title:
Thermal effects in stretching of Go-like models of titin and secondary
  structures

abstract:
  The effect of temperature on mechanical unfolding of proteins is studied
using a Go-like model with a realistic contact map and Lennard-Jones contact
interactions. The behavior of the I27 domain of titin and its serial repeats is
contrasted to that of simple secondary structures. In all cases thermal
fluctuations accelerate the unraveling process, decreasing the unfolding force
nearly linearly at low temperatures. However differences in bonding geometry
lead to different sensitivity to temperature and different changes in the
unfolding pattern. Due to its special native state geometry titin is much more
thermally and elastically stable than the secondary structures. At low
temperatures serial repeats of titin show a parallel unfolding of all domains
to an intermediate state, followed by serial unfolding of the domains. At high
temperatures all domains unfold simultaneously and the unfolding distance
decreases monotonically with the contact order, that is the sequence distance
between the amino acids that form the native contact.


title: Results and Limitations of the Soliton Theory of DNA Transcription

abstract:
  It has been suggested by several authors that nonlinear excitations, in
particular solitary waves, could play a fundamental functional role in the
process of DNA transcription, effecting the opening of the double chain needed
for RNA Polymerase to be able to copy the genetic code. Some models have been
proposed to model the relevant DNA dynamics in terms of a reduced number of
effective degrees of freedom. Here I discuss advantages and disadvantages of
such an approach, and discuss in more detail one of the models, i.e. the one
proposed by Yakushevich.


title: Fast Computation with Neural Oscillators

abstract:
  Artificial spike-based computation, inspired by models of computations in the
central nervous system, may present significant performance advantages over
traditional methods for specific types of large scale problems. In this paper,
we study new models for two common instances of such computation,
winner-take-all and coincidence detection. In both cases, very fast convergence
is achieved independent of initial conditions, and network complexity is linear
in the number of inputs.


title:
A Computational Algebra Approach to the Reverse Engineering of Gene
  Regulatory Networks

abstract:
  This paper proposes a new method to reverse engineer gene regulatory networks
from experimental data. The modeling framework used is time-discrete
deterministic dynamical systems, with a finite set of states for each of the
variables. The simplest examples of such models are Boolean networks, in which
variables have only two possible states. The use of a larger number of possible
states allows a finer discretization of experimental data and more than one
possible mode of action for the variables, depending on threshold values.
Furthermore, with a suitable choice of state set, one can employ powerful tools
from computational algebra, that underlie the reverse-engineering algorithm,
avoiding costly enumeration strategies. To perform well, the algorithm requires
wildtype together with perturbation time courses. This makes it suitable for
small to meso-scale networks rather than networks on a genome-wide scale. The
complexity of the algorithm is quadratic in the number of variables and cubic
in the number of time points. The algorithm is validated on a recently
published Boolean network model of segment polarity development in Drosophila
melanogaster.


title: Genetic Paralog Analysis and Simulations

abstract:
  Using Monte Carlo methods, we simulated the effects of bias in generation and
elimination of paralogs on the size distribution of paralog groups. It was
found that the function describing the decay of the number of paralog groups
with their size depends on the ratio between the probability of duplications of
genes and their deletions, which corresponds to different selection pressures
on the genome size. Slightly different slopes of curves describing the decay of
the number of paralog groups with their size were also observed when the
threshold of homology between paralogous sequences was changed.


title: Bi-Phasic Vesicles: instability induced by adsorption of proteins

abstract:
  The recent discovery of a lateral organization in cell membranes due to small
structures called 'rafts' has motivated a lot of biological and
physico-chemical studies. A new experiment on a model system has shown a
spectacular budding process with the expulsion of one or two rafts when one
introduces proteins on the membrane. In this paper, we give a physical
interpretation of the budding of the raft phase. An approach based on the
energy of the system including the presence of proteins is used to derive a
shape equation and to study possible instabilities. This model shows two
different situations which are strongly dependent on the nature of the
proteins: a regime of easy budding when the proteins are strongly coupled to
the membrane and a regime of difficult budding.


title: Plausible models for propagation of the SARS virus

abstract:
  Using daily infection data for Hong Kong we explore the validity of a variety
of models of disease propagation when applied to the SARS epidemic. Surrogate
data methods show that simple random models are insufficient and that the
standard epidemic susceptible-infected-removed model does not fully account for
the underlying variability in the observed data. As an alternative, we consider
a more complex small world network model and show that such a structure can be
applied to reliably produce simulations quantitative similar to the true data.
The small world network model not only captures the apparently random
fluctuation in the reported data, but can also reproduces mini-outbreaks such
as those caused by so-called ``super-spreaders'' and in the Hong Kong housing
estate Amoy Gardens.


title: Extinction dynamics of Lotka-Volterra ecosystems on evolving networks

abstract:
  We study a model of a multi-species ecosystem described by
Lotka-Volterra-like equations. Interactions among species form a network whose
evolution is determined by the dynamics of the model. Numerical simulations
show power-law distribution of intervals between extinctions, but only for
ecosystems with sufficient variability of species and with networks of
connectivity above certain threshold that is very close to the percolation
threshold of the network. Effect of slow environmental changes on extinction
dynamics, degree distribution of the network of interspecies interactions, and
some emergent properties of our model are also examined.


title:
Galilean Satellites as Sites for Incipient Life, and the Earth as its
  Shelter

abstract:
  Numerous problems connected with an assumption of the life origin on the
Earth do not arise on Galilean satellites. Here, in presence of a practically
non-salt water and of a great deal (~5-10%) of abiogenic organics, a great
diversity of conditions, which are unthinkable for the Earth, were realized
more than once. They were caused by global electrochemical processes in the
magnetic field presence what could entail an absolute enantiomeric synthesis.
The subsequent explosions of the satellites' icy envelopes saturated by the
electrolysis products resulted in appearance of hot massive atmospheres and
warm deep oceans and ejection of the dirty ice fragments (=comet nuclei), what
led to the material exchange with other bodies, etc.


title: Modularity "for free" in genome architecture?

abstract:
  Background: Recent models of genome-proteome evolution have shown that some
of the key traits displayed by the global structure of cellular networks might
be a natural result of a duplication-diversification (DD) process. One of the
consequences of such evolution is the emergence of a small world architecture
together with a scale-free distribution of interactions. Here we show that the
domain of parameter space were such structure emerges is related to a phase
transition phenomenon. At this transition point, modular architecture
spontaneously emerges as a byproduct of the DD process.
  Results: Although the DD models lack any functionality and are thus free from
meeting functional constraints, they show the observed features displayed by
the real proteome maps when tuned close to a sharp transition point separating
a highly connected graph from a disconnected system. Close to such boundary,
the maps are shown to display scale-free hierarchical organization, behave as
small worlds and exhibit modularity.
  Conclusions: It is conjectured that natural selection tuned the average
connectivity in such a way that the network reaches a sparse graph of
connections. One consequence of such scenario is that the scaling laws and the
essential ingredients for building a modular net emerge for free close to such
transition.


title: Specific protein-protein binding in many-component mixtures of proteins

abstract:
  Proteins must bind to specific other proteins in vivo in order to function.
The proteins must bind only to one or a few other proteins of the of order a
thousand proteins typically present in vivo. Using a simple model of a protein,
specific binding in many component mixtures is studied. It is found to be a
demanding function in the sense that it demands that the binding sites of the
proteins be encoded by long sequences of bits, and the requirement for specific
binding then strongly constrains these sequences. This is quantified by the
capacity of proteins of a given size (sequence length), which is the maximum
number of specific-binding interactions possible in a mixture. This calculation
of the maximum number possible is in the same spirit as the work of Shannon and
others on the maximum rate of communication through noisy channels.


title: Modeling DNA Conformational Transformations on the Mesoscopic Scales

abstract:
  The approach for the description of the DNA conformational transformations on
the mesoscopic scales in the frame of the double helix is presented. Due to
consideration of the joint motions of DNA structural elements along the
conformational pathways the models for different transformations may be
constructed in the unifying two-component form. One component of the model is
the degree of freedom of the elastic rod and another component -- the effective
coordinate of the conformational transformation. The internal and external
model components are interrelated, as it is characteristic for the DNA
structure organization. It is shown that the kinetic energy of the
conformational transformation of heterogeneous DNA may be put in homogeneous
form. In the frame of the developed approach the static excitations of the DNA
structure under the transitions between the stable states are found for
internal and external components. The comparison of the data obtained with the
experiment on intrinsic DNA deformability shows good qualitative agreement. The
conclusion is made that the found excitations in the DNA structure may be
classificated as the static conformational solitons.


title:
Ionic effect on combing of single DNA molecules and observation of their
  force-induced melting by fluorescence microscopy

abstract:
  Molecular combing is a powerful and simple method for aligning DNA molecules
onto a surface. Using this technique combined with fluorescence microscopy, we
observed that the length of lambda-DNA molecules was extended to about 1.6
times their contour length (unextended length, 16.2 micrometers) by the combing
method on hydrophobic polymethylmetacrylate (PMMA) coated surfaces. The effects
of sodium and magnesium ions and pH of the DNA solution were investigated.
Interestingly, we observed force-induced melting of single DNA molecules.


title:
Brownian Dynamics Simulation of Nucleosome Formation and Disruption
  under Stretching

abstract:
  Using a Brownian dynamics simulation, we numerically studied the interaction
of DNA with histone and proposed an octamer-rotation model to describe the
process of nucleosome formation. Nucleosome disruption under stretching was
also simulated. The theoretical curves of extension versus time as well as of
force versus extension are consistent with previous experimental results.


