title:
Randomization and Feedback Properties of Directed Graphs Inspired by
  Gene Networks

abstract:
  Having in mind the large-scale analysis of gene regulatory networks, we
review a graph decimation algorithm, called "leaf-removal", which can be used
to evaluate the feedback in a random graph ensemble. In doing this, we consider
the possibility of analyzing networks where the diagonal of the adjacency
matrix is structured, that is, has a fixed number of nonzero entries. We test
these ideas on a network model with fixed degree, using both numerical and
analytical calculations. Our results are the following. First, the leaf-removal
behavior for large system size enables to distinguish between different regimes
of feedback. We show their relations and the connection with the onset of
complexity in the graph. Second, the influence of the diagonal structure on
this behavior can be relevant.


title:
Cerebellar Purkinje Cell Loss in Heterozygous Rora+/-Mice: A
  Longitudinal Study

abstract:
  The staggerer (sg/sg) mutation is a spontaneous deletion in the Rora gene
that prevents the translation of the ligand-binding domain (LBD), leading to
the loss of ROR\alpha activity. The homozygous Rorasg/sg mutant mouse, whose
most obvious phenotype is ataxia associated with cerebellar degeneration, also
displays a variety of other phenotypes. The heterozygous Rora+/sg is able to
develop a cerebellum which is qualitatively normal but with advancing age
suffers a significant loss of cerebellar neuronal cells. A truncated protein
synthesized by the mutated allele may play a role, both in Rorasg/sg and
Rora+/sg. To determine the effects during life span of true haplo-insufficiency
of the ROR\alpha protein, derived from the invalidation of the gene, we
compared the evolution of Purkinje cell numbers in heterozygous Rora knock-out
males (Rora+/-) and in their wildtype counterparts from 1 to 24 months of age.
We also compared the evolution of Purkinje cell numbers in Rora+/- and Rora+/sg
males from 1 to 9 months. The main finding is that in Rora+/- mice, when only a
half dose of protein is synthesized, the deficit was already established at 1
month and did not change during life span....


title: Designing Complex Networks

abstract:
  We suggest a new perspective of research towards understanding the relations
between structure and dynamics of a complex network: Can we design a network,
e.g. by modifying the features of units or interactions, such that it exhibits
a desired dynamics? Here we present a case study where we positively answer
this question analytically for networks of spiking neural oscillators. First,
we present a method of finding the set of all networks (defined by all mutual
coupling strengths) that exhibit an arbitrary given periodic pattern of spikes
as an invariant solution. In such a pattern all the spike times of all the
neurons are exactly predefined. The method is very general as it covers
networks of different types of neurons, excitatory and inhibitory couplings,
interaction delays that may be heterogeneously distributed, and arbitrary
network connectivities. Second, we show how to design networks if further
restrictions are imposed, for instance by predefining the detailed network
connectivity. We illustrate the applicability of the method by examples of
Erd\"{o}s-R\'{e}nyi and power-law random networks. Third, the method can be
used to design networks that optimize network properties. To illustrate this
idea, we design networks that exhibit a predefined pattern dynamics while at
the same time minimizing the networks' wiring costs.


title: Preventing extinction and outbreaks in chaotic populations

abstract:
  Interactions in ecological communities are inherently nonlinear and can lead
to complex population dynamics including irregular fluctuations induced by
chaos. Chaotic population dynamics can exhibit violent oscillations with
extremely small or large population abundances that might cause extinction and
recurrent outbreaks, respectively. We present a simple method that can guide
management efforts to prevent crashes, peaks, or any other undesirable state.
At the same time, the irregularity of the dynamics can be preserved when chaos
is desirable for the population. The control scheme is easy to implement
because it relies on time series information only. The method is illustrated by
two examples: control of crashes in the Ricker map and control of outbreaks in
a stage-structured model of the flour beetle Tribolium. It turns out to be
effective even with few available data and in the presence of noise, as is
typical for ecological settings.


title: Towards a model for protein production rates

abstract: This submission is a duplicate of arXiv:q-bio/0602024 and has been removed.


title: Study of Non-Altered Colorectal Tissue by FT-Raman Spectroscopy

abstract:
  FT-Raman spectroscopy was employed to study (in-vitro) non-altered human
colorectal tissues aiming evaluate their spectral differences. The samples were
collected from 39 patients, adding 144 spectra. The results enable one
estabilish 3 well defined spectroscopic groups of what was consistently checked
by statistical (clustering) and biological (histopathology) analysis. The
similarity within each group was better than 90%. Groups 1 and 2 had 80% of
similarity while presenting both 70% of similarity to group 3. All groups
presented connective and epithelial tissues as histopathological
characteristic. Group 1 differs from others by the presence of soft muscle
while group 3 by presence of fatty tissue. Tissues from group 2 are composed by
samples with connective and epithelial tissues. This study is very relevant in
order to establish the non-altered or normal spectroscopic standard for future
studies and applications on optical biopsy and diagnosis of colorectal cancer.


title:
Self-wiring in neural nets of point-like cortical neurons fails to
  reproduce cytoarchitectural differences

abstract:
  We propose a model for description of activity-dependent evolution and
self-wiring between binary neurons. Specifically, this model can be used for
investigation of growth of neuronal connectivity in the developing neocortex.
By using computational simulations with appropriate training pattern sequences,
we show that long-term memory can be encoded in neuronal connectivity and that
the external stimulations form part of the functioning neocortical circuit. It
is proposed that such binary neuron representations of point-like cortical
neurons fail to reproduce cytoarchitectural differences of the neocortical
organization, which has implications for inadequacies of compartmental models.


title:
Positive and negative design in stability and thermal adaptation of
  natural proteins

abstract:
  The aim of this work is to elucidate how physical principles of protein
design are reflected in natural sequences that evolved in response to the
thermal conditions of the environment. Using an exactly solvable lattice model,
we design sequences with selected thermal properties. Compositional analysis of
designed model sequences and natural proteomes reveals a specific trend in
amino acid compositions in response to the requirement of stability at elevated
environmental temperature, i.e. the increase of fractions of hydrophobic and
charged amino acid residues at the expense of polar ones. We show that this
from both ends of hydrophobicity scale trend is due to positive (to stabilize
the native state) and negative (to destabilize misfolded states) components of
protein design. Negative design strengthens specific repulsive nonnative
interactions that appear in misfolded structures. A pressure to preserve
specific repulsive interactions in non-native conformations may result in
correlated mutations between amino acids which are far apart in the native
state but may be in contact in misfolded conformations. Such correlated
mutations are indeed found in TIM barrel and other proteins.


title: Protein and DNA sequence determinants of thermophilic adaptation

abstract:
  Prokaryotes living at extreme environmental temperatures exhibit pronounced
signatures in the amino acid composition of their proteins and nucleotide
compositions of their genomes reflective of adaptation to their thermal
environments. However, despite significant efforts, the definitive answer of
what are the genomic and proteomic compositional determinants of Optimal Growth
Temperature of prokaryotic organisms remained elusive. Here the authors
performed a comprehensive analysis of amino acid and nucleotide compositional
signatures of thermophylic adaptation by exhaustively evaluating all
combinations of amino acids and nucleotides as possible determinants of Optimal
Growth Temperature for all prokaryotic organisms with fully sequences genomes..
The authors discovered that total concentration of seven amino acids in
proteomes, IVYWREL, serves as a universal proteomic predictor of Optimal Growth
Temperature in prokaryotes. Resolving the old-standing controversy the authors
determined that the variation in nucleotide composition (increase of purine
load, or A+G content with temperature) is largely a consequence of thermal
adaptation of proteins. However, the frequency with which A and G nucleotides
appear as nearest neighbors in genome sequences is strongly and independently
correlated with Optimal Growth Temperature. as a result of codon bias in
corresponding genomes. Together these results provide a complete picture of
proteomic and genomic determinants of thermophilic adaptation.


title: Mitochondrial Dna Replacement Versus Nuclear Dna Persistence

abstract:
  In this paper we consider two populations whose generations are not
overlapping and whose size is large. The number of males and females in both
populations is constant. Any generation is replaced by a new one and any
individual has two parents for what concerns nuclear DNA and a single one (the
mother) for what concerns mtDNA. Moreover, at any generation some individuals
migrate from the first population to the second.
  In a finite random time $T$, the mtDNA of the second population is completely
replaced by the mtDNA of the first. In the same time, the nuclear DNA is not
completely replaced and a fraction $F$ of the ancient nuclear DNA persists. We
compute both $T$ and $F$. Since this study shows that complete replacement of
mtDNA in a population is compatible with the persistence of a large fraction of
nuclear DNA, it may have some relevance for the Out of Africa/Multiregional
debate in Paleoanthropology.


title: Temporal differentiation and the optimization of system output

abstract:
  This paper develops a set of simplified dynamical models with which to
explore the conditions under which temporal differentiation leads to optimized
system output. By temporal differentiation, we mean a division of labor whereby
different subtasks associated with performing a given task are done at
different times. The idea is that, by focusing on one particular set of
subtasks at a time, it is possible to increase the efficiency with which each
subtask is performed, thereby allowing for faster completion of the overall
task. For this paper, we consider a process whereby some resource is converted
into some final product in a series of three agent-mediated steps. Temporal
differentiation is incorporated by allowing the agents to oscillate between
performing the first two steps and performing the last step. We find that
temporal differentiation is favored when the number of agents is small, and
when the process intermediates have a much longer lifetime than the original
resource. Within the framework of biological systems, we argue that these
results provide a possible evolutionary basis for the emergence of sleep, and
also of distinct REM and non-REM sleep states. We also discuss our use of a
three-step model. Briefly, in order for temporal differentiation to increase
product output in a mean-field description of resource metabolism, it is
necessary for temporal differentiation to have a nonlinear effect on individual
process rates. For stochastic models, we argue that temporal differentiation
can increase product output even in fundamentally linear systems.


