title:
Nanosurgery: Observation of Peptidoglycan Strands in Lactobacillus
  helveticus Cell Walls

abstract:
  The internal cell wall structure of the bacterium Lactobacillus helveticus
has been observed in situ in aqueous solution using an atomic force microscope
(AFM). The AFM tip was used not only for imaging but presumably to remove
mechanically large patches of the outer cell wall after appropriate chemical
treatment, which typically leaves the bacteria alive. The surface exposed after
such a surgery revealed ca. 26 nm thick twisted strands within the cell wall.
The structure and location of the observed strands are consistent with the
glycan backbone of peptidoglycan fibers that give strength to the cell wall.
The found structural organization of these fibers has not been observed
previously.


title:
Predicting spike times of a detailed conductance-based neuron model
  driven by stochastic spike arrival

abstract:
  Reduced models of neuronal activity such as Integrate-and-Fire models allow a
description of neuronal dynamics in simple, intuitive terms and are easy to
simulate numerically. We present a method to fit an Integrate-and-Fire-type
model of neuronal activity, namely a modified version of the Spike Response
Model, to a detailed Hodgkin-Huxley-type neuron model driven by stochastic
spike arrival. In the Hogkin-Huxley model, spike arrival at the synapse is
modeled by a change of synaptic conductance. For such conductance spike input,
more than 70% of the postsynaptic action potentials can be predicted with the
correct timing by the Integrate-and-Fire-type model. The modified Spike
Response Model is based upon a linearized theory of conductance-driven
Integrate-and-Fire neuron.


title: Phase Transition in Reconstituted Chromatin

abstract:
  By observing reconstituted chromatin by fluorescence microscopy (FM) and
atomic force microscopy (AFM), we found that the density of nucleosomes
exhibits a bimodal profile, i.e., there is a large transition between the dense
and dispersed states in reconstituted chromatin. Based on an analysis of the
spatial distribution of nucleosome cores, we deduced an effective thermodynamic
potential as a function of the nucleosome-nucleosome distance. This enabled us
to interpret the folding transition of chromatin in terms of a first-order
phase transition. This mechanism for the condensation of chromatin is discussed
in terms of its biological significance.


title: Evolvability is a Selectable Trait

abstract:
  Concomitant with the evolution of biological diversity must have been the
evolution of mechanisms that facilitate evolution, due to the essentially
infinite complexity of protein sequence space. We describe how evolvability can
be an object of Darwinian selection, emphasizing the collective nature of the
process. We quantify our theory with computer simulations of protein evolution.
These simulations demonstrate that rapid or dramatic environmental change leads
to selection for greater evolvability. The selective pressure for large scale
genetic moves, such as DNA exchange, becomes increasingly strong as the
environmental conditions become more uncertain. Our results demonstrate that
evolvability is a selectable trait and allow for the explanation of a large
body of experimental results.


title:
Existence and Stability of Standing Pulses in Neural Networks : I
  Existence

abstract:
  We consider the existence of standing pulse solutions of a neural network
integro-differential equation. These pulses are bistable with the zero state
and may be an analogue for short term memory in the brain. The network consists
of a single-layer of neurons synaptically connected by lateral inhibition. Our
work extends the classic Amari result by considering a non-saturating gain
function. We consider a specific connectivity function where the existence
conditions for single-pulses can be reduced to the solution of an algebraic
system. In addition to the two localized pulse solutions found by Amari, we
find that three or more pulses can coexist. We also show the existence of
nonconvex ``dimpled'' pulses and double pulses. We map out the pulse shapes and
maximum firing rates for different connection weights and gain functions.


title:
Existence and Stability of Standing Pulses in Neural Networks: II
  Stability

abstract:
  We analyze the stability of standing pulse solutions of a neural network
integro-differential equation. The network consists of a coarse-grained layer
of neurons synaptically connected by lateral inhibition with a non-saturating
nonlinear gain function. When two standing single-pulse solutions coexist, the
small pulse is unstable, and the large pulse is stable. The large single-pulse
is bistable with the ``all-off'' state. This bistable localized activity may
have strong implications for the mechanism underlying working memory. We show
that dimple pulses have similar stability properties to large pulses but double
pulses are unstable.


title:
Effects of receptor clustering on ligand dissociation: Theory and
  simulations

abstract:
  Receptor-ligand binding is a critical first step in signal transduction and
the duration of the interaction can impact signal generation. In mammalian
cells, clustering of receptors may be facilitated by heterogeneous zones of
lipids, known as lipid rafts. In vitro experiments show that disruption of
rafts significantly alters the dissociation of fibroblast growth factor-2
(FGF-2) from heparan sulfate proteoglycans, co-receptors for FGF-2. In this
paper, we develop a continuum stochastic formalism in order to (i) study how
rebinding affects the dissociation of ligands from a planar substrate, and (ii)
address the question of how receptor clustering influences ligand rebinding. We
find that clusters reduce the effective dissociation rate dramatically when the
clusters are dense and the overall surface density of receptors is low. The
effect is much less pronounced in the case of high receptor density and shows
non-monotonic behavior with time. These predictions are verified via lattice
Monte Carlo simulations. Comparison with experimental results suggests that the
theory does not capture the complete biological system. We speculate that
additional co-operative mechanisms might be present in order to increase ligand
retention, and present one possible ``internal diffusion'' model.