title: Aging Concept in Population Dynamics

abstract:
  Author's early work on aging is developed to yield a relationship between
life spans and the velocity of aging. The mathematical analysis shows that the
mean extent of the advancement of aging throughout one's life is conserved, or
equivalently, the product of the mean life span, and the mean rate of aging is
constant. The result is in harmony with our experiences: It accounts for the
unlimited replicability of tumor cells, and predicts the prolonged life spans
of hibernating hamsters, in accordance with the Lyman and coworkers experiment.
Comparing the present result and the empirical relationship between life spans
of various mammals and basal metabolic rates, it is suggested that the mean
rate of aging is intimately connected with the mean basal metabolic rate. With
the help of this information, we inquire the reason of the difference in mean
life spans between women and men, the result showing that the relative mean
life span of women to men is 1 08, for various nations, which is close to the
corresponding relative value of the basal metabolic rate. The present theory
suggests, however, that this relationship between life spans and basal
metabolic rates must be treated with caution.


title: Random Walks for Spike-Timing Dependent Plasticity

abstract:
  Random walk methods are used to calculate the moments of negative image
equilibrium distributions in synaptic weight dynamics governed by spike-timing
dependent plasticity (STDP). The neural architecture of the model is based on
the electrosensory lateral line lobe (ELL) of mormyrid electric fish, which
forms a negative image of the reafferent signal from the fish's own electric
discharge to optimize detection of sensory electric fields. Of particular
behavioral importance to the fish is the variance of the equilibrium
postsynaptic potential in the presence of noise, which is determined by the
variance of the equilibrium weight distribution. Recurrence relations are
derived for the moments of the equilibrium weight distribution, for arbitrary
postsynaptic potential functions and arbitrary learning rules. For the case of
homogeneous network parameters, explicit closed form solutions are developed
for the covariances of the synaptic weight and postsynaptic potential
distributions.


title:
RNA Binding Density on X-chromosome Differing from that on 22 Autosomes
  in Human

abstract:
  To test whether X-chromosome has unique genomic characteristics, X-chromosome
and 22 autosomes were compared for RNA binding density. Nucleotide sequences on
the chromosomes were divided into 50kb per segment that was recoded as a set of
frequency values of 7-nucleotide (7nt) strings using all possible 7nt strings
(47=16384). 120 genes highly expressed in tonsil germinal center B cells were
selected for calculating 7nt string frequency values of all introns (RNAs). The
binding density of DNA segments and RNAs was determined by the amount of
complement sequences. It was shown for the first time that gene-poor and low
gene expression X-chromosome had the lowest percentage of the DNA segments that
can highly bind RNAs, whereas gene-rich and high gene expression chromosome 19
had the highest percentage of the segments. On the basis of these results, it
is proposed that the nonrandom properties of distribution of RNA highly binding
DNA segments on the chromosomes provide strong evidence that lack of RNA highly
binding segments may be a cause of X-chromosome inactivation


title: A model for processivity of molecular motors

abstract:
  We propose a two-dimensional model for a complete description of the dynamics
of molecular motors, including both the processive movement along track
filaments and the dissociation from the filaments. The theoretical results on
the distributions of the run length and dwell time at a given ATP
concentration, the dependences of mean run length, mean dwell time and mean
velocity on ATP concentration and load are in good agreement with the previous
experimental results.


title:
Control of spiral waves and turbulent states in a cardiac model by
  travelling-wave perturbations

abstract:
  We propose a travelling-wave perturbation method to control the
spatiotemporal dynamics in a cardiac model. It is numerically demonstrated that
the method can successfully suppress the wave instability (alternans in action
potential duration) in the one-dimensional case and convert spiral waves and
turbulent states to the normal travelling wave states in the two-dimensional
case. An experimental scheme is suggested which may provide a new design for a
cardiac defibrillator.


title: Folding thermodynamics of three beta-sheet peptides: A model study

abstract:
  We study the folding thermodynamics of a beta-hairpin and two three-stranded
beta-sheet peptides using a simplified sequence-based all-atom model, in which
folding is driven mainly by backbone hydrogen bonding and effective hydrophobic
attraction. The native populations obtained for these three sequences are in
good agreement with experimental data. We also show that the apparent native
population depends on which observable is studied; the hydrophobicity energy
and the number of native hydrogen bonds give different results. The magnitude
of this dependence matches well with the results obtained in two different
experiments on the beta-hairpin.


title: Mechanism of unidirectional movement of kinesin motors

abstract:
  Kinesin motors have been studied extensively both experimentally and
theoretically. However, the microscopic mechanism of the processive movement of
kinesin is still an open question. In this paper, we propose a hand-over-hand
model for the processivity of kinesin, which is based on chemical, mechanical,
and electrical couplings. In the model the processive movement does not need to
rely on the two heads' coordination in their ATP hydrolysis and mechanical
cycles. Rather, the ATP hydrolyses at the two heads are independent. The much
higher ATPase rate at the trailing head than the leading head makes the motor
walk processively in a natural way, with one ATP being hydrolyzed per step. The
model is consistent with the structural study of kinesin and the measured
pathway of the kinesin ATPase. Using the model the estimated driving force of ~
5.8 pN is in agreements with the experimental results (5~7.5 pN). The
prediction of the moving time in one step (~10 microseconds) is also consistent
with the measured values of 0~50 microseconds. The previous observation of
substeps within the 8-nm step is explained. The shapes of velocity-load (both
positive and negative) curves show resemblance to previous experimental
results.


title: Model for processive movement of myosin V and myosin VI

abstract:
  Myosin V and myosin VI are two classes of two-headed molecular motors of the
myosin superfamily that move processively along helical actin filaments in
opposite directions. Here we present a hand-over-hand model for their
processive movements. In the model, the moving direction of a dimeric molecular
motor is automatically determined by the relative orientation between its two
heads at free state and its head's binding orientation on track filament. This
determines that myosin V moves toward the barbed end and myosin VI moves toward
the pointed end of actin. During the moving period in one step, one head
remains bound to actin for myosin V whereas two heads are detached for myosin
VI: The moving manner is determined by the length of neck domain. This
naturally explains the similar dynamic behaviors but opposite moving directions
of myosin VI and mutant myosin V (the neck of which is truncated to only
one-sixth of the native length). Because of different moving manners, myosin VI
and mutant myosin V exhibit significantly broader step-size distribution than
native myosin V. However, all three motors give the same mean step size of 36
nm (the pseudo-repeat of actin helix). Using the model we study the dynamics of
myosin V quantitatively, with theoretical results in agreement with previous
experimental ones.


title: Thermodynamics of alpha- and beta-structure formation in proteins

abstract:
  An atomic protein model with a minimalistic potential is developed and then
tested on an alpha-helix and a beta-hairpin, using exactly the same parameters
for both peptides. We find that melting curves for these sequences to a good
approximation can be described by a simple two-state model, with parameters
that are in reasonable quantitative agreement with experimental data. Despite
the apparent two-state character of the melting curves, the energy
distributions are found to lack a clear bimodal shape, which is discussed in
some detail. We also perform a Monte Carlo-based kinetic study and find, in
accord with experimental data, that the alpha-helix forms faster than the
beta-hairpin.


title: Two-state folding over a weak free-energy barrier

abstract:
  We present a Monte Carlo study of a model protein with 54 amino acids that
folds directly to its native three-helix-bundle state without forming any
well-defined intermediate state. The free-energy barrier separating the native
and unfolded states of this protein is found to be weak, even at the folding
temperature. Nevertheless, we find that melting curves to a good approximation
can be described in terms of a simple two-state system, and that the relaxation
behavior is close to single exponential. The motion along individual reaction
coordinates is roughly diffusive on timescales beyond the reconfiguration time
for an individual helix. A simple estimate based on diffusion in a square-well
potential predicts the relaxation time within a factor of two.


title:
Sequence-based study of two related proteins with different folding
  behaviors

abstract:
  ZSPA-1 is an engineered protein that binds to its parent, the
three-helix-bundle Z domain of staphylococcal protein A. Uncomplexed ZSPA-1
shows a reduced helix content and a melting behavior that is less cooperative,
compared with the wild-type Z domain. Here we show that the difference in
folding behavior between these two sequences can be partly understood in terms
of an off-lattice model with 5-6 atoms per amino acid and a minimalistic
potential, in which folding is driven by backbone hydrogen bonding and
effective hydrophobic attraction.


title: Coupled folding-binding versus docking: A lattice model study

abstract:
  Using a simple hydrophobic/polar protein model, we perform a Monte Carlo
study of the thermodynamics and kinetics of binding to a target structure for
two closely related sequences, one of which has a unique folded state while the
other is unstructured. We obtain significant differences in their binding
behavior. The stable sequence has rigid docking as its preferred binding mode,
while the unstructured chain tends to first attach to the target and then fold.
The free-energy profiles associated with these two binding modes are compared.


title: K-Winners-Take-All Computation with Neural Oscillators

abstract:
  Artificial spike-based computation, inspired by models of computation in the
central nervous system, may present significant performance advantages over
traditional methods for specific types of large scale problems. This paper
describes very simple network architectures for k-winners-take-all and
soft-winner-take-all computation using neural oscillators. Fast convergence is
achieved from arbitrary initial conditions, which makes the networks
particularly suitable to track time-varying inputs.


title: Random Boolean Network Models and the Yeast Transcriptional Network

abstract:
  The recently measured yeast transcriptional network is analyzed in terms of
simplified Boolean network models, with the aim of determining feasible rule
structures, given the requirement of stable solutions of the generated Boolean
networks. We find that for ensembles of generated models, those with canalyzing
Boolean rules are remarkably stable, whereas those with random Boolean rules
are only marginally stable. Furthermore, substantial parts of the generated
networks are frozen, in the sense that they reach the same state regardless of
initial state. Thus, our ensemble approach suggests that the yeast network
shows highly ordered dynamics.


title:
Acid-mediated tumor invasion: How does vasculature affect the growth
  characteristics?