title: Response and fluctuations of a two-state signaling module with feedback

abstract:
  We study the stochastic kinetics of a signaling module consisting of a
two-state stochastic point process with negative feedback. In the active state,
a product is synthesized which increases the active-to-inactive transition rate
of the process. We analyze this simple autoregulatory module using a
path-integral technique based on the temporal statistics of state flips of the
process. We develop a systematic framework to calculate averages,
autocorrelations, and response functions by treating the feedback as a weak
perturbation. Explicit analytical results are obtained to first order in the
feedback strength. Monte Carlo simulations are performed to test the analytical
results in the weak feedback limit and to investigate the strong feedback
regime. We conclude by relating some of our results to experimental
observations in the olfactory and visual sensory systems.


title:
A quantitative study of the benefits of co-regulation using the spoIIA
  operon as an example

abstract:
  The distribution of most genes is not random, and functionally linked genes
are often found in clusters. Several theories have been put forward to explain
the emergence and persistence of operons in bacteria. Careful analysis of
genomic data favours the co-regulation model, where gene organization into
operons is driven by the benefits of coordinated gene expression and
regulation. Direct evidence that co-expression increases the individual's
fitness enough to ensure operon formation and maintenance is, however, still
lacking. Here, a previously described quantitative model of the network that
controls the transcription factor sigmaF during sporulation in Bacillus
subtilis is employed to quantify the benefits arising from both organisation of
the sporulation genes into the spoIIA operon and from translational coupling.
The analysis shows that operon organization, together with translational
coupling, is important because of the inherent stochastic nature of gene
expression which skews the ratios between protein concentrations in the absence
of co- regulation. The predicted impact of different forms of gene regulation
on fitness and survival agrees quantitatively with published sporulation
efficiencies.


title: Probability distribution of bubble lengths in DNA

abstract:
  The distribution of bubble lengths in double-stranded DNA is presented for
segments of varying guanine-cytosine (GC) content, obtained with Monte Carlo
simulations using the Peyrard-Bishop-Dauxois model at 310 K. An analytical
description of the obtained distribution in the whole regime investigated,
i.e., up to bubble widths of the order of tens of nanometers, is available. We
find that the decay lengths and characteristic exponents of this distribution
show two distinct regimes as a function of GC content. The observed
distribution is attributed to the anharmonic interactions within base pairs.
The results are discussed in the framework of the Poland-Scheraga and the
Peyrard-Bishop (with linear instead of nonlinear stacking interaction) models.


title: The influence of risk perception in epidemics: a cellular agent model

abstract:
  Our work stems from the consideration that the spreading of a disease is
modulated by the individual's perception of the infected neighborhood and
his/her strategy to avoid being infected as well. We introduced a general
``cellular agent'' model that accounts for a hetereogeneous and variable
network of connections. The probability of infection is assumed to depend on
the perception that an individual has about the spreading of the disease in her
local neighborhood and on broadcasting media. In the one-dimensional
homogeneous case the model reduces to the DK one, while for long-range coupling
the dynamics exhibits large fluctuations that may lead to the complete
extinction of the disease.


abstract:
  Statistical mechanics of relative species abundance (RSA) patterns in
biological networks is presented. The theory is based on multispecies
replicator dynamics equivalent to the Lotka-Volterra equation, with diverse
interspecies interactions. Various RSA patterns observed in nature are derived
from a single parameter related to productivity or maturity of a community. The
abundance distribution is formed like a widely observed left-skewed lognormal
distribution. It is also found that the ``canonical hypothesis'' is supported
in some parameter region where the typical RSA patterns are observed. As the
model has a general form, the result can be applied to similar patterns in
other complex biological networks, e.g. gene expression.


title:
Schwinger Boson Formulation and Solution of the Crow-Kimura and Eigen
  Models of Quasispecies Theory

abstract:
  We express the Crow-Kimura and Eigen models of quasispecies theory in a
functional integral representation. We formulate the spin coherent state
functional integrals using the Schwinger Boson method. In this formulation, we
are able to deduce the long-time behavior of these models for arbitrary
replication and degradation functions.
  We discuss the phase transitions that occur in these models as a function of
mutation rate. We derive for these models the leading order corrections to the
infinite genome length limit.


title:
Pushing it to the Limit: Adaptation With Dynamically Switching Gain
  Control

abstract:
  With this paper we propose a model to simulate the functional aspects of
light adaptation in retinal photoreceptors. Our model, however, does not link
specific stages to the detailed molecular processes which are thought to
mediate adaptation in real photoreceptors. We rather model the photoreceptor as
a self-adjusting integration device, which adds up properly amplified luminance
signals. The integration process and the amplification obey a switching
behavior that acts to locally shut down the integration process in dependence
on the internal state of the receptor. The mathematical structure of our model
is quite simple, and its computational complexity is quite low. We present
results of computer simulations which demonstrate that our model adapts
properly to at least four orders of input magnitude.


title:
Mathematical modeling of tumor therapy with oncolytic viruses: Effects
  of parametric heterogeneity on cell dynamics

abstract:
  One of the mechanisms that ensure cancer robustness is tumor heterogeneity,
and its effects on tumor cells dynamics have to be taken into account when
studying cancer progression. There is no unifying theoretical framework in
mathematical modeling of carcinogenesis that would account for parametric
heterogeneity. Here we formulate a modeling approach that naturally takes stock
of inherent cancer cell heterogeneity and illustrate it with a model of
interaction between a tumor and an oncolytic virus. We show that several
phenomena that are absent in homogeneous models, such as cancer recurrence,
tumor dormancy, an others, appear in heterogeneous setting. We also demonstrate
that, within the applied modeling framework, to overcome the adverse effect of
tumor cell heterogeneity on cancer progression, a heterogeneous population of
an oncolytic virus must be used. Heterogeneity in parameters of the model, such
as tumor cell susceptibility to virus infection and virus replication rate, can
lead to complex, time-dependent behaviors of the tumor. Thus, irregular,
quasi-chaotic behavior of the tumor-virus system can be caused not only by
random perturbations but also by the heterogeneity of the tumor and the virus.
The modeling approach described here reveals the importance of tumor cell and
virus heterogeneity for the outcome of cancer therapy. It should be
straightforward to apply these techniques to mathematical modeling of other
types of anticancer therapy.


title: Sex and hermaphroditism in the Penna model

abstract:
  No abstract given. Confirms earlier simulatiobns of the self-organization of
dominance in the sexual Penna model, and the advantage of hermaphroditic over
sexual reproduction.


title:
Toxin-allelopathy among phytoplankton species prevents competitive
  exclusion

abstract:
  Toxic or allelopathic compounds liberated by toxin-producing phytoplankton
(TPP) acts as a strong mediator in plankton dynamics. On an analysis of a set
of phytoplankton biomass-data that have been collected by our group in the
North-West part of the Bay of Bengal, and by analysis of a three-component
mathematical model under a constant as well as a stochastic environment, we
explore the role of toxin-allelopathy in determining the dynamic behaviour of
the competing-phytoplankton species. The overall results, based on analytical
and numerical wings, demonstrate that toxin-allelopathy due to the
toxin-producing phytoplankton (TPP) promotes a stable coexistence of those
competitive phytoplankton that would otherwise exhibit competitive exclusion of
the weak species. Our study suggests that TPP might be a potential candidate
for maintaining the coexistence and diversity of competing phytoplankton
species.


title: Synergy from Silence in a Combinatorial Neural Code

abstract:
  The manner in which groups of neurons represent events in the external world
is fundamental to neuroscience. Here, we analyze the population code of the
retina during naturalistic stimulation and show that the information conveyed
by specific multi-neuronal firing patterns can be very different from the sum
of the pattern's parts. Synchronous spikes convey more information than either
of the participating cells, but almost always less than their sum, making them
redundant coding symbols. Surprisingly, patterns of spiking and silence are
mostly synergistic - carrying information that is accessible only by observing
the whole pattern of activity, rather than its components, and signifying
unique features in the stimulus. These results demonstrate that the retina uses
a combinatorial code and that the brain can benefit significantly from
recognizing multi-neuronal firing patterns.


title: A p-Adic Model of DNA Sequence and Genetic Code

abstract:
  Using basic properties of p-adic numbers, we consider a simple new approach
to describe main aspects of DNA sequence and genetic code. Central role in our
investigation plays an ultrametric p-adic information space which basic
elements are nucleotides, codons and genes. We show that a 5-adic model is
appropriate for DNA sequence. This 5-adic model, combined with 2-adic distance,
is also suitable for genetic code and for a more advanced employment in
genomics. We find that genetic code degeneracy is related to the p-adic
distance between codons.

categories: q-bio.GN cs.IT math-ph math.IT math.MP physics.bio-ph


title:
Evidence for an unfolded border-collision bifurcation in paced cardiac
  tissue

abstract:
  We investigate, both experimentally and theoretically, the bifurcation to
alternans in heart tissue. Previously, this phenomenon has been modeled either
as a smooth or as border-collision period-doubling bifurcation. Using a new
experimental technique, we find a hybrid behavior: very close to the
bifurcation point the dynamics are smooth-like, whereas further away they are
border-collision-like. This behavior is captured by a new type of model, called
an unfolded border-collision bifurcation.


title:
Relationship between Thermodynamic Driving Force and One-Way Fluxes in
  Reversible Chemical Reactions

abstract:
  Chemical reaction systems operating in nonequilibrium open-system states
arise in a great number of contexts, including the study of living organisms,
in which chemical reactions, in general, are far from equilibrium. Here we
introduce a theorem that relates forward and re-verse fluxes and free energy
for any chemical process operating in a steady state. This rela-tionship, which
is a generalization of equilibrium conditions to the case of a chemical process
occurring in a nonequilibrium steady state, provides a novel equivalent
definition for chemical reaction free energy. In addition, it is shown that
previously unrelated theories introduced by Ussing and Hodgkin and Huxley for
transport of ions across membranes, Hill for catalytic cycle fluxes, and Crooks
for entropy production in microscopically reversible systems, are united in a
common framework based on this relationship.

