each point in parameter space, such that each element of
the model is either directly experimentally accessible, or amenable to a
straightforward biochemical interpretation. This ensemble of local linear
models, encompassing all possible explicit kinetic models, then allows for a
systematic statistical exploration of the comprehensive parameter space. The
method is applied to two paradigmatic examples: The glycolytic pathway of yeast
and a realistic-scale representation of the photosynthetic Calvin cycle.


title:
The Bacterial Chemotactic Response Reflects a Compromise Between
  Transient and Steady State Behavior

abstract:
  Swimming bacteria detect chemical gradients by performing temporal
comparisons of recent measurements of chemical concentration. These comparisons
are described quantitatively by the chemotactic response function, which we
expect to optimize chemotactic behavioral performance. We identify two
independent chemotactic performance criteria: in the short run, a favorable
response function should move bacteria up chemoattractant gradients, while in
the long run, bacteria should aggregate at peaks of chemoattractant
concentration. Surprisingly, these two criteria conflict, so that when one
performance criterion is most favorable, the other is unfavorable. Since both
types of behavior are biologically relevant, we include both behaviors in a
composite optimization that yields a response function that closely resembles
experimental measurements. Our work suggests that the bacterial chemotactic
response function can be derived from simple behavioral considerations, and
sheds light on how the response function contributes to chemotactic
performance.


title: CFinder: Locating cliques and overlapping modules in biological networks

abstract:
  Summary: Most cellular tasks are performed not by individual proteins, but by
groups of functionally associated proteins, often referred to as modules. In a
protein assocation network modules appear as groups of densely interconnected
nodes, also called communities or clusters. These modules often overlap with
each other and form a network of their own, in which nodes (links) represent
the modules (overlaps). We introduce CFinder, a fast program locating and
visualizing overlapping, densely interconnected groups of nodes in undirected
graphs, and allowing the user to easily navigate between the original graph and
the web of these groups. We show that in gene (protein) association networks
CFinder can be used to predict the function(s) of a single protein and to
discover novel modules. CFinder is also very efficient for locating the cliques
of large sparse graphs.
  Availability: CFinder (for Windows, Linux, and Macintosh) and its manual can
be downloaded from http://angel.elte.hu/clustering.
  Contact: cfinder@angel.elte.hu