abstract:
  We study the growth of an implanted a-vascular tumor seed in two-dimensions
based on a model where the mechanism of invasion is centered on tumor-induced
acidification of the micro-environment and consequent death of normal cells.
The spatial distribution of the acid density around the tumor is found using
mean-field analysis. By assuming that the viability of both normal and tumor
cells falls sharply below certain threshold values of the local pH, we
determine the conditions for the formation of a necrotic core at the center, as
well as its radius as a function of the tumor radius. We show that the mean
micro-vessel density (MVD) plays a pivotal role in determining the growth
characteristics of the tumor. When the MVD is sufficiently small, accumulation
of excess acid inside the tumor leads to the formation of a necrotic core,
which occupies a significant fraction of the total area in large tumors.
However, necrosis is reduced when the mean MVD inside the tumor is larger than
outside because of the more efficient removal of excess acid. At sufficiently
high MVD, necrosis is absent in the tumor, or confined to small regions mostly
devoid of micro-vessels. Quantitative estimates of MVD for these different
phases of growth are obtained, and verified using explicit cellular automaton
simulations. Recent experimental studies on the correlation between necrosis
and MVD support our main conclusions.


title: Novel steady state of a microtubule assembly in a confined geometry

abstract:
  We study the steady state of an assembly of microtubules in a confined
volume, analogous to the situation inside a cell where the cell boundary forms
a natural barrier to growth. We show that the dynamical equations for growing
and shrinking microtubules predict the existence of two steady states, with
either exponentially decaying or exponentially increasing distribution of
microtubule lengths. We identify the regimes in parameter space corresponding
to these steady states. In the latter case, the apparent catastrophe frequency
near the boundary was found to be significantly larger than that in the
interior. Both the exponential distribution of lengths and the increase in the
catastrophe frequency near the cell margin is in excellent agreement with
recent experimental observations.


title: How to find decision makers in neural circuits?

abstract:
  Neural circuits often face the problem of classifying stimuli into discrete
groups and making decisions based on such classifications. Neurons of these
circuits can be distinguished according to their correlations with different
features of stimulus or response, which allows defining sensory or motor
neuronal types. In this study we define the third class of neurons, which is
responsible for making decision. We suggest two descriptions for contribution
of units to decision making: first, as a spatial derivative of correlations
between neural activity and the decision; second, as an impact of variability
in a given neuron on the response. These two definitions are shown to be
equivalent, when they can be compared. We also suggest an experimental strategy
for determining contributions to decision making, which uses electric
stimulation with time- varying random current.


title:
Self-organized patterns and traffic flow in colonies of organisms: from
  bacteria and social insects to vertebrates

abstract:
  Flocks of birds and schools of fish are familiar examples of spatial patterns
formed by living organisms. In contrast to the patterns on the skins of, say,
zebra and giraffe, the patterns of our interest are {\it transient} although
different patterns change over different time scales. The aesthetic beauty of
these patterns have attracted the attentions of poets and philosophers for
centuries. Scientists from various disciplines, however, are in search of
common underlying principles that give rise to the transient patterns in
colonies of organisms. Such patterns are observed not only in colonies of
organisms as simple as single-cell bacteria, as interesting as social insects
like ants and termites as well as in colonies of vertebrates as complex as
birds and fish but also in human societies. In recent years, particularly over
the last one decade, physicists have utilized the conceptual framework as well
as the methodological toolbox of statistical mechanics to unravel the mystery
of these patterns. In this article we present an overview emphasizing the
common trends that rely on theoretical modelling of these systems using the
so-called agent-based Lagrangian approach.


title: Two hypotheses about natural intelligence

abstract:
  We assume that the natural intelligence (human, particularly) is equivalent
to a large inferring structure, which took shape in the last 400/500 million
years. Then two hypotheses, about this structure and its development, are put
forward for consideration. The first one concerns the transmission, from one
generation to another, of the structure: we propose that this passage is done
by direct transfer, mother to children, during pregnancy (maternal download).
The second hypothesis regards the structure evolution: now the acquired
improvements can be transferred to the descendants, so it is possible to
envisage a governed evolutionary process (evolution by improvements).


title:
Fluctuations and correlations in an individual-based model of biological
  coevolution

abstract:
  We extend our study of a simple model of biological coevolution to its
statistical properties. Staring with a complete description in terms of a
master equation, we provide its relation to the deterministic evolution
equations used in previous investigations. The stationary states of the
mutationless model are generally well approximated by Gaussian distributions,
so that the fluctuations and correlations of the populations can be computed
analytically. Several specific cases are studied by Monte Carlo simulations,
and there is excellent agreement between the data and the theoretical
predictions.


title:
Graded persisting activity of heterogeneous neuron ensembles subject to
  white noises

abstract:
  Effects of distractions such as noises and parameter heterogeneity have been
studied on the firing activity of ensemble neurons, each of which is described
by the extended Morris-Lecar model showing the graded persisting firings with
the aid of an included ${\rm Ca}^{2+}$-dependent cation current. Although the
sustained activity of {\it single} neurons is rather robust in a sense that the
activity is realized even in the presence of the distractions, the graded
frequency of sustained firings is vulnerable to them. It has been shown,
however, that the graded persisting activity of {\it ensemble} neurons becomes
much robust to the distractions by the pooling (ensemble) effect. When the
coupling is introduced, the synchronization of firings in ensemble neurons is
enhanced, which is beneficial to firings of target neurons.


title: Power laws in biological networks

abstract:
  The rapidly developing theory of complex networks indicates that real
networks are not random, but have a highly robust large-scale architecture,
governed by strict organizational principles. Here, we focus on the properties
of biological networks, discussing their scale-free and hierarchical features.
We illustrate the major network characteristics using examples from the
metabolic network of the bacterium Escherichia coli. We also discuss the
principles of network utilization, acknowledging that the interactions in a
real network have unequal strengths. We study the interplay between topology
and reaction fluxes provided by flux-balance analysis. We find that the
cellular utilization of the metabolic network is both globally and locally
highly inhomogeneous, dominated by "hot-spots", representing connected
high-flux pathways.


title:
Speed-Up of DNA Melting Algorithm with Complete Nearest Neighbor
  Properties

abstract:
  We describe a faster and more accurate algorithm for computing the
statistical mechanics of DNA denaturation according to the Poland-Scheraga
type. Nearest neighbor thermodynamics is included in a complete and general
way. The algorithm represents an optimization with respect to algorithmic
complexity of the partition function algorithm of Yeramian et al.: We reduce
the computation time for a base-pairing probability profile from O(N2) to O(N).
This speed-up comes in addition to the speed-up due to a multiexponential
approximation of the loop entropy factor as introduced by Fixman and Freire.
The speed-up, however, is independent of the multiexponential approximation and
reduces time from O(N3) to O(N2) in the exact case. In addition to calculating
the standard base-pairing probability profiles, we propose to use the algorithm
to calculate various other probabilities (loops, helices, tails) for a more
direct view of the melting regions and their positions and sizes.


title:
Temperature Dependent Conformational Transitions and Hydrogen Bond
  Dynamics of the Elastin-Like Octapeptide GVG(VPGVG): a Molecular Dynamics
  Study

abstract:
  A joint experimental / theoretical investigation of the elastin-like
octapeptide GVG(VPGVG) was carried out. In this paper a comprehensive molecular
dynamics study of the temperature dependent folding and unfolding of the
octapeptide is presented. The current study, as well as its experimental
counterpart find that this peptide undergoes an "inverse temperature
transition", ITT, leading to a folding at about 310-330 K. In addition, an
unfolding transition is identified at unusually high temperatures approaching
the boiling point of water. Due to the small size of the system two broad
temperature regimes are found: the "ITT regime" (at about 280-320 K) and the
"unfolding regime" at about T > 330 K, where the peptide has a maximum
probability of being folded at approximately 330 K. A detailed molecular
picture involving a thermodynamic order parameter, or reaction coordinate, for
this process is presented along with a time-correlation function analysis of
the hydrogen bond dynamics within the peptide as well as between the peptide
and solvating water molecules. Correlation with experimental evidence and
ramifications on the properties of elastin are discussed.


title:
Spectra and waiting-time densities in firing resonant and nonresonant
  neurons

abstract:
  The response of a neural cell to an external stimulus can follow one of the
two patterns: Nonresonant neurons monotonously relax to the resting state after
excitation while resonant ones show subthreshold oscillations. We investigate
how do these subthreshold properties of neurons affect their suprathreshold
response. Vice versa we ask: Can we distinguish between both types of neuronal
dynamics using suprathreshold spike trains? The dynamics of neurons is given by
stochastic FitzHugh-Nagumo and Morris-Lecar models with either having a focus
or a node as the stable fixpoint. We determine numerically the spectral power
density as well as the interspike interval density in response to a random
(noise-like) signals. We show that the information about the type of dynamics
obtained from power spectra is of limited validity. In contrast, the interspike
interval density gives a very sensitive instrument for the diagnostics of
whether the dynamics has resonant or nonresonant properties. For the latter
value we formulate a fit formula and use it to reconstruct theoretically the
spectral power density, which coincides with the numerically obtained spectra.
We underline that the renewal theory is applicable to analysis of
suprathreshold responses even of resonant neurons.


title:
Lattice gas cellular automata model for rippling and aggregation in
  myxobacteria

abstract:
  A lattice-gas cellular automaton (LGCA) model is used to simulate rippling
and aggregation in myxobacteria. An efficient way of representing cells of
different cell size, shape and orientation is presented that may be easily
extended to model later stages of fruiting body formation. This LGCA model is
designed to investigate whether a refractory period, a minimum response time, a
maximum oscillation period and non-linear dependence of reversals of cells on
C-factor are necessary assumptions for rippling. It is shown that a refractory
period of 2-3 minutes, a minimum response time of up to 1 minute and no maximum
oscillation period best reproduce rippling in the experiments of {\it
Myxoccoccus xanthus}. Non-linear dependence of reversals on C-factor is
critical at high cell density. Quantitative simulations demonstrate that the
increase in wavelength of ripples when a culture is diluted with non-signaling
cells can be explained entirely by the decreased density of C-signaling cells.
This result further supports the hypothesis that levels of C-signaling
quantitatively depend on and modulate cell density. Analysis of the
interpenetrating high density waves shows the presence of a phase shift
analogous to the phase shift of interpenetrating solitons. Finally, a model for
swarming, aggregation and early fruiting body formation is presented.