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


title:
Activity-dependent self-wiring is a basis of structural plastisity in
  neural networks

abstract:
  Dynamical wiring and rewiring in neural networks are carried out by
activity-dependent growth and retraction of axons and dendrites, guided by
gudance molecules, released by target cells. Experience-dependent structural
changes in cortical microcurcuts lead to changes in activity, i.e. to changes
in information encoded. Specific pattens of external stimulation can lead to
creation of new synaptical connections between neurons. Calcium influxes
controlled by neuronal activity regulates processes of neurotrophic factors
release by neurons, growth cones movement and synapse differentiation in
developing neural system, therefore activity-dependent self-wiring can serve as
a basis of structural plasticity in cortical networks and can be considered as
a form of learning.


title:
Structural network heterogeneities and network dynamics: a possible
  dynamical mechanism for hippocampal memory reactivation

abstract:
  The hippocampus has the capacity for reactivating recently acquired memories
[1-3] and it is hypothesized that one of the functions of sleep reactivation is
the facilitation of consolidation of novel memory traces [4-11]. The dynamic
and network processes underlying such a reactivation remain, however, unknown.
We show that such a reactivation characterized by local, self-sustained
activity of a network region may be an inherent property of the recurrent
excitatory-inhibitory network with a heterogeneous structure. The entry into
the reactivation phase is mediated through a physiologically feasible
regulation of global excitability and external input sources, while the
reactivated component of the network is formed through induced network
heterogeneities during learning. We show that structural changes needed for
robust reactivation of a given network region are well within known
physiological parameters [12,13].


title:
Comment on: ``Solving the riddle of the bright mismatches: Labeling and
  effective binding in oligonucleotide arrays"

abstract:
  In a recent paper [Phys. Rev. E 68, 011906 (2003)], Naef and Magnasco
suggested that the "bright" mismatches observed in Affymetrix microarray
experiments are caused by the fluorescent molecules used to label RNA target
sequences, which would impede target-probe hybridization. Their conclusion is
based on the observation of "unexpected" asymmetries in the affinities obtained
by fitting microarray data from publicly available experiments. We point out
here that the observed asymmetry is due to the inequivalence of RNA and DNA,
and that the reported affinities are consistent with stacking free energies
obtained from melting experiments of unlabeled nucleic acids in solution. The
conclusion of Naef and Magnasco is therefore based on an unjustified
assumption.


title:
Large-scale inference and graph theoretical analysis of gene-regulatory
  networks in B. stubtilis

abstract:
  We present the methods and results of a two-stage modeling process that
generates candidate gene-regulatory networks of the bacterium B. subtilis from
experimentally obtained, yet mathematically underdetermined microchip array
data. By employing a computational, linear correlative procedure to generate
these networks, and by analyzing the networks from a graph theoretical
perspective, we are able to verify the biological viability of our inferred
networks, and we demonstrate that our networks' graph theoretical properties
are remarkably similar to those of other biological systems. In addition, by
comparing our inferred networks to those of a previous, noisier implementation
of the linear inference process [17], we are able to identify trends in graph
theoretical behavior that occur both in our networks as well as in their
perturbed counterparts. These commonalities in behavior at multiple levels of
complexity allow us to ascertain the level of complexity to which our process
is robust to noise.


title:
A variational approach to the stochastic aspects of cellular signal
  transduction

abstract:
  Cellular signaling networks have evolved to cope with intrinsic fluctuations,
coming from the small numbers of constituents, and the environmental noise.
Stochastic chemical kinetics equations govern the way biochemical networks
process noisy signals. The essential difficulty associated with the master
equation approach to solving the stochastic chemical kinetics problem is the
enormous number of ordinary differential equations involved. In this work, we
show how to achieve tremendous reduction in the dimensionality of specific
reaction cascade dynamics by solving variationally an equivalent quantum field
theoretic formulation of stochastic chemical kinetics. The present formulation
avoids cumbersome commutator computations in the derivation of evolution
equations, making more transparent the physical significance of the variational
method. We propose novel time-dependent basis functions which work well over a
wide range of rate parameters. We apply the new basis functions to describe
stochastic signaling in several enzymatic cascades and compare the results so
obtained with those from alternative solution techniques. The variational
ansatz gives probability distributions that agree well with the exact ones,
even when fluctuations are large and discreteness and nonlinearity are
important. A numerical implementation of our technique is many orders of
magnitude more efficient computationally compared with the traditional Monte
Carlo simulation algorithms or the Langevin simulations.


title:
Distance based Inference for Gene-Ontology Analysis of Microarray
  Experiments

abstract:
  The increasing availability of high throughput data arising from gene
expression studies leads to the necessity of methods for summarizing the
available information. As annotation quality improves it is becoming common to
rely on the Gene Ontology (GO) to build functional profiles that characterize a
set of genes using the frequency of use of each GO term or group of terms in
the array. In this work we describe a statistical model for such profiles,
provide methods to compare profiles and develop inferential procedures to
assess this comparison. An R-package implementing the methods is available.


title:
Minimal model of self-replicating nanocells: a physically embodied
  information-free scenario

abstract:
  The building of minimal self-reproducing systems with a physical embodiment
(generically called protocells) is a great challenge, with implications for
both theory and applied sciences. Although the classical view of a living
protocell assumes that it includes information-carrying molecules as an
essential ingredient, a dividing cell-like structure can be built from a
metabolism-container coupled system, only. An example of such a system, modeled
with dissipative particle dynamics, is presented here. This article
demonstrates how a simple coupling between a precursor molecule and surfactant
molecules forming micelles can experience a growth-division cycle in a
predictable manner, and analyzes the influence of crucial parameters on this
replication cycle. Implications of these results for origins of cellular life
and living technology are outlined.


title:
The interplay between discrete noise and nonlinear chemical kinetics in
  a signal amplification cascade

abstract:
  We used various analytical and numerical techniques to elucidate signal
propagation in a small enzymatic cascade which is subjected to external and
internal noise. The nonlinear character of catalytic reactions, which underlie
protein signal transduction cascades, renders stochastic signaling dynamics in
cytosol biochemical networks distinct from the usual description of stochastic
dynamics in gene regulatory networks. For a simple 2-step enzymatic cascade
which underlies many important protein signaling pathways, we demonstrated that
the commonly used techniques such as the linear noise approximation and the
Langevin equation become inadequate when the number of proteins becomes too
low. Consequently, we developed a new analytical approximation, based on mixing
the generating function and distribution function approaches, to the solution
of the master equation that describes nonlinear chemical signaling kinetics for
this important class of biochemical reactions. Our techniques work in a much
wider range of protein number fluctuations than the methods used previously. We
found that under certain conditions the burst-phase noise may be injected into
the downstream signaling network dynamics, resulting possibly in unusually
large macroscopic fluctuations. In addition to computing first and second
moments, which is the goal of commonly used analytical techniques, our new
approach provides the full time-dependent probability distributions of the
colored non-Gaussian processes in a nonlinear signal transduction cascade.


title: Modeling gene's length distribution in genomes

abstract:
  We show, that the specific distribution of gene's length, which is observed
in natural genomes, might be a result of a growth process, in which a single
length scale $L(t)$ develops that grows with time as $t^{1/3}$. This length
scale could be associated with the length of the longest gene in an evolving
genome. The growth kinetics of the genes resembles the one observed in physical
systems with conserved ordered parameter. We show, that in genome this
conservation is guaranteed by compositional compensation along DNA strands of
the purine-like trends introduced by genes. The presented mathematical model is
the modified Bak-Sneppen model of critical self-organization applied to the
one-dimensional system of $N$ spins. The spins take discrete values, which
represent gene's length.


title: Multi-scale modeling of follicular ovulation as a reachability problem

abstract:
  During each ovarian cycle, only a definite number of follicles ovulate, while
the others undergo a degeneration process called atresia. We have designed a
multi-scale mathematical model where ovulation and atresia result from a
hormonal controlled selection process. A 2D-conservation law describes the age
and maturity structuration of the follicular cell population. In this paper, we
focus on the operating mode of the control, through the study of the
characteristics of the conservation law. We describe in particular the set of
microscopic initial conditions leading to the macroscopic phenomenon of either
ovulation or atresia, in the framework of backwards reachable sets theory.


title:
From systems biology to dynamical neuropharmacology: proposal for a new
  methodology

abstract:
  The concepts and methods of Systems Biology are being extended to
neuropharmacology, to test and design drugs against neurological and
psychiatric disorders. Computational modeling by integrating compartmental
neural modeling technique and detailed kinetic description of pharmacological
modulation of transmitter-receptor interaction is offered as a method to test
the electrophysiological and behavioral effects of putative drugs. Even more,
an inverse method is suggested as a method for controlling a neural system to
realize a prescribed temporal pattern. In particular, as an application of the
proposed new methodology a computational platform is offered to analyze the
generation and pharmacological modulation of theta rhythm related to anxiety is
analyzed here in more detail.


title: Topological classification of RNA structures

abstract:
  We present a novel topological classification of RNA secondary structures
with pseudoknots. It is based on the topological genus of the circular diagram
associated to the RNA base-pair structure. The genus is a positive integer
number, whose value quantifies the topological complexity of the folded RNA
structure. In such a representation, planar diagrams correspond to pure RNA
secondary structures and have zero genus, whereas non planar diagrams
correspond to pseudoknotted structures and have higher genus. We analyze real
RNA structures from the databases wwPDB and Pseudobase, and classify them
according to their topological genus. We compare the results of our statistical
survey with existing theoretical and numerical models. We also discuss possible
applications of this classification and show how it can be used for identifying
new RNA structural motifs.