title: An ionically based mapping model with memory for cardiac restitution

abstract:
  Many features of the sequence of action potentials produced by repeated
stimulation of a cardiac patch can be modeled by a 1D mapping, but not the full
behavior observed in the restitution portrait: in particular, not (i) distinct
slopes for dynamic and S1-S2 restitution (rate dependence) and not (ii) long
transients in the approach to steady state (accomodation). To address these
shortcomings, \emph{ad hoc} 2D mappings, where the second variable is a
``memory'' variable, have been proposed; it seems that these models exhibit
some, but not all, of the relevant behavior. In this paper we introduce a new
2D mapping and determine a set of parameters for it that gives a rather
accurate description of the full restitution portrait found for one animal. The
changes in the mapping, compared to previous models, result from requiring that
the mapping can be derived as an asymptotic limit of a simple ionic model.
Among other benefits, one can interpret the parameters in the mapping in terms
of the ionic model. The ionic model is an extension of a two-current model that
adds a third dependent variable, a generalized concentration. The simplicity of
the ionic model and the physiological basis for the mapping contribute to the
usefulness of these ideas for describing restitution data in a variety of
contexts. The fitting procedure is straightforward and can easily be applied to
obtain a mathematical model for data from other experiments, including
experiments on different species. Uniqueness of the parameter choice is also
discussed.


title: Dynamics of force-induced DNA slippage

abstract:
  We study the basepairing dynamics of DNA with repetitive sequences where
local strand slippage can create, annihilate, and move bulge loops. Using an
explicit theoretical model, we find a rich dynamical behavior as a function of
an applied shear force f: reptation-like dynamics at f=f_c with a rupture time
scaling as N^3 with its length N, drift-diffusion dynamics for f_c < f < f^*,
and a dynamical transition to an unraveling mode of strand separation at f =
f^*. We predict a viscoelastic behavior for periodic DNA with time and force
scales that can be programmed into its sequence.


title: Tumor Gompertzian growth by cellular energetic balance

abstract:
  A macroscopic model of the tumor Gompertzian growth is proposed. The new
approach is based on the energetic balance among the different cell activities,
described by methods of statistical mechanics and related to the growth
inhibitor factors. The model is successfully applied to the multicellular tumor
spheroid data.


title:
Three-body Interactions Improve the Prediction of Rate and Mechanism in
  Protein Folding Models

abstract:
  Here we study the effects of many-body interactions on rate and mechanism in
protein folding, using the results of molecular dynamics simulations on
numerous coarse-grained C-alpha-model single-domain proteins. After adding
three-body interactions explicitly as a perturbation to a Go-like Hamiltonian
with native pair-wise interactions only, we have found 1) a significantly
increased correlation with experimental phi-values and folding rates, 2) a
stronger correlation of folding rate with contact order, matching the
experimental range in rates when the fraction of three-body energy in the
native state is ~ 20%, and 3) a considerably larger amount of 3-body energy
present in Chymotripsin inhibitor than other proteins studied.

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


title: Effects of internal fluctuations on the spreading of Hantavirus

abstract:
  We study the spread of Hantavirus over a host population of deer mice using a
population dynamics model. We show that taking into account the internal
fluctuations in the mouse population due to its discrete character strongly
alters the behaviour of the system. In addition to the familiar transition
present in the deterministic model, the inclusion of internal fluctuations
leads to the emergence of an additional deterministically hidden transition. We
determine parameter values that lead to maximal propagation of the disease, and
discuss some implications for disease prevention policies.


title: The effect of biodiversity on the Hantavirus epizootic

abstract:
  We analyze a mathematical model of the epizootic of Hantavirus in mice
population, including the effect of species which compete with the host. We
show that the existence of the second species has an important consequence for
the prevalence of the infectious agent in the host. When the two mice species
survive in the ecosystem, the competitive pressure of the second species may
lead to reduction or complete elimination of the prevalence of infection. The
transition between the disappearance of the infection and its presence occurs
at a critical value of the competitor's population, resembling a second order
phase transition in a statistical system. The results provide a rigorous
framework for the study of the impact of biodiversity in the propagation of
infectious diseases, and further lends itself to future experimental
verification.