title:
Switching Time Statistics for Driven Neuron Models: Analytic Expressions
  versus Numerics

abstract:
  Analytical expressions are put forward to investigate the forced spiking
activity of abstract neuron models such as the driven leaky integrate-and-fire
(LIF) model. The method is valid in a wide parameter regime beyond the
restraining limits of weak driving (linear response) and/or weak noise. The
novel approximation is based on a discrete state Markovian modeling of the full
dynamics with time-dependent rates. The scheme yields very good agreement with
numerical Langevin and Fokker-Planck simulations of the full non-stationary
dynamics for both, the first-passage time statistics and the interspike
interval (residence time) distributions.

categories: q-bio.NC cond-mat.dis-nn cond-mat.stat-mech nlin.AO


title:
Extinction times for birth-death processes: exact results, continuum
  asymptotics, and the failure of the Fokker-Planck approximation

abstract:
  We consider extinction times for a class of birth-death processes commonly
found in applications, where there is a control parameter which determines
whether the population quickly becomes extinct, or rather persists for a long
time. We give an exact expression for the discrete case and its asymptotic
expansion for large values of the population. We have results below the
threshold, at the threshold, and above the threshold (where there is a
quasi-stationary state and the extinction time is very long.) We show that the
Fokker-Planck approximation is valid only quite near the threshold. We compare
our analytical results to numerical simulations for the SIS epidemic model,
which is in the class that we treat. This is an interesting example of the
delicate relationship between discrete and continuum treatments of the same
problem.


title: Cooperativity and Contact Order in Protein Folding

abstract:
  The effects of cooperativity are studied within Go-Lennard-Jones models of
proteins by making the contact interactions dependent on the proximity to the
native conformation. The kinetic universality classes are found to remain the
same as in the absence of cooperativity. For a fixed native geometry, small
changes in the effective contact map may affect the folding times in a chance
way and to the extent that is comparable to the shift in the folding times due
to cooperativity. The contact order controlls folding scenarios: the average
times necessary to bring pairs of amino acids into their near native
separations depend on the sequential distances within the pairs. This
dependence is largely monotonic, regardless of the cooperativity, and the
dominant trend could be described by a single parameter like the average
contact order. However, it is the deviations from the trend which are usually
found to set the net folding times.


title:
Consciousness, cognition, and context: extending the global neuronal
  workspace model

abstract:
  We adapt an information theory analysis of interacting cognitive biological
and social modules to the problem of the global neuronal workspace, the current
standard neuroscience picture of consciousness. Tunable punctuation emerges in
a natural manner, suggesting the possibility of fitting appropriate phase
transition power law, and, away from transition, generalized Onsager relation
expressions, to observational data on conscious reaction. The development can
be extended in a straightforward way to include the role of psychosocial
stress, culture, or other embedding structured contexts in individual
consciousness, producing a 'biopsychosocial' model that closely retains the
flavor of the standard treatment, but better meets philosophical and other
objections to brain-only descriptions.


title:
Quantum Physics in Neuroscience and Psychology: A New Theory With
  Respect to Mind/Brain Interaction

abstract:
  The cognitive frame in which most neuropsychological research on the neural
basis of behavior is conducted contains the assumption that brain mechanisms
per se fully suffice to explain all psychologically described phenomena. This
assumption stems from the idea that the brain is made up entirely of material
particles and fields, and that all causal mechanisms must therefore be
formulated solely in terms of properties of these elements. One consequence of
this stance is that psychological terms having intrinsic mentalistic and/or
experiential content (terms such as "feeling," "knowing," and "effort") have
not been included as primary causal factors in neuropsychological research:
insofar as properties are not described in material terms they are deemed
irrelevant to the causal mechanisms underlying brain function. However, the
origin of this demand that experiential realities be excluded from the causal
base is a theory of nature that has been known for more that three quarters of
a century to be fundamentally incorrect. It is explained here why it is
consequently scientifically unwarranted to assume that material factors alone
can in principle explain all causal mechanisms relevant to neuroscience. More
importantly, it is explained how a key quantum effect can be introduced into
brain dynamics in a simple and practical way that provides a rationally
coherent, causally formulated, physics-based way of understanding and using the
psychological and physical data derived from the growing set of studies of the
capacity of directed attention and mental effort to systematically alter brain
function.


title:
Increasing biological complexity is positively correlated with the
  relative genome-wide expansion of non-protein-coding DNA sequences

abstract:
  Background: Prior to the current genomic era it was suggested that the number
of protein-coding genes that an organism made use of was a valid measure of its
complexity. It is now clear, however, that major incongruities exist and that
there is only a weak relationship between biological complexity and the number
of protein coding genes. For example, using the protein-coding gene number as a
basis for evaluating biological complexity would make urochordates and insects
less complex than nematodes, and humans less complex than rice. Results: We
analyzed the ratio of noncoding to total genomic DNA (ncDNA/tgDNA) for 85
sequenced species and found that this ratio correlates well with increasing
biological complexity. The ncDNA/tgDNA ratio is generally contained within the
bandwidth of 0.05-0.24 for prokaryotes, but rises to 0.26-0.52 in unicellular
eukaryotes, and to 0.62-0.985 for developmentally complex multicellular
organisms. Significantly, prokaryotic species display a non-uniform species
distribution approaching the mean of 0.1177 ncDNA/tgDNA (p=1.58 x 10^-13), and
a nonlinear ncDNA/tgDNA relationship to genome size (r=0.15). Importantly, the
ncDNA/tgDNA ratio corrects for ploidy, and is not substantially affected by
variable loads of repetitive sequences. Conclusions: We suggest that the
observed noncoding DNA increases and compositional patterns are primarily a
function of increased information content. It is therefore possible that
introns, intergenic sequences, repeat elements, and genomic DNA previously
regarded as genetically inert may be far more important to the evolution and
functional repertoire of complex organisms than has been previously
appreciated.


title: Helix-coil Transition in Closed Circular DNA

abstract:
  A simplified model for the closed circular DNA (ccDNA) is proposed to
describe some specific features of the helix-coil transition in such molecule.
The Hamiltonian of ccDNA is related to the one introduced earlier for the
linear DNA. The basic assumption is that the reduced energy of the hydrogen
bond is not constant through the transition process but depends effectively on
the fraction of already broken bonds. A transformation formula is obtained
which relates the temperature of ccDNA at a given degree of helicity during the
transition to the temperature of the corresponding linear chain at the same
degree of helicity. The formula provides a simple method to calculate the
melting curve for the ccDNA from the experimental melting curve of the linear
DNA with the same nucleotide sequence.


title: A Selective Advantage for Conservative Viruses

abstract:
  In this letter we study the full semi-conservative treatment of a model for
the co-evolution of a virus and an adaptive immune system. Regions of viability
are calculated for both conservatively and semi-conservatively replicating
viruses interacting with a realistic semi-conservatively replicating immune
system. The conservative virus is found to have a selective advantage in the
form of an ability to survive in regions with a wider range of mutation rates
than its semi-conservative counterpart. This may help explain the existence of
a rich range of viruses with conservatively replicating genomes, a trait which
is found nowhere else in nature.


title: Quantitative patterns in the structure of model and empirical food webs

abstract:
  We analyze the properties of model food webs and of fifteen community food
webs from a variety of environments. We first perform a theoretical analysis of
the niche model of Williams and Martinez. We derive analytical expressions for
the distributions of species' number of prey, number of predators, and total
number of trophic links and find that they follow universal functional forms.
We also derive expressions for a number of other biologically relevant
parameters, including the fraction of top, intermediate, basal, and cannibal
species, the standard deviations of generality and vulnerability, the
correlation coefficient between species' number of prey and number of
predators, and assortativity. We show that our findings are robust under rather
general conditions. We then use our analytical predictions as a guide to the
analysis of fifteen of the most complete empirical food webs available. We
uncover quantitative unifying patterns that describe the properties of the
model food webs and most of the trophic webs considered. Our results support a
strong new hypothesis that the empirical distributions of number of prey and
number of predators follow universal functional forms that, without free
parameters, match our analytical predictions. Further, we find that the
empirically observed correlation coefficient, assortativity, and fraction of
cannibal species are consistent with our analytical expressions and simulations
of the niche model. Finally, we show that the average distance between nodes
and the average clustering coefficient show a high degree of regularity for
both the empirical data and simulations of the niche model. Our findings
suggest that statistical physics concepts such as scaling and universality may
be useful in the description of natural ecosystems.


title: Morphogenesis by coupled regulatory networks

abstract:
  Based on a recently proposed non-equilibrium mechanism for spatial pattern
formation [cond-mat/0312366] we study how morphogenesis can be controlled by
locally coupled discrete dynamical networks, similar to gene regulation
networks of cells in a developing multicellular organism. As an example we
study the developmental problem of domain formation and proportion regulation
in the presence of noise and cell flow. We find that networks that solve this
task exhibit a hierarchical structure of information processing and are of
similar complexity as developmental circuits of living cells. A further focus
of this paper is a detailed study of noise-induced dynamics, which is a major
ingredient of the control dynamics in the developmental network model. A master
equation for domain boundary readjustments is formulated and solved for the
continuum limit. Evidence for a first order phase transition in equilibrium
domain size at vanishing noise is given by finite size scaling. A second order
phase transition at increased cell flow is studied in a mean field
approximation. Finally, we discuss potential applications.