title: A "Quasi-Rapid" Extinction Population Dynamics and Mammoths Overkill

abstract:
  In this work we suggest and consider an original, simple mathematical model
of a "quasi-rapid" extinction population dynamics. It describes a decrease and
final extinction of the population of one prey species by a "quasi-rapid"
interaction with one predator species with increasing population. This
"quasi-rapid" interaction means ecologically that prey species behaves
practically quite passively (since there is no time for any reaction, i.e.
defense), like an appropriate environment, in respect to "quasi-rapid" activity
of the predator species that can have different "quasi-rapid" hunting
abilities. Mathematically, our model is based on a non-Lotka-Volterraian system
of two differential equations of the first order, first of which is linear
while second, depending of a parameter that characterizes hunting ability is
nonlinear. We compare suggested "quasi-rapid" extinction population dynamics
and the global model of the overkill of the prehistoric megafauna (mammoths).
We demonstrate that our "quasi-rapid" extinction population dynamics is able to
restitute successfully correlations between empirical (archeological) data and
overkill theory in North America as well as Australia. For this reason, we
conclude that global overkill theory, completely mathematically modelable by
"quasi-rapid" extinction population dynamics can consistently explain the
Pleistocene extinctions of the megafauna.


title:
Nonoptimal Component Placement, but Short Processing Paths, due to
  Long-Distance Projections in Neural Systems

abstract:
  It has been suggested that neural systems across several scales of
organization show optimal component placement, in which any spatial
rearrangement of the components would lead to an increase of total wiring.
Using extensive connectivity datasets for diverse neural networks combined with
spatial coordinates for network nodes, we applied an optimization algorithm to
the network layouts, in order to search for wire-saving component
rearrangements. We found that optimized component rearrangements could
substantially reduce total wiring length in all tested neural networks.
Specifically, total wiring among 95 primate (Macaque) cortical areas could be
decreased by 32%, and wiring of neuronal networks in the nematode
Caenorhabditis elegans could be reduced by 48% on the global level, and by 49%
for neurons within frontal ganglia. Wiring length reductions were possible due
to the existence of long-distance projections in neural networks. We explored
the role of these projections by comparing the original networks with minimally
rewired networks of the same size, which possessed only the shortest possible
connections. In the minimally rewired networks, the number of processing steps
along the shortest paths between components was significantly increased
compared to the original networks. Additional benchmark comparisons also
indicated that neural networks are more similar to network layouts that
minimize the length of processing paths, rather than wiring length. These
findings suggest that neural systems are not exclusively optimized for minimal
global wiring, but for a variety of factors including the minimization of
processing steps.


title:
Synthetic Turing protocells: vesicle self-reproduction through
  symmetry-breaking instabilities

abstract:
  The reproduction of a living cell requires a repeatable set of chemical
events to be properly coordinated. Such events define a replication cycle,
coupling the growth and shape change of the cell membrane with internal
metabolic reactions. Although the logic of such process is determined by
potentially simple physico-chemical laws, the modeling of a full,
self-maintained cell cycle is not trivial. Here we present a novel approach to
the problem which makes use of so called symmetry breaking instabilities as the
engine of cell growth and division. It is shown that the process occurs as a
consequence of the breaking of spatial symmetry and provides a reliable
mechanism of vesicle growth and reproduction. Our model opens the possibility
of a synthetic protocell lacking information but displaying self-reproduction
under a very simple set of chemical reactions.


title:
Unbalanced synaptic inhibition can create intensity-tuned auditory
  cortex neurons

abstract:
  Intensity-tuned auditory cortex neurons may be formed by intensity-tuned
synaptic excitation. Synaptic inhibition has also been shown to enhance, and
possibly even create intensity-tuned neurons. Here we show, using in vivo whole
cell recordings in pentobarbital-anesthetized rats, that some intensity-tuned
neurons are indeed created solely through disproportionally large inhibition at
high intensities, without any intensity-tuned excitation. Since inhibition is
essentially cortical in origin, these neurons provide examples of auditory
feature-selectivity arising de novo at the cortex.


title:
The structural de-correlation time: A robust statistical measure of
  convergence of biomolecular simulations

abstract:
  Although atomistic simulations of proteins and other biological systems are
approaching microsecond timescales, the quality of trajectories has remained
difficult to assess. Such assessment is critical not only for establishing the
relevance of any individual simulation but also in the extremely active field
of developing computational methods. Here we map the trajectory assessment
problem onto a simple statistical calculation of the ``effective sample size''
- i.e., the number of statistically independent configurations. The mapping is
achieved by asking the question, ``How much time must elapse between snapshots
included in a sample for that sample to exhibit the statistical properties
expected for independent and identically distributed configurations?'' The
resulting ``structural de-correlation time'' is robustly calculated using exact
properties deduced from our previously developed ``structural histograms,''
without any fitting parameters. We show the method is equally and directly
applicable to toy models, peptides, and a 72-residue protein model. Variants of
our approach can readily be applied to a wide range of physical and chemical
systems.


title:
Scaling graphs of heart rate time series in athletes demonstrate the
  VLF, LF and HF regions

abstract:
  Scaling analysis of heart rate time series has emerged as an useful tool for
assessment of autonomic cardiac control. We investigate the heart rate time
series of ten athletes (five males and five females), by applying detrended
fluctuation analysis (DFA). High resolution ECGs are recorded under
standardized resting conditions over 30 minutes and subsequently heart rate
time series are extracted and artefacts filtered. We find three distinct
regions of scale-invariance, which correspond to the well-known VLF, LF, and HF
bands in the power spectra of heart rate variability. The scaling exponents
alpha are alphaHF: 1.15 [0.96-1.22], alphaLF: 0.68 [0.57-0.84], alphaVLF:
0.83[0.82-0.99]; p<10^-5). In conclusion, DFA scaling exponents of heart rate
time series should be fitted to the VLF, LF, and HF ranges, respectively.


title: Mathematic principles underlying genetic structures

abstract:
  Many people are familiar with the physico-chemical properties of gene
sequences. In this paper I present a mathematical perspective: how do
mathematical principles such as information theory, coding theory, and
combinatorics influence the beginnings of life and the formation of the genetic
codes we observe today? What constraints on possible life forms are imposed by
information-theoretical concepts? Further, I detail how mathematical principles
can help us to analyse the genetic sequences we observe in the world today.


title: Cytoskeletal bundle bending, buckling, and stretching behavior

abstract:
  F-actin bundles constitute principal components of a multitude of
cytoskeletal processes including stereocilia, filopodia, microvilli,
neurosensory bristles, cytoskeletal stress fibers, and the sperm acrosome. The
bending, buckling, and stretching behaviors of these processes play key roles
in cellular functions ranging from locomotion to mechanotransduction and
fertilization. Despite their central importance to cellular function, F-actin
bundle mechanics remain poorly understood. Here, we demonstrate that bundle
bending stiffness is a state-dependent quantity with three distinct regimes
that are mediated by bundle dimensions in addition to crosslink properties. We
calculate the complete state-dependence of the bending stiffness and elucidate
the mechanical origin of each. A generic set of design parameters delineating
the regimes in state-space is derived and used to predict the bending stiffness
of a variety of F-actin bundles found in cells. Finally, the broad and direct
implications that the isolated state-dependence of F-actin bundle stiffness has
on the interpretation of the bending, buckling, and stretching behavior of
cytoskeletal bundles is addressed.


title:
Amplitude equation approach to spatiotemporal dynamics of cardiac
  alternans

abstract:
  Amplitude equations are derived that describe the spatiotemporal dynamics of
cardiac alternans during periodic pacing of one- and two-dimensional
homogeneous tissue and one-dimensional anatomical reentry in a ring of
homogeneous tissue. These equations provide a simple physical understanding of
arrhythmogenic patterns of period-doubling oscillations of action potential
duration with a spatially varying phase and amplitude as well as explicit
quantitative predictions that can be compared to ionic model simulations or
experiments. The form of the equations is expected to be valid for a large
class of ionic models but the coefficients are only derived analytically for a
two-variable ionic model and calculated numerically for the original Noble
model of Purkinje fiber action potential.In paced tissue, the main result is
the existence of a linear instability that produces a periodic pattern of
discordant alternans. Moreover, the patterns of alternans can be either
stationary, with fixed nodes, or travelling, with moving nodes and hence
quasiperiodic oscillations of action potential duration, depending on the
relative strength of the destabilizing effect of CV-restitution and the
stabilizing effect of diffusive coupling. In both the paced geometries and the
ring, the onset of alternans is different in tissue than for a paced isolated
cell. The implications of these results for alternans dynamics during
two-dimensional reentry are briefly discussed.


title: A Simple Solution of the Lotka-Volterra Equations

abstract:
  In this work we consider a simple, approximate, tending toward exact,
solution of the system of two usual Lotka-Volterra differential equations.
Given solution is obtained by an iterative method. In any finite approximation
order of this solution, exponents of the corresponding Lotka-Volterra variables
have simple, time polynomial form. When approximation order tends to infinity
obtained approximate solution converges toward exact solution in some finite
time interval.


title:
Nestedness and degree distributions are necessarily linked in mutualist
  systems

abstract:
  Replacement of papers q-bio/0605026 and q-bio/0607043 by a single manuscript
(q-bio/0701029) follows suggestions from a magazine's referee


title: Systematic Field Theory of the RNA Glass Transition

abstract:
  We prove that the Laessig-Wiese (LW) field theory for the freezing transition
of the secondary structure of random RNA is renormalizable to all orders in
perturbation theory. The proof relies on a formulation of the model in terms of
random walks and on the use of the multilocal operator product expansion.
Renormalizability allows us to work in the simpler scheme of open polymers, and
to obtain the critical exponents at 2-loop order. It also allows to prove some
exact exponent identities, conjectured in LW.


title: The risk of extinction - the mutational meltdown or the overpopulation

abstract:
  The phase diagrams survival-extinction for the Penna model with parameters:
(mutations rate)-(birth rate), (mutation rate)-(harmful mutations threshold),
(harmful mutation threshold)-(minimal reproduction age) are presented. The
extinction phase may be caused by either mutational meltdown or overpopulation.
When the Verhulst factor is responsible for removing only newly born babies and
does not act on adults the overpopulation is avoided and only genetic factors
may lead to species extinction.


title:
Free-energy distribution of binary protein-protein binding suggests
  cross-species interactome differences

abstract:
  Major advances in large-scale yeast two hybrid (Y2H) screening have provided
a global view of binary protein-protein interactions across species as
dissimilar as human, yeast, and bacteria. Remarkably, these analyses have
revealed that all species studied have a degree distribution of protein-protein
binding that is approximately scale-free (varies as a power law) even though
their evolutionary divergence times differ by billions of years. The universal
power-law shows only the surface of the rich information harbored by these
high-throughput data. We develop a detailed mathematical model of the
protein-protein interaction network based on association free energy, the
biochemical quantity that determines protein-protein interaction strength. This
model reproduces the degree distribution of all of the large-scale Y2H data
sets available and allows us to extract the distribution of free energy, the
likelihood that a pair of proteins of a given species will bind. We find that
across-species interactomes have significant differences that reflect the
strengths of the protein-protein interaction. Our results identify a global
evolutionary shift: more evolved organisms have weaker binary protein-protein
binding. This result is consistent with the evolution of increased protein
unfoldedness and challenges the dogma that only specific protein-protein
interactions can be biologically functional..

categories: q-bio.QM cond-mat.stat-mech physics.bio-ph q-bio.MN


title:
Asymptotic analysis and analytical solutions of a model of cardiac
  excitation

abstract:
  We describe an asymptotic approach to gated ionic models of single-cell
cardiac excitability. It has a form essentially different from the Tikhonov
fast-slow form assumed in standard asymptotic reductions of excitable systems.
This is of interest since the standard approaches have been previously found
inadequate to describe phenomena such as the dissipation of cardiac wave fronts
and the shape of action potential at repolarization. The proposed asymptotic
description overcomes these deficiencies by allowing, among other non-Tikhonov
features, that a dynamical variable may change its character from fast to slow
within a single solution. The general asymptotic approach is best demonstrated
on an example which should be both simple and generic. The classical model of
Purkinje fibers (Noble, 1962) has the simplest functional form of all cardiac
models but according to the current understanding it assigns a physiologically
incorrect role to the Na current. This leads us to suggest an ``Archetypal
Model'' with the simplicity of the Noble model but with a structure more
typical to contemporary cardiac models. We demonstrate that the Archetypal
Model admits a complete asymptotic solution in quadratures. To validate our
asymptotic approach, we proceed to consider an exactly solvable ``caricature''
of the Archetypal Model and demonstrate that the asymptotic of its exact
solution coincides with the solutions obtained by substituting the
``caricature'' right-hand sides into the asymptotic solution of the generic
Archetypal Model. This is necessary, because, unlike in standard asymptotic
descriptions, no general results exist which can guarantee the proximity of the
non-Tikhonov asymptotic solutions to the solutions of the corresponding
detailed ionic model.


title: Evidence for social role in a dolphin social network

abstract:
  Social animals have to take into consideration the behaviour of conspecifics
when making decisions to go by their daily lives. These decisions affect their
fitness and there is therefore an evolutionary pressure to try making the right
choices. In many instances individuals will make their own choices and the
behaviour of the group will be a democratic integration of all decisions.
However, in some instances it can be advantageous to follow the choice of a few
individuals in the group if they have more information regarding the situation
that has arisen. Here I provide early evidence that decisions about shifts in
activity states in a population of bottlenose dolphin follow such a decision
making process. This unshared consensus is mediated by a non-vocal signal which
can be communicated globally within the dolphin school. These signals are
emitted by individuals that tend to have more information about the behaviour
of potential competitors because of their position in the social network. I
hypothesise that this decision making process emerged from the social structure
of the population and the need to maintain mixed-sex schools.


title:
Multiple Sources of the European Neolithic: Mathematical Modelling
  Constrained by Radiocarbon Dates

abstract:
  We present a mathematical model, based on the compilation and statistical
processing of radiocarbon dates, of the transition from the Mesolithic to the
Neolithic, from about 7,000 to 4,000 BC in Europe. The arrival of the Neolithic
is traditionally associated with the establishment of farming-based economies;
yet in considerable areas of north-eastern Europe it is linked with the
beginning of pottery-making in the context of foraging-type communities.
Archaeological evidence, radiocarbon dates and genetic markers are consistent
with the spread of farming from a source in the Near East. However, farming was
less important in the East; the Eastern and Western Neolithic have distinct
signatures. We use a population dynamics model to suggest that this distinction
can be attributed to the presence of two waves of advance, one from the Near
East, and another through Eastern Europe. Thus, we provide a quantitative
framework in which a unified interpretation of the Western and Eastern
Neolithic can be developed.


title: Statistically enhanced self-attraction of random patterns

abstract:
  In this work we develop a theory of interaction of randomly patterned
surfaces as a generic prototype model of protein-protein interactions. The
theory predicts that pairs of randomly superimposed identical (homodimeric)
random patterns have always twice as large magnitude of the energy fluctuations
with respect to their mutual orientation, as compared with pairs of different
(heterodimeric) random patterns. The amplitude of the energy fluctuations is
proportional to the square of the average pattern density, to the square of the
amplitude of the potential and its characteristic length, and scales linearly
with the area of surfaces. The greater dispersion of interaction energies in
the ensemble of homodimers implies that strongly attractive complexes of random
surfaces are much more likely to be homodimers, rather than heterodimers. Our
findings suggest a plausible physical reason for the anomalously high fraction
of homodimers observed in real protein interaction networks.


title:
Hysteresis and bi-stability by an interplay of calcium oscillations and
  action potential firing

abstract:
  Many cell types exhibit oscillatory activity, such as repetitive action
potential firing due to the Hodgkin-Huxley dynamics of ion channels in the cell
membrane or reveal intracellular inositol triphosphate (IP$_3$) mediated
calcium oscillations (CaOs) by calcium-induced calcium release channels
(IP$_3$-receptor) in the membrane of the endoplasmic reticulum (ER). The
dynamics of the excitable membrane and that of the IP$_3$-mediated CaOs have
been the subject of many studies. However, the interaction between the
excitable cell membrane and IP$_3$-mediated CaOs, which are coupled by
cytosolic calcium which affects the dynamics of both, has not been studied.
This study for the first time applied stability analysis to investigate the
dynamic behavior of a model, which includes both an excitable membrane and an
intracellular IP$_3$-mediated calcium oscillator. Taking the IP$_3$
concentration as a control parameter, the model exhibits a novel rich spectrum
of stable and unstable states with hysteresis. The four stable states of the
model correspond in detail to previously reported growth-state dependent states
of the membrane potential of normal rat kidney fibroblasts in cell culture. The
hysteresis is most pronounced for experimentally observed parameter values of
the model, suggesting a functional importance of hysteresis. This study shows
that the four growth-dependent cell states may not reflect the behavior of
cells that have differentiated into different cell types with different
properties, but simply reflect four different states of a single cell type,
that is characterized by a single model.


title:
Fisher Waves and Front Roughening in a Two-Species Invasion Model with
  Preemptive Competition

abstract:
  We study front propagation when an invading species competes with a resident;
we assume nearest-neighbor preemptive competition for resources in an
individual-based, two-dimensional lattice model. The asymptotic front velocity
exhibits power-law dependence on the difference between the two species' clonal
propagation rates (key ecological parameters). The mean-field approximation
behaves similarly, but the power law's exponent slightly differs from the
individual-based model's result. We also study roughening of the front, using
the framework of non-equilibrium interface growth. Our analysis indicates that
initially flat, linear invading fronts exhibit Kardar-Parisi-Zhang (KPZ)
roughening in one transverse dimension. Further, this finding implies, and is
also confirmed by simulations, that the temporal correction to the asymptotic
front velocity is of ${\cal O}(t^{-2/3})$.


title:
Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1
  Tat Fluctuations Drive Phenotypic Diversity

abstract:
  Stochastic gene expression has been implicated in a variety of cellular
processes, including cell differentiation and disease. In this issue of Cell,
Weinberger et al. (2005) take an integrated computational-experimental approach
to study the Tat transactivation feedback loop in HIV-1 and show that
fluctuations in a key regulator, Tat, can result in a phenotypic bifurcation.
This phenomenon is observed in an isogenic population where individual cells
display two distinct expression states corresponding to latent and productive
infection by HIV-1. These findings demonstrate the importance of stochastic
gene expression in molecular "decision-making."

categories: q-bio.MN cond-mat.soft physics.bio-ph q-bio.CB


title:
Supplemental Data: Stochastic Gene Expression in a Lentiviral Positive
  Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity

abstract:
  Supplemental data for "Stochastic Gene Expression in a Lentiviral Positive
Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity"
[q-bio.MN/0608002, Cell. 2005 Jul 29;122(2):169-82].


title: Correlation, selection and the evolution of species networks

abstract:
  We use a generalised version of the individual-based Tangled Nature model of
evolutionary ecology to study the relationship between ecosystem structure and
evolutionary history. Our evolved model ecosystems typically exhibit
interaction networks with exponential degree distributions and an inverse
dependence between connectance and species richness. We use a simplified
network evolution model to demonstrate that the observed degree distributions
can occur as a consequence of partial correlations in the inheritance process.
Futher to this, in the limit of low connectance and maximal correlation,
distributions of power law form, $P(k){\propto}1/k$, can be achieved. We also
show that a hyperbolic relationship between connectance and species richness,
$C{\sim}1/D$ can arise as a consequence of probabilistic constraints on the
evolutionary search process.