title:
The impact of non-linear functional responses on the long-term evolution
  of food web structure

abstract:
  We investigate the long-term web structure emerging in evolutionary food web
models when different types of functional responses are used. We find that
large and complex webs with several trophic layers arise only if the population
dynamics is such that it allows predators to focus on their best prey species.
This can be achieved using modified Lotka-Volterra or Holling/Beddington
functional responses with effective couplings that depend on the predator's
efficiency at exploiting the prey, or a ratio-dependent functional response
with adaptive foraging. In contrast, if standard Lotka-Volterra or
Holling/Beddington functional responses are used, long-term evolution generates
webs with almost all species being basal, and with additionally many links
between these species. Interestingly, in all cases studied, a large proportion
of weak links result naturally from the evolution of the food webs.


title:
Host-Parasite Co-evolution and Optimal Mutation Rates for
  Semi-conservative Quasispecies

abstract:
  In this paper, we extend a model of host-parasite co-evolution to incorporate
the semi-conservative nature of DNA replication for both the host and the
parasite. We find that the optimal mutation rate for the semi-conservative and
conservative hosts converge for realistic genome lengths, thus maintaining the
admirable agreement between theory and experiment found previously for the
conservative model and justifying the conservative approximation in some cases.
We demonstrate that, while the optimal mutation rate for a conservative and
semi-conservative parasite interacting with a given immune system is similar to
that of a conservative parasite, the properties away from this optimum differ
significantly. We suspect that this difference, coupled with the requirement
that a parasite optimize survival in a range of viable hosts, may help explain
why semi-conservative viruses are known to have significantly lower mutation
rates than their conservative counterparts.


title: Complex cooperativity of ATP hydrolysis in the F1-ATPase molecular motor

abstract:
  F1-ATPase catalyses ATP hydrolysis and converts the cellular chemical energy
into mechanical rotation. The hydrolysis reaction in F1-ATPase does not follow
the widely believed Michaelis-Menten mechanism. Instead, the hydrolysis
mechanism behaves in an ATP-dependent manner. We develop a model for enzyme
kinetics and hydrolysis cooperativity of F1-ATPase which involves the
binding-state changes to the coupling catalytic reactions. The quantitative
analysis and modeling suggest the existence of complex cooperative hydrolysis
between three different catalysis sites of F1-ATPase. This complexity may be
taken into account to resolve the arguments on the bindingchange mechanism in
F1-ATPase.


title:
Cluster approximations for probabilistic systems: a new perspective of
  epidemiological modelling

abstract:
  Especially in lattice structured populations, homogeneous mixing represents
an inadequate assumption. Various improvements upon the ordinary pair
approximation based on a number of assumptions concerning the higher-order
correlations have been proposed. To find approaches that allow for a derivation
of their dynamics remains a great challenge. By representing the population
with its connectivity patterns as a homogeneous network, we propose a
systematic methodology for the description of the epidemic dynamics that takes
into account spatial correlations up to a desired range. The equations which
the dynamical correlations are subject to, are derived in a straightforward
way, and they are solved very efficiently due to their binary character. The
method embeds very naturally spatial patterns such as the presence of loops
characterizing the square lattice or the treelike structure ubiquitous in
random networks, providing an improved description of the steady state as well
as the invasion dynamics.


title:
Toy Models and Statistical Mechanics of Subgraphs and Motifs of Genetic
  and Protein Networks

abstract:
  Theoretical physics is used for a toy model of molecular biology to assess
conditions that lead to the edge of chaos (EOC) in a network of biomolecules.
Results can enhance our ability to understand complex diseases and their
treatment or cure.


title:
A First Principles Density-Functional Calculation of the Electronic and
  Vibrational Structure of the Key Melanin Monomers

abstract:
  We report first principles density functional calculations for hydroquinone
(HQ), indolequinone (IQ) and semiquinone (SQ). These molecules are believed to
be the basic building blocks of the eumelanins, a class of bio-macromolecules
with important biological functions (including photoprotection) and with
potential for certain bioengineering applications. We have used the DeltaSCF
(difference of self consistent fields) method to study the energy gap between
the highest occupied molecular orbital (HOMO) and the lowest unoccupied
molecular orbital (LUMO), Delta_HL. We show that Delta_HL is similar in IQ and
SQ but approximately twice as large in HQ. This may have important implications
for our understanding of the observed broad band optical absorption of the
eumelanins. The possibility of using this difference in Delta_HL to molecularly
engineer the electronic properties of eumelanins is discussed. We calculate the
infrared and Raman spectra of the three redox forms from first principles. Each
of the molecules have significantly different infrared and Raman signatures,
and so these spectra could be used in situ to non-destructively identify the
monomeric content of macromolecules. It is hoped that this may be a helpful
analytical tool in determining the structure of eumelanin macromolecules and
hence in helping to determine the structure-property-function relationships
that control the behaviour of the eumelanins.

categories: q-bio.BM cond-mat.mtrl-sci cond-mat.soft physics.bio-ph physics.chem-ph


title:
Simulation of Drosophila Circadian Oscillations, Mutations, and Light
  Responses by a Model with VRI, PDP-1, and CLK

abstract:
  A model of Drosophila circadian rhythm generation was developed to represent
feedback loops based on transcriptional regulation of per, Clk (dclock), Pdp-1,
and vri (vrille). The model postulates that histone acetylation kinetics make
transcriptional activation a nonlinear function of [CLK]. Such a nonlinearity
is essential to simulate robust circadian oscillations of transcription in our
model and in previous models. Simulations suggest two positive feedback loops
involving Clk are not essential for oscillations, because oscillations of [PER]
were preserved when Clk, vri, or Pdp-1 expression was fixed. Eliminating the
negative feedback loop in which PER represses per expression abolished
oscillations. Simulations of per or Clk null mutations and of vri, Clk, or
Pdp-1 heterozygous null mutations altered model behavior in ways similar to
experimental data. The model simulated a photic phase-response curve resembling
experimental curves, and oscillations entrained to simulated light-dark cycles.
The model makes experimental predictions, some of which could be tested in
transgenic Drosophila.


title: Mathematical model of solid tumor formation

abstract:
  The problem of the onset and growth of solid tumour in homogeneous tissue is
regarded using an approach based on local interaction between the tumoral and
the sane tissue cells. The characteristic sizes and growth rates of spherical
tumours, the points of the beginning and the end of spherical growth, and the
further development of complex structures (elongated outgrowths, dendritic
structures, and metastases) are derived from the assumption that the
reproduction rate of a population of cancer cells is a non-monotone function of
their local concentration. The predicted statistical distribution of the
characteristic tumour sizes, when compared to the clinical data, will make a
basis for checking the validity of the theory.


title: Parametric Inference for Biological Sequence Analysis

abstract:
  One of the major successes in computational biology has been the unification,
using the graphical model formalism, of a multitude of algorithms for
annotating and comparing biological sequences. Graphical models that have been
applied towards these problems include hidden Markov models for annotation,
tree models for phylogenetics, and pair hidden Markov models for alignment. A
single algorithm, the sum-product algorithm, solves many of the inference
problems associated with different statistical models. This paper introduces
the \emph{polytope propagation algorithm} for computing the Newton polytope of
an observation from a graphical model. This algorithm is a geometric version of
the sum-product algorithm and is used to analyze the parametric behavior of
maximum a posteriori inference calculations for graphical models.


title:
Realistic protein-protein association rates from a simple diffusional
  model neglecting long-range interactions, free energy barriers, and landscape
  ruggedness

abstract:
  We develop a simple but rigorous model of protein-protein association
kinetics based on diffusional association on free energy landscapes obtained by
sampling configurations within and surrounding the native complex binding
funnels. Guided by results obtained on exactly solvable model problems, we
transform the problem of diffusion in a potential into free diffusion in the
presence of an absorbing zone spanning the entrance to the binding funnel. The
free diffusion problem is solved using a recently derived analytic expression
for the rate of association of asymmetrically oriented molecules. Despite the
required high steric specificity and the absence of long-range attractive
interactions, the computed rates are typically on the order of 10^4-10^6 M-1
s-1, several orders of magnitude higher than rates obtained using a purely
probabilistic model in which the association rate for free diffusion of
uniformly reactive molecules is multiplied by the probability of a correct
alignment of the two partners in a random collision. As the association rates
of many protein-protein complexes are also in the 10^5-10^6 M-1 s-1, our
results suggest that free energy barriers arising from desolvation and/or
side-chain freezing during complex formation or increased ruggedness within the
binding funnel, which are completely neglected in our simple diffusional model,
do not contribute significantly to the dynamics of protein-protein association.
The transparent physical interpretation of our approach that computes
association rates directly from the size and geometry of protein-protein
binding funnels makes it a useful complement to Brownian dynamics simulations.


title: The Waterwheel in the Waterfall

abstract:
  A fundamental problem in evolutionary ecology research is to explain how
different species coexist in natural ecosystems. This question is directly
related with species trophic competition. However, competition theory, based on
the classical logistic Lotka-Volterra equations, leads to erroneous conclusions
about species coexistence. The reason for this is incorrectly interpreted
interspecific interactions, expressed in the form of the competition
coefficients. Here I use the logistic Lotka-Volterra type competition equations
derived from the so called resource competition models to obtain the necessary
conditions for species coexistence. These models show that only species with
identical competitive abilities may coexist. Due to such relations between
competing species ecosystems biodiversity decreases in the course of evolution.


title: Homochiral growth through enantiomeric cross-inhibition

abstract:
  The stability and conservation properties of a recently proposed
polymerization model are studied. The achiral (racemic) solution is linearly
unstable once the relevant control parameter (here the fidelity of the
catalyst) exceeds a critical value. The growth rate is calculated for different
fidelity parameters and cross-inhibition rates. A chirality parameter is
defined and shown to be conserved by the nonlinear terms of the model. Finally,
a truncated version of the model is used to derive a set of two ordinary
differential equations and it is argued that these equations are more realistic
than those used in earlier models of that form.