title:
Estimating the Number of Essential Genes in Random Transposon
  Mutagenesis Libraries

abstract:
  Biologists use random transposon mutagenesis to construct knockout libraries
for bacteria. Random mutagenesis offers cost and efficiency benefits over the
standard site directed mutagenesis, but one can no longer ensure that all the
nonessential genes will appear in the library. In random libraries for haploid
organisms, there is always a class of genes for which knockout clones have not
been made, and the members of this class are either essential or nonessential.
One requires statistical methods to estimate the number of essential genes. Two
groups of researchers, Blades and Broman and Jacobs et al., independently and
simultaneously developed methods to do this. Blades and Broman used a Gibbs
sampler and Jacobs et al. used a parametric bootstrap. We compare the
performance of these two methods and find that they both depend on having an
accurate probabilistic model for transposon insertion or on having a library
with a large number of clones. At this point, we do not have good enough
probabilistic models so we must build libraries that have at least five clones
per open reading frame to accurately estimate the number of essential genes.


title: Focal adhesions as mechanosensors: the two-spring model

abstract:
  Adhesion-dependent cells actively sense the mechanical properties of their
environment through mechanotransductory processes at focal adhesions, which are
integrin-based contacts connecting the extracellular matrix to the
cytoskeleton. Here we present first steps towards a quantitative understanding
of focal adhesions as mechanosensors. It has been shown experimentally that
high levels of force are related to growth of and signaling at focal adhesions.
In particular, activation of the small GTPase Rho through focal adhesions leads
to the formation of stress fibers. Here we discuss one way in which force might
regulate the internal state of focal adhesions, namely by modulating the
internal rupture dynamics of focal adhesions. A simple two-spring model shows
that the stiffer the environment, the more efficient cellular force is built up
at focal adhesions by molecular motors interacting with the actin filaments.


title:
Bistability of cell-matrix adhesions resulting from non-linear
  receptor-ligand dynamics

abstract:
  Bistability is a major mechanism for cellular decision making and usually
results from positive feedback in biochemical control systems. Here we show
theoretically that bistability between unbound and bound states of adhesion
clusters results from positive feedback mediated by structural rather than
biochemical processes, namely by receptor-ligand dissociation and association
dynamics which depend non-linearly on mechanical force and receptor-ligand
separation. For small cell-matrix adhesions, we find rapid switching between
unbound and bound states, which in the initial stages of adhesion allows the
cell to explore its environment through many transient adhesions.


title:
Damage segregation at fissioning may increase growth rates: A
  superprocess model

abstract:
  A fissioning organism may purge unrepairable damage by bequeathing it
preferentially to one of its daughters. Using the mathematical formalism of
superprocesses, we propose a flexible class of analytically tractable models
that allow quite general effects of damage on death rates and splitting rates
and similarly general damage segregation mechanisms. We show that, in a
suitable regime, the effects of randomness in damage segregation at fissioning
are indistinguishable from those of randomness in the mechanism of damage
accumulation during the organism's lifetime. Moreover, the optimal population
growth is achieved for a particular finite, non-zero level of combined
randomness from these two sources. In particular, when damage accumulates
deterministically, optimal population growth is achieved by a moderately
unequal division of damage between the daughters. Too little or too much
division is sub-optimal. Connections are drawn both to recent experimental
results on inheritance of damage in protozoans, to theories of the evolution of
aging, and to models of resource division between siblings.


title: Does mobility decrease cooperation?

abstract:
  We explore the minimal conditions for sustainable cooperation on a spatially
distributed population of memoryless, unconditional strategies (cooperators and
defectors) in presence of unbiased, non contingent mobility in the context of
the Prisoner's Dilemma game. We find that cooperative behavior is not only
possible but may even be enhanced by such an ``always-move'' rule, when
compared with the strongly viscous (``never-move'') case. In addition, mobility
also increases the capability of cooperation to emerge and invade a population
of defectors, what may have a fundamental role in the problem of the onset of
cooperation.


title:
Transient Resetting: A Novel Mechanism for Synchrony and Its Biological
  Examples

abstract:
  The study of synchronization in biological systems is essential for the
understanding of the rhythmic phenomena of living organisms at both molecular
and cellular levels. In this paper, by using simple dynamical systems theory,
we present a novel mechanism, named transient resetting, for the
synchronization of uncoupled biological oscillators with stimuli. This
mechanism not only can unify and extend many existing results on (deterministic
and stochastic) stimulus-induced synchrony, but also may actually play an
important role in biological rhythms. We argue that transient resetting is a
possible mechanism for the synchronization in many biological organisms, which
might also be further used in medical therapy of rhythmic disorders. Examples
on the synchronization of neural and circadian oscillators are presented to
verify our hypothesis.


title:
Cicada's wings as determinant factor for the sound emission: The case of
  \textit{Quesada gigas}

abstract:
  Cicadas (Homoptera:Cicadidae) are insects able to produce loudly songs and it
is known that the mechanism to produce sound of tymballing cicadas works as a
Helmholtz resonator. In this work we offer evidence on the participation of the
wings in a high quality resonating process which defines the details of the
acoustic properties of the calling song. The study is carry on \textit{Quesada
gigas} species and it is dividied in three stages: (i) the acoustical
characterization of the abdominal cavity, (ii) the record and calculation of
frequency spectrum of the calling song, and (iii) the measurement of the
vibration modes of the wings. The comparison between all the results
unequivocally show the dramatic influence of the wings in the moment in which
the insect emits its calling song.


title: The Discretizable Molecular Distance Geometry Problem

abstract:
  Given a weighted undirected graph $G=(V,E,d)$, the Molecular Distance
Geometry Problem (MDGP) is that of finding a function $x:G\to \mathbb{R}^{3}$,
where $||x(u)-x(v)||=d(u,v)$ for each $\{u,v\}\in E$. We show that under a few
assumptions usually satisfied in proteins, the MDGP can be formulated as a
search in a discrete space. We call this MDGP subclass the Discretizable MDGP
(DMDGP). We show that the DMDGP is \textbf{NP}-complete and we propose an
algorithm, called Branch-and-Prune (BP), which solves the DMDGP exactly. The BP
algorithm performs exceptionally well in terms of solution accuracy and can
find all solutions to any DMDGP instance. We successfully test the BP algorithm
on several randomly generated instances.


title: Linear model of tumor growth in a changing environment

abstract:
  We propose a model for describing the growth on an untreated tumor, which is
characterized in a simple way by a minimal number of parameters with a
well-defined physical interpretation. The model is motivated by invoking the
Master Equation and the Principle of Detailed Balance in the present context,
and it is easily generalizable to include the effects of various types of
therapies. In the simplest version that we consider here, it leads to a linear
equation that describes the population growth in a dynamic environment, for
which a complete solution can be given in terms of the integral of the growth
rate. The essential features of the general solution for this case are
illustrated with a few examples.


title:
The effect of finite population size on the evolutionary dynamics in
  multi-person Prisoner's Dilemma

abstract:
  We study the influence of stochastic effects due to finite population size in
the evolutionary dynamics of populations interacting in the multi-person
Prisoner's Dilemma game. This paper is an extension of the investigation
presented in a recent paper [Eriksson and Lindgren (2005), J. Theor. Biol.
232(3), 399]. One of the main results of the previous study is that there are
modes of dynamic behaviour, such as limit cycles and fixed points, that are
maintained due to a non-zero mutation level, resulting in a significantly
higher level of cooperation than was reported in earlier studies. In the
present study, we investigate two mechanisms in the evolutionary dynamics for
finite populations: (i) a stochastic model of the mutation process, and (ii) a
stochastic model of the selection process. The most evident effect comes from
the second extension, where we find that a previously stable limit cycle is
replaced by a trajectory that to a large extent is close to a fixed point that
is stable in the deterministic model. The effect is strong even when population
size is as large as 10,000. The effect of the first mechanism is less
pronounced, and an argument for this difference is given.


title: A simple model of cognitive processing in repeated games

abstract:
  In repeated interactions between individuals, we do not expect that exactly
the same situation will occur from one time to another. Contrary to what is
common in models of repeated games in the literature, most real situations may
differ a lot and they are seldom completely symmetric. The purpose of this
paper is to discuss a simple model of cognitive processing in the context of a
repeated interaction with varying payoffs. The interaction between players is
modelled by a repeated game with random observable payoffs. Cooperation is not
simply associated with a certain action but needs to be understood as a
phenomenon of the behaviour in the repeated game. The players are thus faced
with a more complex situation, compared to the Prisoner's Dilemma that has been
widely used for investigating the conditions for cooperation in evolving
populations. Still, there are robust cooperating strategies that usually evolve
in a population of players. In the cooperative mode, these strategies select an
action that allows for maximizing the sum of the payoff of the two players in
each round, regardless of the own payoff. Two such players maximise the
expected total long-term payoff. If the opponent deviates from this scheme, the
strategy invokes a punishment action, which aims at lowering the opponent's
score for the rest of the (possibly infinitely) repeated game. The introduction
of mistakes to the game actually pushes evolution towards more cooperative
strategies even though the game becomes more difficult.


title:
Inductive Reasoning Games as Influenza Vaccination Models: Mean Field
  Analysis

abstract:
  We define and analyze an inductive reasoning game of voluntary yearly
vaccination in order to establish whether or not a population of individuals
acting in their own self-interest would be able to prevent influenza epidemics.
We find that epidemics are rarely prevented. We also find that severe epidemics
may occur without the introduction of pandemic strains. We further address the
situation where market incentives are introduced to help ameliorating
epidemics. Surprisingly, we find that vaccinating families exacerbates
epidemics. However, a public health program requesting prepayment of
vaccinations may significantly ameliorate influenza epidemics.


title: Invertibility of the TKF model of sequence evolution

abstract:
  We consider character sequences evolving on a phylogenetic tree under the
TKF91 model. We show that as the sequence lengths tend to infinity the the
topology of the phylogenetic tree and the edge lengths are determined by any
one of (a) the alignment of sequences (b) the collection of sequence lengths.
We also show that the probability of any homology structure on a collection of
sequences related by a TKF91 process on a tree is independent of the root
location.
  Keywords: phylogenetics, DNA sequence evolution models, identifiability,
alignment


title: Clone size distributions in networks of genetic similarity

abstract:
  We build networks of genetic similarity in which the nodes are organisms
sampled from biological populations. The procedure is illustrated by
constructing networks from genetic data of a marine clonal plant. An important
feature in the networks is the presence of clone subgraphs, i.e. sets of
organisms with identical genotype forming clones. As a first step to understand
the dynamics that has shaped these networks, we point up a relationship between
a particular degree distribution and the clone size distribution in the
populations. We construct a dynamical model for the population dynamics,
focussing on the dynamics of the clones, and solve it for the required
distributions. Scale free and exponentially decaying forms are obtained
depending on parameter values, the first type being obtained when clonal growth
is the dominant process. Average distributions are dominated by the power law
behavior presented by the fastest replicating populations.


title:
A Petri Net approach to the study of persistence in chemical reaction
  networks

abstract:
  Persistency is the property, for differential equations in $\R^n$, that
solutions starting in the positive orthant do not approach the boundary. For
chemical reactions and population models, this translates into the
non-extinction property: provided that every species is present at the start of
the reaction, no species will tend to be eliminated in the course of the
reaction. This paper provides checkable conditions for persistence of chemical
species in reaction networks, using concepts and tools from Petri net theory.
Nontrivial examples are provided to illustrate the theory.


title: Ground state and glass transition of the RNA secondary structure

abstract:
  RNA molecules form a sequence-specific self-pairing pattern at low
temperatures. We analyze this problem using a random pairing energy model as
well as a random sequence model that includes a base stacking energy in favor
of helix propagation. The free energy cost for separating a chain into two
equal halves offers a quantitative measure of sequence specific pairing. In the
low temperature glass phase, this quantity grows quadratically with the
logarithm of the chain length, but it switches to a linear behavior of entropic
origin in the high temperature molten phase. Transition between the two phases
is continuous, with characteristics that resemble those of a disordered elastic
manifold in two dimensions. For designed sequences, however, a power-law
distribution of pairing energies on a coarse-grained level may be more
appropriate. Extreme value statistics arguments then predict a power-law growth
of the free energy cost to break a chain, in agreement with numerical
simulations. Interestingly, the distribution of pairing distances in the ground
state secondary structure follows a remarkable power-law with an exponent -4/3,
independent of the specific assumptions for the base pairing energies.


title: Bacterial gene regulation in diauxic and nondiauxic growth

abstract:
  When bacteria are grown on a mixture of two growth-limiting substrates, they
exhibit a rich spectrum of substrate consumption patterns including diauxic
growth, simultaneous consumption, and bistable growth. In previous work, we
showed that a minimal model accounting only for enzyme induction and dilution
captures all the substrate consumption patterns. Here, we construct the
bifurcation diagram of the minimal model. The bifurcation diagram explains
several general properties of mixed-substrate growth. (1) In almost all cases
of diauxic growth, the "preferred" substrate is the one that, by itself,
supports a higher specific growth rate. In the literature, this property is
often attributed to optimality of regulatory mechanisms. Here, we show that the
minimal model, which contains only induction, displays the property under
fairly general conditions. This suggests that the higher growth rate of the
preferred substrate is an intrinsic property of the induction and dilution
kinetics.(2) The model explains the phenotypes of various mutants containing
lesions in the regions encoding for the operator, repressor, and peripheral
enzymes. A particularly striking phenotype is the "reversal of the diauxie" in
which the wild-type and mutant strains consume the very same two substrates in
opposite order. This phenotype is difficult to explain in terms of molecular
mechanisms, but it turns out to be a natural consequence of the model. We show
furthermore that the model is robust. The key property of the model, namely,
the competitive dynamics of the enzymes, is preserved even if the model is
modified to account for various regulatory mechanisms. Finally, the model has
important implications for size regulation in development, since it suggests
that protein dilution is one mechanism for coupling patterning and growth.


title: The synchronization of stochastic oscillators

abstract:
  We examine microscopic mechanisms for coupling stochastic oscillators so that
they display similar and correlated temporal variations. Unlike oscillatory
motion in deterministic dynamical systems, complete synchronization of
stochastic oscillators does not occur, but appropriately defined oscillator
phase variables coincide. This is illustrated in model chemical systems and
genetic networks that produce oscillations in the dynamical variables, and we
show that suitable coupling of different networks can result in their phase
synchronization.

categories: q-bio.QM cond-mat.stat-mech nlin.CD q-bio.MN


title:
Learning with incomplete information - and the mathematical structure
  behind it

abstract:
  Learning and the ability to learn are important factors in development and
evolutionary processes [1]. Depending on the level, the complexity of learning
can strongly vary. While associative learning can explain simple learning
behaviour [1,2] much more sophisticated strategies seem to be involved in
complex learning tasks. This is particularly evident in machine learning theory
[3] (reinforcement learning [4], statistical learning [5]), but it equally
shows up in trying to model natural learning behaviour [2]. A general setting
for modelling learning processes in which statistical aspects are relevant is
provided by the neural network (NN) paradigm. This is in particular of interest
for natural, learning by experience situations. NN learning models can
incorporate elementary learning mechanisms based on neuro-physiological
analogies, such as the Hebb rule, and lead to quantitative results concerning
the dynamics of the learning process [6]. The Hebb rule, however, cannot be
directly applied in all cases, and in particular for realistic problems, such
as "delayed reinforcement" [4,6], the sophistication of the algorithms rapidly
increases. We want to present here a model which can cope with such non trivial
tasks, while still being elementary and based only on procedures which one may
think of as natural, without any appeal to higher strategies [7]. We can show
the capability of this model to provide good learning in many, very different
settings [7,8,9]. It may help therefore understanding some basic features of
learning.


title:
Characterization of Metastatic Tumor Formation by the Colony Size
  Distribution

abstract:
  Knowledge regarding the kinetics of metastatic tumor formation, as related to
the growth of the primary tumor, represents a fundamental issue in cancer
biology. Using an in vivo mammalian model, we show here that one can obtain
useful information from the frequency distribution of the sizes of metastatic
colonies in distant organs after serial sectioning and image reconstruction. To
explain the experimental findings, we constructed a biophysical model based on
the respective growth patterns of the primary tumor and metastases and a
stochastic process of metastatic colony formation. Heterogeneous distributions
of various biological parameters were considered. We found that the elementary
assumption of exponential forms of growth for the primary tumor and metastatic
colonies predicts a linear relation on a log-log plot of a metastatic colony
size distribution, which was consistent with the experimental results.
Furthermore, the slope of the curve signifies the ratio of growth rates of the
primary and the metastases. Non-exponential (Gompertzian and logistic) tumor
growth patterns were also incorporated into the theory to explain possible
deviation from the log-log linear relation. The observed metastasis-free
probability also supported the assumption of a time-dependent Poisson process.
With this approach, we determined the mechanistic parameters governing the
process of metastatogenesis in the lungs for two murine tumor cell lines (KHT
and MCaK). Since biological parameters specified in the model could be obtained
in the laboratory, a workable metastatic "assay" may be established for various
malignancies and in turn contribute in formulating rational treatment regimens
for subclinical metastases.


title:
A mass conserved reaction-diffusion system captures properties of cell
  polarity

abstract:
  Various molecules exclusively accumulate at the front or back of migrating
eukaryotic cells in response to a shallow gradient of extracellular signals.
Directional sensing and signal amplification highlight the essential properties
in the migrating cells, known as cell polarity. In addition to these, such
properties of cell polarity involve unique determination of migrating direction
(uniqueness of axis) and localized gradient sensing at the front edge
(localization of sensitivity), both of which may be required for smooth
migration. Here we provide the mass conservation system based on the
reaction-diffusion system with two components, where the mass of the two
components is always conserved. Using two models belonging to this mass
conservation system, we demonstrate through both numerical simulation and
analytical approximations that the spatial pattern with a single peak
(uniqueness of axis) can be generally observed and that the existent peak
senses a gradient of parameters at the peak position, which guides the movement
of the peak. We extended this system with multiple components, and we developed
a multiple-component model in which cross-talk between members of the Rho
family of small GTPases is involved. This model also exhibits the essential
properties of the two models with two components. Thus, the mass conservation
system shows properties similar to those of cell polarity, such as uniqueness
of axis and localization of sensitivity, in addition to directional sensing and
signal amplification.


title:
Does the 1/f frequency-scaling of brain signals reflect self-organized
  critical states?

abstract:
  Many complex systems display self-organized critical states characterized by
1/f frequency scaling of power spectra. Global variables such as the
electroencephalogram, scale as 1/f, which could be the sign of self-organized
critical states in neuronal activity. By analyzing simultaneous recordings of
global and neuronal activities, we confirm the 1/f scaling of global variables
for selected frequency bands, but show that neuronal activity is not consistent
with critical states. We propose a model of 1/f scaling which does not rely on
critical states, and which is testable experimentally.


title:
Temporal Symmetry in Primary Auditory Cortex: Implications for Cortical
  Connectivity

abstract:
  Neurons in primary auditory cortex (AI) in the ferret (Mustela putorius) that
are well described by their spectro-temporal response field (STRF), are found
also to have a distinctive property that we call temporal symmetry. For
temporally symmetric neurons, every temporal cross-section of the STRF (impulse
response) is given by the same function of time, except for a scaling and a
"Hilbert rotation". This property held in 85% of neurons (123 out of 145)
recorded from awake animals, and in 96% of neurons (70 out of 73) recorded from
anesthetized animals. This property of temporal symmetry is highly constraining
for possible models of functional neural connectivity within and into AI. We
find that the simplest models of functional thalamic input, from the ventral
Medial Geniculate Body (MGB), into the entry layers of AI are ruled out because
they are incompatible with the constraints of the observed temporal symmetry.
This is also the case for the simplest models of functional intracortical
connectivity. Plausible models that do generate temporal symmetry, both from
thalamic and intracortical inputs, are presented. In particular, we propose
that two specific characteristics of the thalamo-cortical interface may be
responsible. The first is a temporal mismatch between the fast dynamics of the
thalamus and the slow responses of the cortex. The second is that all thalamic
inputs into a cortical module (or a cluster of cells) must be restricted to one
point of entry (or one cell in the cluster). This latter property implies a
lack of correlated horizontal interactions across cortical modules during the
STRF measurements. The implications of these insights in the auditory system,
and comparisons with similar properties in the visual system, are explored.