title: Deleting species from model food webs

abstract:
  We use food webs generated by a model to investigate the effects of deleting
species on other species in the web and on the web as a whole. The model
incorporates a realistic population dynamics, adaptive foragers and other
features which allow for the construction of model webs which resemble
empirical food webs. A large number of simulations were carried out to produce
a substantial number of model webs on which deletion experiments could be
performed. We deleted each species in four hundred distinct model webs and
determined, on average, how many species were eliminated from the web as a
result. Typically only a small number of species became extinct; in no instance
was the web close to collapse. Next, we examined how the the probability of
extinction of a species depended on its relationship with the deleted species.
This involved the exploration of the concept of indirect predator and prey
species and the extent that the probability of extinction depended on the
trophic level of the two species. The effect of deletions on the web itself was
studied by searching for keystone species, whose removal caused a major
restructuring of the community, and also by looking at the correlation between
a number of food web properties (number of species, linkage density, fraction
of omnivores, degree of cycling and redundancy) and the stability of the web to
deletions. With the exception of redundancy, we found little or no correlation.
In particular, we found no evidence that complexity in terms of increased
species number or links per species is destabilising.


title: Stability and the Evolvability of Function in a Model Protein

abstract:
  Functional proteins must fold with some minimal stability to a structure that
can perform a biochemical task. Here we use a simple model to investigate the
relationship between the stability requirement and the capacity of a protein to
evolve the function of binding to a ligand. Although our model contains no
built-in tradeoff between stability and function, proteins evolved function
more efficiently when the stability requirement was relaxed. Proteins with both
high stability and high function evolved more efficiently when the stability
requirement was gradually increased than when there was constant selection for
high stability. These results show that in our model, the evolution of function
is enhanced by allowing proteins to explore sequences corresponding to
marginally stable structures, and that it is easier to improve stability while
maintaining high function than to improve function while maintaining high
stability. Our model also demonstrates that even in the absence of a
fundamental biophysical tradeoff between stability and function, the speed with
which function can evolve is limited by the stability requirement imposed on
the protein.


title:
Regulation of Neuromodulator Receptor Efficacy - Implications for
  Whole-Neuron and Synaptic Plasticity

abstract:
  Membrane receptors for neuromodulators (NM) are highly regulated in their
distribution and efficacy - a phenomenon which influences the individual cell's
response to central signals of NM release. Even though NM receptor regulation
is implicated in the pharmacological action of many drugs, and is also known to
be influenced by various environmental factors, its functional consequences and
modes of action are not well understood. In this paper we summarize relevant
experimental evidence on NM receptor regulation (specifically dopamine D1 and
D2 receptors) in order to explore its significance for neural and synaptic
plasticity. We identify the relevant components of NM receptor regulation
(receptor phosphorylation, receptor trafficking and sensitization of
second-messenger pathways) gained from studies on cultured cells. Key
principles in the regulation and control of short-term plasticity
(sensitization) are identified, and a model is presented which employs direct
and indirect feedback regulation of receptor efficacy. We also discuss
long-term plasticity which involves shifts in receptor sensitivity and loss of
responsivity to NM signals. Finally, we discuss the implications of NM receptor
regulation for models of brain plasticity and memorization. We emphasize that a
realistic model of brain plasticity will have to go beyond Hebbian models of
long-term potentiation and depression. Plasticity in the distribution and
efficacy of NM receptors may provide another important source of functional
plasticity with implications for learning and memory.


title: Correction algorithm for finite sample statistics

abstract:
  Assume in a sample of size M one finds M_i representatives of species i with
i=1...N^*. The normalized frequency p^*_i=M_i/M, based on the finite sample,
may deviate considerably from the true probabilities p_i. We propose a method
to infer rank-ordered true probabilities r_i from measured frequencies M_i. We
show that the rank-ordered probabilities provide important informations on the
system, e.g., the true number of species, the Shannon- and the Renyi-entropies.


title: Online tool for the discrimination of equi-distributions

abstract:
  For many applications one wishes to decide whether a certain set of numbers
originates from an equiprobability distribution or whether they are unequally
distributed. Distributions of relative frequencies may deviate significantly
from the corresponding probability distributions due to finite sample effects.
Hence, it is not trivial to discriminate between an equiprobability
distribution and non-equally distributed probabilities when knowing only
frequencies. Based on analytical results we provide a software tool which
allows to decide whether data correspond to an equiprobability distribution.
The tool is available at http://bioinf.charite.de/equifreq/. Its application is
demonstrated for the distribution of point mutations in coding genes.


title: Mechanisms of pattern formation during T cell adhesion

abstract:
  T cells form intriguing patterns during adhesion to antigen-presenting cells.
The patterns at the cell-cell contact zone are composed of two types of
domains, which either contain short TCR/MHCp receptor-ligand complexes or the
longer LFA-1/ICAM-1 complexes. The final pattern consists of a central TCR/MHCp
domain surrounded by a ring-shaped LFA-1/ICAM-1 domain, while the
characteristic pattern formed at intermediate times is inverted with TCR/MHCp
complexes at the periphery of the contact zone and LFA-1/ICAM-1 complexes in
the center. In this article, we present a statistical-mechanical model of cell
adhesion and propose a novel mechanism for the T cell pattern formation. Our
mechanism for the formation of the intermediate inverted pattern is based (i)
on the initial nucleation of numerous TCR/MHCp microdomains, and (ii) on the
diffusion of free receptors and ligands into the contact zone. Due to this
inward diffusion, TCR/MHCp microdomains at the rim of the contact zone grow
faster and form an intermediate peripheral ring for sufficiently large TCR/MHCp
concentrations. In agreement with experiments, we find that the formation of
the final pattern with a central TCR/MHCp domain requires active cytoskeletal
transport processes. Without active transport, the intermediate inverted
pattern seems to be metastable in our model, which might explain patterns
observed during natural killer (NK) cell adhesion. At smaller TCR/MHCp complex
concentrations, we observe a different regime of pattern formation with
intermediate multifocal TCR/MHCp patterns which resemble experimental patterns
found during thymozyte adhesion.


title: Molecular Signatures from Gene Expression Data

abstract:
  Motivation: ``Molecular signatures'' or ``gene-expression signatures'' are
used to predict patients' characteristics using data from coexpressed genes.
Signatures can enhance understanding about biological mechanisms and have
diagnostic use. However, available methods to search for signatures fail to
address key requirements of signatures, especially the discovery of sets of
tightly coexpressed genes. Results: After suggesting an operational definition
of signature, we develop a method that fulfills these requirements, returning
sets of tightly coexpressed genes with good predictive performance. This method
can also identify when the data are inconsistent with the hypothesis of a few,
stable, easily interpretable sets of coexpressed genes. Identification of
molecular signatures in some widely used data sets is questionable under this
simple model, which emphasizes the needed for further work on the
operationalization of the biological model and the assessment of the stability
of putative signatures. Availability: The code (R with C++) is available from
http://www.ligarto.org/rdiaz/Software/Software.html under the GNU GPL.


title: A Fast Reconstruction Algorithm for Gene Networks

abstract:
  This paper deals with gene networks whose dynamics is assumed to be generated
by a continuous-time, linear, time invariant, finite dimensional system (LTI)
at steady state. In particular, we deal with the problem of network
reconstruction in the typical practical situation in which the number of
available data is largely insufficient to uniquely determine the network. In
order to try to remove this ambiguity, we will exploit the biologically a
priori assumption of network sparseness, and propose a new algorithm for
network reconstruction having a very low computational complexity (linear in
the number of genes) so to be able to deal also with very large networks (say,
thousands of genes). Its performances are also tested both on artificial data
(generated with linear models) and on real data obtained by Gardner et al. from
the SOS pathway in Escherichia coli.


title: Size of Outbreaks Near the Epidemic Threshold

abstract:
  The spread of infectious diseases near the epidemic threshold is
investigated. Scaling laws for the size and the duration of outbreaks
originating from a single infected individual in a large susceptible population
are obtained. The maximal size of an outbreak n_* scales as N^{2/3} with N the
population size. This scaling law implies that the average outbreak size <n>
scales as N^{1/3}. Moreover, the maximal and the average duration of an
outbreak grow as t_* ~ N^{1/3} and <t> ~ ln N, respectively.


title: Ideas are Not Replicators but Minds Are

abstract:
  An idea is not a replicator because it does not consist of coded
self-assembly instructions. It may retain structure as it passes from one
individual to another, but does not replicate it. The cultural replicator is
not an idea but an associatively-structured network of them that together form
an internal model of the world, or worldview. A worldview is a primitive,
uncoded replicator, like the autocatalytic sets of polymers widely believed to
be the earliest form of life. Primitive replicators generate self-similar
structure, but because the process happens in a piecemeal manner, through
bottom-up interactions rather than a top-down code, they replicate with low
fidelity, and acquired characteristics are inherited. Just as polymers catalyze
reactions that generate other polymers, the retrieval of an item from memory
can in turn trigger other items, thus cross-linking memories, ideas, and
concepts into an integrated conceptual structure. Worldviews evolve idea by
idea, largely through social exchange. An idea participates in the evolution of
culture by revealing certain aspects of the worldview that generated it,
thereby affecting the worldviews of those exposed to it. If an idea influences
seemingly unrelated fields this does not mean that separate cultural lineages
are contaminating one another, because it is worldviews, not ideas, that are
the basic unit of cultural evolution.