title:
Incubation periods under various anti-retroviral therapies in
  homogeneous mixing and age-structured dynamical models: A theoretical
  approach

abstract:
  With the launch of second line anti-retroviral therapy for HIV infected
individuals, there has been an increased expectation on surviving period of
people with HIV. We consider previously well-known models in HIV epidemiology
where the parameter for incubation period is used as one of the important
components to explain the dynamics of the variables. Such models are extended
here to explain the dynamics with respect to a given therapy that prolongs life
of an HIV infected individual. A deconvolution method is demonstrated for
estimation of parameters in the situations when no-therapy and multiple
therapies are given to the infected population. The models and deconvolution
method are extended in order to study the impact of therapy in age-structured
populations. A generalization for a situation when n-types of therapies are
available is given. Models are demonstrated using hypothetical data and
sensitivity of the parameters are also computed.


title: Quasispecies Theory for Multiple-Peak Fitness Landscapes

abstract:
  We use a path integral representation to solve the Eigen and Crow-Kimura
molecular evolution models for the case of multiple fitness peaks with
arbitrary fitness and degradation functions. In the general case, we find that
the solution to these molecular evolution models can be written as the optimum
of a fitness function, with constraints enforced by Lagrange multipliers and
with a term accounting for the entropy of the spreading population in sequence
space. The results for the Eigen model are applied to consider virus or cancer
proliferation under the control of drugs or the immune system.


title:
Model for Osteosarcoma-9 as a Potent Factor in Cell Survivor and
  Resistance to Apoptosis

abstract:
  In this paper we use a simple toy model to explore the function of the gene
Osteosarcoma-9. We are in particular interested in understanding the role of
this gene as a potent anti-apoptotic factor. The theoretical description is
constrained by experimental data from induction of apoptosis in cells where
OS-9 is overexpressed. The data available suggest that OS-9 promotes cell
viability and confers resistance to apoptosis, potentially implicating OS-9 in
the survival of cancer cells. Three different apoptosis inducing mechanisms
were tested and are here modelled. More complex and realistic models are also
discussed.


title: Geometrical approach to tumor growth

abstract:
  Tumor growth has a number of features in common with a physical process known
as molecular beam epitaxy. Both growth processes are characterized by the
constraint of growth development to the body border, and surface diffusion of
cells/particles at the growing edge. However, tumor growth implies an
approximate spherical symmetry that makes necessary a geometrical treatment of
the growth equations. The basic model was introduced in a former article [C.
Escudero, Phys. Rev. E 73, 020902(R) (2006)], and in the present work we extend
our analysis and try to shed light on the possible geometrical principles that
drive tumor growth. We present two-dimensional models that reproduce the
experimental observations, and analyse the unexplored three-dimensional case,
for which new conclusions on tumor growth are derived.

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


title:
Two-population replicator dynamics and number of Nash equilibria in
  random matrix games

abstract:
  We study the connection between the evolutionary replicator dynamics and the
number of Nash equilibria in large random bi-matrix games. Using techniques of
disordered systems theory we compute the statistical properties of both, the
fixed points of the dynamics and the Nash equilibria. Except for the special
case of zero-sum games one finds a transition as a function of the so-called
co-operation pressure between a phase in which there is a unique stable fixed
point of the dynamics coinciding with a unique Nash equilibrium, and an
unstable phase in which there are exponentially many Nash equilibria with
statistical properties different from the stationary state of the replicator
equations. Our analytical results are confirmed by numerical simulations of the
replicator dynamics, and by explicit enumeration of Nash equilibria.


title:
Longevity of orders is related to the longevity of their constituent
  genera rather than genus richness

abstract:
  Longevity of a taxonomic group is an important issue in understanding the
dynamics of evolution. In this respect a key observation is that genera,
families or orders can each be assigned a characteristic average lifetime [Van
Valen, L., (1973) Evolutionary Theory 1, 1-30]. Using the fossil marine animal
genera database [Sepkoski, J.J.Jr. (2002) A Compendium of Fossil Marine Animal
Genera, Bull. Am. Paleontol. 363, 563 pp.] we here examine key determinants for
robustness of a higher taxonomic group in terms of the characteristics of its
constituents. We find insignificant correlation between the size of an order
and its stability against extinction, whereas we observe amazingly large
correlation between the lifetime of an order and the lifetime of its
constituent genera.


title:
Frequency decomposition of conditional Granger causality and application
  to multivariate neural field potential data

abstract:
  It is often useful in multivariate time series analysis to determine
statistical causal relations between different time series. Granger causality
is a fundamental measure for this purpose. Yet the traditional pairwise
approach to Granger causality analysis may not clearly distinguish between
direct causal influences from one time series to another and indirect ones
acting through a third time series. In order to differentiate direct from
indirect Granger causality, a conditional Granger causality measure in the
frequency domain is derived based on a partition matrix technique. Simulations
and an application to neural field potential time series are demonstrated to
validate the method.


title: Granger Causality: Basic Theory and Application to Neuroscience

abstract:
  Multi-electrode neurophysiological recordings produce massive quantities of
data. Multivariate time series analysis provides the basic framework for
analyzing the patterns of neural interactions in these data. It has long been
recognized that neural interactions are directional. Being able to assess the
directionality of neuronal interactions is thus a highly desired capability for
understanding the cooperative nature of neural computation. Research over the
last few years has shown that Granger causality is a key technique to furnish
this capability. The main goal of this article is to provide an expository
introduction to the concept of Granger causality. Mathematical frameworks for
both bivariate Granger causality and conditional Granger causality are
developed in detail with particular emphasis on their spectral representations.
The technique is demonstrated in numerical examples where the exact answers of
causal influences are known. It is then applied to analyze multichannel local
field potentials recorded from monkeys performing a visuomotor task. Our
results are shown to be physiologically interpretable and yield new insights
into the dynamical organization of large-scale oscillatory cortical networks.


title: Sequence sensitivity of breathing dynamics in heteropolymer DNA

abstract:
  We study the fluctuation dynamics of localized denaturation bubbles in
heteropolymer DNA with a master equation and complementary stochastic
simulation based on novel DNA stability data. A significant dependence of
opening probability and waiting time between bubble events on the local DNA
sequence is revealed and quantified for a biological sequence of the T7
bacteriophage. Quantitative agreement with data from fluorescence correlation
spectroscopy (FCS) is demonstrated.


title: Network growth approach to macroevolution

abstract:
  We propose a novel network growth model coupled with the competition
interaction to simulate macroevolution. Our work shows that the competition
plays an important role in macroevolution and it is more rational to describe
the interaction between species by network structures. Our model presents a
complete picture of the development of phyla and the splitting process. It is
found that periodic mass extinction occurred in our networks without any
extraterrestrial factors and the lifetime distribution of species is very close
to fossil record. We also perturb networks with two scenarios of mass
extinctions on different hierarchic levels in order to study their recovery.


title:
A versatile maskless microscope projection photolithography system and
  its application in light-directed fabrication of DNA microarrays

abstract:
  We present a maskless microscope projection lithography system (MPLS), in
which photomasks have been replaced by a Digital Micromirror Device type
spatial light modulator (DMD, Texas Instruments). Employing video projector
technology high resolution patterns, designed as bitmap images on the computer,
are displayed using a micromirror array consisting of about 786000 tiny
individually addressable tilting mirrors. The DMD, which is located in the
image plane of an infinity corrected microscope, is projected onto a substrate
placed in the focal plane of the microscope objective. With a 5x(0.25 NA) Fluar
microscope objective, a fivefold reduction of the image to a total size of 9
mm2 and a minimum feature size of 3.5 microns is achieved. Our system can be
used in the visible range as well as in the near UV (with a light intensity of
up to 76 mW/cm2 around the 365 nm Hg-line). We developed an inexpensive and
simple method to enable exact focusing and controlling of the image quality of
the projected patterns. Our MPLS has originally been designed for the
light-directed in situ synthesis of DNA microarrays. One requirement is a high
UV intensity to keep the fabrication process reasonably short. Another demand
is a sufficient contrast ratio over small distances (of about 5 microns). This
is necessary to achieve a high density of features (i.e. separated sites on the
substrate at which different DNA sequences are synthesized in parallel fashion)
while at the same time the number of stray light induced DNA sequence errors is
kept reasonably small. We demonstrate the performance of the apparatus in
light-directed DNA chip synthesis and discuss its advantages and limitations.


title: Force balance and membrane shedding at the Red Blood Cell surface

abstract:
  During the aging of the red-blood cell, or under conditions of extreme
echinocytosis, membrane is shed from the cell plasma membrane in the form of
nano-vesicles. We propose that this process is the result of the
self-adaptation of the membrane surface area to the elastic stress imposed by
the spectrin cytoskeleton, via the local buckling of membrane under increasing
cytoskeleton stiffness. This model introduces the concept of force balance as a
regulatory process at the cell membrane, and quantitatively reproduces the rate
of area loss in aging red-blood cells.


title:
Simulation Studies of A Phenomenological Model for the Assembly of
  Elongated Virus Capsids

abstract:
  We extend our previously developed general approach (1) to study a
phenomenological model in which the simulated packing of hard, attractive
spheres on a prolate spheroid surface with convexity constraints produces
structures identical to those of prolate virus capsid structures. Our
simulation approach combines the traditional Monte Carlo method with the method
of random sampling on an ellipsoidal surface and a convex hull searching
algorithm. Using this approach we study the assembly and structural origin of
non-icosahedral, elongated virus capsids, such as two aberrant flock house
virus (FHV) particles and the prolate prohead of bacteriophage phi29, and
discuss the implication of our simulation results in the context of recent
experimental findings.