title: Space-irrelevant scaling law for fish school sizes

abstract:
  Universal scaling in the power-law size distribution of pelagic fish schools
is established. The power-law exponent of size distributions is extracted
through the data collapse. The distribution depends on the school size only
through the ratio of the size to the expected size of the schools an arbitrary
individual engages in. This expected size is linear in the ratio of the spatial
population density of fish to the breakup rate of school. By means of extensive
numerical simulations, it is verified that the law is completely independent of
the dimension of the space in which the fish move. Besides the scaling analysis
on school size distributions, the integrity of schools over extended periods of
time is discussed.


title: Mathematical modeling of filamentous microorganisms

abstract:
  Growth patterns generated by filamentous organisms (e.g. actinomycetes and
fungi) involve spatial and temporal dynamics at different length scales.
Several mathematical models have been proposed in the last thirty years to
address these specific dynamics. Phenomenological macroscopic models are able
to reproduce the temporal dynamics of colony-related quantities (e.g. colony
growth rate) but do not explain the development of mycelial morphologies nor
the single hyphal growth. Reaction-diffusion models are a bridge between
macroscopic and microscopic worlds as they produce mean-field approximations of
single-cell behaviors. Microscopic models describe intracellular events, such
as branching, septation and translocation. Finally, completely discrete models,
cellular automata, simulate the microscopic interaction among cells to
reproduce emergent cooperative behaviors of large colonies. In this comment, we
review a selection of models for each of these length scales, stressing their
advantages and shortcomings.


title:
Kinetics of protein-DNA interaction: facilitated target location in
  sequence-dependent potential

abstract:
  Recognition and binding of specific sites on DNA by proteins is central for
many cellular functions such as transcription, replication, and recombination.
In the process of recognition, a protein rapidly searches for its specific site
on a long DNA molecule and then strongly binds this site. Here we aim to find a
mechanism that can provide both a fast search (1-10 sec) and high stability of
the specific protein-DNA complex ($K_d=10^{-15}-10^{-8}$ M).
  Earlier studies have suggested that rapid search involves the sliding of a
protein along the DNA. Here we consider sliding as a one-dimensional (1D)
diffusion in a sequence-dependent rough energy landscape. We demonstrate that,
in spite of the landscape's roughness, rapid search can be achieved if 1D
sliding is accompanied by 3D diffusion. We estimate the range of the specific
and non-specific DNA-binding energy required for rapid search and suggest
experiments that can test our mechanism. We show that optimal search requires a
protein to spend half of time sliding along the DNA and half diffusing in 3D.
We also establish that, paradoxically, realistic energy functions cannot
provide both rapid search and strong binding of a rigid protein. To reconcile
these two fundamental requirements we propose a search-and-fold mechanism that
involves the coupling of protein binding and partial protein folding.
  Proposed mechanism has several important biological implications for search
in the presence of other proteins and nucleosomes, simultaneous search by
several proteins etc. Proposed mechanism also provides a new framework for
interpretation of experimental and structural data on protein-DNA interactions.


title:
Functional Bias and Spatial Organization of Genes in Mutational Hot and
  Cold Regions in the Human Genome

abstract:
  The neutral mutation rate is known to vary widely along human chromosomes,
leading to mutational hot and cold regions. We provide evidence that categories
of functionally-related genes reside preferentially in mutationally hot or cold
regions, the size of which we have measured. Genes in hot regions are biased
toward extra-cellular communication (surface receptors, cell adhesion, immune
response, etc.) while those in cold regions are biased toward essential
cellular processes (gene regulation, RNA processing, protein modification,
etc.). From a selective perspective, this organization of genes could minimize
the mutational load on genes that need to be conserved and allow fast evolution
for genes that must frequently adapt. We also analyze the effect of gene
duplication and chromosomal recombination, which contribute significantly to
these biases for certain categories of hot genes. Overall, our results show
that genes are located non-randomly with respect to hot and cold regions,
offering the possibility that selection acts at the level of gene location in
the human genome.


title: Entanglement Invariants and Phylogenetic Branching

abstract:
  It is possible to consider stochastic models of sequence evolution in
phylogenetics in the context of a dynamical tensor description inspired from
physics. Approaching the problem in this framework allows for the well
developed methods of mathematical physics to be exploited in the biological
arena. We present the tensor description of the homogeneous continuous time
Markov chain model of phylogenetics with branching events generated by
dynamical operations. Standard results from phylogenetics are shown to be
derivable from the tensor framework. We summarize a powerful approach to
entanglement measures in quantum physics and present its relevance to
phylogenetic analysis. Entanglement measures are found to give distance
measures that are equivalent to, and expand upon, those already known in
phylogenetics. In particular we make the connection between the group invariant
functions of phylogenetic data and phylogenetic distance functions. We
introduce a new distance measure valid for three taxa based on the group
invariant function known in physics as the "tangle". All work is presented for
the homogeneous continuous time Markov chain model with arbitrary rate
matrices.


title: Physics of RecA-mediated homologous recognition

abstract:
  Most proteins involved in processing DNA accomplish their activities as a
monomer or as a component of a multimer containing a relatively small number of
other elements. They generally act locally, binding to one or a few small
regions of the DNA substrate. Striking exceptions are the \textit{E. coli}
protein RecA and its homologues in other species, whose activities are
associated with homologous DNA recombination. The active form of RecA in DNA
recombination is a stiff nucleoprotein filament formed by RecA and DNA, within
which the DNA is extended by 50%. Invoking physical and geometrical ideas, we
show that the filamentary organization greatly enhances the rate of homologous
recognition while preventing the formation of topological traps originating
from multi-site recognition.


title: The Speed of Adaptation in Large Asexual Populations

abstract:
  In large asexual populations, beneficial mutations have to compete with each
other for fixation. Here, I derive explicit analytic expressions for the rate
of substitution and the mean beneficial effect of fixed mutations, under the
assumptions that the population size N is large, that the mean effect of new
beneficial mutations is smaller than the mean effect of new deleterious
mutations, and that new beneficial mutations are exponentially distributed. As
N increases, the rate of substitution approaches a constant, which is equal to
the mean effect of new beneficial mutations. The mean effect of fixed mutations
continues to grow logarithmically with N. The speed of adaptation, measured as
the change of log fitness over time, also grows logarithmically with N for
moderately large N, and it grows double-logarithmically for extremely large N.
Moreover, I derive a simple formula that determines whether at given N
beneficial mutations are expected to compete with each other or go to fixation
independently. Finally, I verify all results with numerical simulations.


title:
Replication at periodically changing multiplicity of infection promotes
  stable coexistence of competing viral populations

abstract:
  RNA viruses are a widely used tool to study evolution experimentally. Many
standard protocols of virus propagation and competition are done at nominally
low multiplicity of infection (m.o.i.), but lead during one passage to two or
more rounds of infection, of which the later ones are at high m.o.i. Here, we
develop a model of the competition between wild type (wt) and a mutant under a
regime of alternating m.o.i. We assume that the mutant is deleterious when it
infects cells on its own, but derives a selective advantage when rare and
coinfecting with wt, because it can profit from superior protein products
created by the wt. We find that, under these assumptions, replication at
alternating low and high m.o.i. may lead to the stable coexistence of wt and
mutant for a wide range of parameter settings. The predictions of our model are
consistent with earlier observations of frequency-dependent selection in VSV
and HIV-1. Our results suggest that frequency-dependent selection may be common
in typical evolution experiments with viruses.


title: Analysis of trends in human longevity by new model

abstract:
  Trends in human longevity are puzzling, especially when considering the
limits of human longevity. Partially, the conflicting assertions are based upon
demographic evidence and the interpretation of survival and mortality curves
using the Gompertz model and the Weibull model; these models are sometimes
considered to be incomplete in describing the entire curves. In this paper a
new model is proposed to take the place of the traditional models. We directly
analysed the rectangularity (the parts of the curves being shaped like a
rectangle) of survival curves for 17 countries and for 1876-2001 in Switzerland
(it being one of the longest-lived countries) with a new model. This model is
derived from the Weibull survival function and is simply described by two
parameters, in which the shape parameter indicates 'rectangularity' and
characteristic life indicates the duration for survival to be 'exp(-1)'. The
shape parameter is essentially a function of age and it distinguishes humans
from technical devices. We find that although characteristic life has increased
up to the present time, the slope of the shape parameter for middle age has
been saturated in recent decades and that the rectangularity above
characteristic life has been suppressed, suggesting there are ultimate limits
to human longevity. The new model and subsequent findings will contribute
greatly to the interpretation and comprehension of our knowledge on the human
ageing processes.


title: A Simple Cellular Automaton Model for Influenza A Viral Infections

abstract:
  Viral kinetics have been extensively studied in the past through the use of
spatially homogeneous ordinary differential equations describing the time
evolution of the diseased state. However, spatial characteristics such as
localized populations of dead cells might adversely affect the spread of
infection, similar to the manner in which a counter-fire can stop a forest fire
from spreading. In order to investigate the influence of spatial
heterogeneities on viral spread, a simple 2-D cellular automaton (CA) model of
a viral infection has been developed. In this initial phase of the
investigation, the CA model is validated against clinical immunological data
for uncomplicated influenza A infections. Our results will be shown and
discussed.


abstract:
  General functions for human survival and mortality may support a possibility
of general mechanisms in human ageing. We discovered that the survival and
mortality curves could be described very simply and accurately by the Weibull
survival function with age-dependent shape parameter. The age-dependence of
shape parameter determines the shape of the survival and mortality curves and
tells the nature of the ageing rate. Especially, the progression of shape
parameter with age may be explained by the increase of interaction among vital
processes or the evolution of susceptibility to faults with age. Age-related
diseases may be attributed to the evolution of susceptibility to faults with
age.


title: Topological structure and interaction strengths in model food webs

abstract:
  We report the results of carrying out a large number of simulations on a
coevolutionary model of multispecies communities. A wide range of parameter
values were investigated which allowed a rather complete picture of the change
in behaviour of the model as these parameters were varied to be built up. Our
main interest was in the nature of the community food webs constructed via the
simulations. We identify the range of parameter values which give rise to
realistic food webs and give arguments which allow some of the structure which
is found to be understood in an intuitive way. Since the webs are evolved
according to the rules of the model, the strengths of the predator-prey links
are not determined a priori, and emerge from the process of constructing the
web. We measure the distribution of these link strengths, and find that there
are a large number of weak links, in agreement with recent suggestions. We also
review some of the data on food webs available in the literature, and make some
tentative comparisons with our results. The difficulties of making such
comparisons and the possible future developments of the model are also briefly
discussed.


title: Toric ideals of phylogenetic invariants

abstract:
  Statistical models of evolution are algebraic varieties in the space of joint
probability distributions on the leaf colorations of a phylogenetic tree. The
phylogenetic invariants of a model are the polynomials which vanish on the
variety. Several widely used models for biological sequences have transition
matrices that can be diagonalized by means of the Fourier transform of an
abelian group. Their phylogenetic invariants form a toric ideal in the Fourier
coordinates. We determine generators and Gr\"obner bases for these toric
ideals. For the Jukes-Cantor and Kimura models on a binary tree, our Gr\"obner
bases consist of certain explicitly constructed polynomials of degree at most
four.


title:
Size of the stable population in the Penna bit-string model of
  biological aging

abstract:
  In this paper the Penna model is reconsidered. With computer simulations we
check how the control parameters of the model influence the size of the stable
population.


title: Discriminative Topological Features Reveal Biological Network Mechanisms

abstract:
  Recent genomic and bioinformatic advances have motivated the development of
numerous random network models purporting to describe graphs of biological,
technological, and sociological origin. The success of a model has been
evaluated by how well it reproduces a few key features of the real-world data,
such as degree distributions, mean geodesic lengths, and clustering
coefficients. Often pairs of models can reproduce these features with
indistinguishable fidelity despite being generated by vastly different
mechanisms. In such cases, these few target features are insufficient to
distinguish which of the different models best describes real world networks of
interest; moreover, it is not clear a priori that any of the presently-existing
algorithms for network generation offers a predictive description of the
networks inspiring them. To derive discriminative classifiers, we construct a
mapping from the set of all graphs to a high-dimensional (in principle
infinite-dimensional) ``word space.'' This map defines an input space for
classification schemes which allow us for the first time to state unambiguously
which models are most descriptive of the networks they purport to describe. Our
training sets include networks generated from 17 models either drawn from the
literature or introduced in this work, source code for which is freely
available. We anticipate that this new approach to network analysis will be of
broad impact to a number of communities.


title: Dynamics of heterodimeric kinesins and cooperation of kinesins

abstract:
  Using the model for the processive movement of a dimeric kinesin we proposed
before, we study the dynamics of a number of mutant homodimeric and
heterodimeric kinesins that were constructed by Kaseda et al. (Kaseda, K.,
Higuchi, H. and Hirose, K. PNAS 99, 16058 (2002)). The theoretical results of
ATPase rate per head, moving velocity, and stall force of the motors show good
agreement with the experimental results by Kaseda et al.: The puzzling dynamic
behaviors of heterodimeric kinesin that consists of two distinct heads compared
with its parent homodimers can be easily explained by using independent ATPase
rates of the two heads in our model. We also study the collective kinetic
behaviors of kinesins in MT-gliding motility. The results explains well that
the average MT-gliding velocity is independent of the number of bound motors
and is equal to the moving velocity of a single kinesin relative to MT.


title:
The Spread of Infectious Disease with Household-Structure on the Complex
  Networks

abstract:
  In this paper we study the household-structure SIS epidemic spreading on
general complex networks. The household structure gives us the way to
distinguish inner and the outer infection rate. Unlike household-structure
models on homogenous networks, such as regular and random networks, here we
consider heterogeneous networks with arbitrary degree distribution p(k). First
we introduce the epidemic model. Then rate equations under mean field
appropriation and computer simulations are used here to analyze our model. Some
unique phenomena only existing in divergent network with household structure is
found, while we also get some similar conclusions that some simple geometrical
quantities of networks have important impression on infection property of
infectous disease. It seems that in our model even when local cure rate is
greater than inner infection rate in every household, disease still can spread
on scale-free network. It implies that no disease is spreading in every single
household, but for the whole network, disease is spreading. Since our society
network seems like this structure, maybe this conclusion remind us that during
disease spreading we should pay more attention on network structure than local
cure condition.


title: An Exact Model of Fluctuations in Gene Expression

abstract:
  Fluctuations in the measured mRNA levels of unperturbed cells under fixed
conditions have often been viewed as an impediment to the extraction of
information from expression profiles. Here, we argue that such expression
fluctuations should themselves be studied as a source of valuable information
about the underlying dynamics of genetic networks. By analyzing microarray data
taken from Saccharomyces cerevisiae, we demonstrate that correlations in
expression fluctuations have a highly statistically significant dependence on
gene function, and furthermore exhibit a remarkable scale-free network
structure. We therefore present what we view to be the simplest
phenomenological model of a genetic network which can account for the presence
of biological information in transcript level fluctuations. We proceed to
exactly solve this model using a path integral technique and derive several
quantitative predictions. Finally, we propose several experiments by which
these predictions might be rigorously tested.


title: Response variability in balanced cortical networks

abstract:
  We study the spike statistics of neurons in a network with dynamically
balanced excitation and inhibition. Our model, intended to represent a generic
cortical column, comprises randomly connected excitatory and inhibitory leaky
integrate-and-fire neurons, driven by excitatory input from an external
population. The high connectivity permits a mean-field description in which
synaptic currents can be treated as Gaussian noise, the mean and
autocorrelation function of which are calculated self-consistently from the
firing statistics of single model neurons. Within this description, we find
that the irregularity of spike trains is controlled mainly by the strength of
the synapses relative to the difference between the firing threshold and the
post-firing reset level of the membrane potential. For moderately strong
synapses we find spike statistics very similar to those observed in primary
visual cortex.


title: Mean field methods for cortical network dynamics

abstract:
  We review the use of mean field theory for describing the dynamics of dense,
randomly connected cortical circuits. For a simple network of excitatory and
inhibitory leaky integrate-and-fire neurons, we can show how the firing
irregularity, as measured by the Fano factor, increases with the strength of
the synapses in the network and with the value to which the membrane potential
is reset after a spike. Generalizing the model to include conductance-based
synapses gives insight into the connection between the firing statistics and
the high-conductance state observed experimentally in visual cortex. Finally,
an extension of the model to describe an orientation hypercolumn provides
understanding of how cortical interactions sharpen orientation tuning, in a way
that is consistent with observed firing statistics.


title: Microelectromagnets for the manipulation of biological systems

abstract:
  Microelectromagnet devices, a ring trap and a matrix, were developed for the
microscopic control of biological systems. The ring trap is a circular Au wire
with an insulator on top. The matrix has two arrays of straight Au wires, one
array perpendicular to the other, that are separated and topped by insulating
layers. Microelectromagnets can produce strong magnetic fields to stably
manipulate magnetically tagged biological systems in a fluid. Moreover, by
controlling the currents flowing through the wires, a microelectromagnet matrix
can move a peak in the magnetic field magnitude continuously over the surface
of the device, generate multiple peaks simultaneously and control them
independently. These capabilities of a matrix can be used to trap, continuously
transport, assemble, separate and sort biological samples on micrometer length
scales. Combining microelectromagnets with microfluidic systems, chip-based
experimental systems can be realized for novel applications in biological and
biomedical studies.


title:
To a Problem of Not Increasing Dynamic Compliance at Asthma Patients
  with Ventilating Disorders after Berotec Inhalation

abstract:
  The purpose of research was to check up the influence of decrease of
nonequality of ventilating (after bronchodilator (berotec) inhalation (BI)) on
the magnitude of dynamic compliance of lungs (Cdyn) at asthma patients with
ventilating infringements. Methods and materials: 20 patients (with 2 and 3
degrees of ventilating infringements (VC<73%, FEV1<51%, MVV<56%), without
restrictive disease of lungs, suffering from bronchial asthma were studied
before and after BI by plotting volume, rate flow, against the transpulmonare
pressure. About the change of nonequality of ventilating we consider by the
change after BI of Cdyn, Cdyn at once after flow interruption (Cdyn1), tissue
resistance at inhalation (Rti in) and exhalation (Rti ex), parameters of
ventilating and general parameters of respiratory mechanics. Results: the
parameters of ventilating were improved (P < 0,05). General parameters of
respiratory mechanics also improved. Rti in and Rti ex are made 0,48+0,16;
1,05+0,25 kPa/l/s before BI and decreased 0,09+0,04; 0,28+0,09 kPa/l/s after BI
(P < 0,05; P < 0,05). But Cdyn and Cdyn1 are not changed after BI. Conclusions:
1. The decrease of ventilation nonequality and tissue friction after BI do not
influence on the initially reduced dynamic compliance of lungs at asthma
patients without any restrictive diseases of lungs. 2. The cause of not
increasing of dynamic compliance after BI probably due by changes in elastic
component of parenchyma of lungs, insensitive to berotec.


title: High conductance states in a mean field cortical network model

abstract:
  Measured responses from visual cortical neurons show that spike times tend to
be correlated rather than exactly Poisson distributed. Fano factors vary and
are usually greater than 1 due to the tendency of spikes being clustered into
bursts. We show that this behavior emerges naturally in a balanced cortical
network model with random connectivity and conductance-based synapses. We
employ mean field theory with correctly colored noise to describe temporal
correlations in the neuronal activity. Our results illuminate the connection
between two independent experimental findings: high conductance states of
cortical neurons in their natural environment, and variable non-Poissonian
spike statistics with Fano factors greater than 1.