title: Protein folding rates correlate with heterogeneity of folding mechanism

abstract:
  By observing trends in the folding kinetics of experimental 2-state proteins
at their transition midpoints, and by observing trends in the barrier heights
of numerous simulations of coarse grained, C-alpha model, Go proteins, we show
that folding rates correlate with the degree of heterogeneity in the formation
of native contacts. Statistically significant correlations are observed between
folding rates and measures of heterogeneity inherent in the native topology, as
well as between rates and the variance in the distribution of either
experimentally measured or simulated phi-values.


title:
The effects of non-native interactions on protein folding rates: Theory
  and simulation

abstract:
  Proteins are minimally frustrated polymers. However, for realistic protein
models non-native interactions must be taken into account. In this paper we
analyze the effect of non-native interactions on the folding rate and on the
folding free energy barrier. We present an analytic theory to account for the
modification on the free energy landscape upon introduction of non-native
contacts, added as a perturbation to the strong native interactions driving
folding. Our theory predicts a rate-enhancement regime at fixed temperature,
under the introduction of weak, non-native interactions. We have thoroughly
tested this theoretical prediction with simulations of a coarse-grained protein
model, by employing an off-lattice $C_\alpha$ model of the src-SH3 domain. The
strong agreement between results from simulations and theory confirm the non
trivial result that a relatively small amount of non-native interaction energy
can actually assist the folding to the native structure.


title: Do theoretical physicists care about the protein-folding problem?

abstract:
  The prediction of the biologically active native conformation of a protein is
one of the fundamental challenges of structural biology. This problem remains
yet unsolved mainly due to three factors: the partial knowledge of the
effective free energy function that governs the folding process, the enormous
size of the conformational space of a protein and, finally, the relatively
small differences of energy between conformations, in particular, between the
native one and the ones that make up the unfolded state.
  Herein, we recall the importance of taking into account, in a detailed
manner, the many interactions involved in the protein folding problem (such as
steric volume exclusion, Ramachandran forces, hydrogen bonds, weakly polar
interactions, coulombic energy or hydrophobic attraction) and we propose a
strategy to effectively construct a free energy function that, including the
effects of the solvent, could be numerically tractable. It must be pointed out
that, since the internal free energy function that is mainly described does not
include the constraints of the native conformation, it could only help to reach
the 'molten globule' state. We also discuss about the limits and the lacks from
which suffer the simple models that we, physicists, love so much.


title: Simulation and Experiment of Extinction or Adaptation

abstract:
  Can unicellular organisms survive a drastic temperature change, and adapt to
it after many generations? In simulations of the Penna model of biological
ageing, both extinction and adaptation were found for asexual and sexual
reproduction as well as for parasex. These model investigations are the basis
for the design of evolution experiments with heterotrophic flagellates.


title:
The Emergence of Scaling in Sequence-based Physical Models of Protein
  Evolution

abstract:
  It has recently been discovered that many biological systems, when
represented as graphs, exhibit a scale-free topology. One such system is the
set of structural relationships among protein domains. The scale-free nature of
this and other systems has previously been explained using network growth
models that, while motivated by biological processes, do not explicitly
consider the underlying physics or biology. In the present work we explore a
sequence-based model for the evolution protein structures and demonstrate that
this model is able to recapitulate the scale-free nature observed in graphs of
real protein structures. We find that this model also reproduces other
statistical feature of the protein domain graph. This represents, to our
knowledge, the first such microscopic, physics-based evolutionary model for a
scale-free network of biological importance and as such has strong implications
for our understanding of the evolution of protein structures and of other
biological networks.


title:
The role of M cells and the long QT syndrome in cardiac arrhythmias:
  simulation studies of reentrant excitations using a detailed
  electrophysiological model

abstract:
  In this numerical study, we investigate the role of intrinsic heterogeneities
of cardiac tissue due to M cells in the generation and maintenance of reentrant
excitations using the detailed Luo-Rudy dynamic model. This model has been
extended to include a description of the long QT 3 syndrome, and is studied in
both one dimension, corresponding to a cable traversing the ventricular wall,
and two dimensions, representing a transmural slice. We focus on two possible
mechanisms for the generation of reentrant events. We first investigate if
early-after-depolarizations occurring in M cells can initiate reentry. We find
that, even for large values of the long QT strength, the electrotonic coupling
between neighboring cells prevents early-after-depolarizations from creating a
reentry. We then study whether M cell domains, with their slow repolarization,
can function as wave blocks for premature stimuli. We find that the inclusion
of an M cell domain can result in some cases in reentrant excitations and we
determine the lifetime of the reentry as a function of the size and geometry of
the domain and of the strength of the long QT syndrome.

categories: q-bio.TO cond-mat.other nlin.PS q-bio.OT


title:
The Effects of Stacking on the Configurations and Elasticity of Single
  Stranded Nucleic Acids

abstract:
  Stacking interactions in single stranded nucleic acids give rise to
configurations of an annealed rod-coil multiblock copolymer. Theoretical
analysis identifies the resulting signatures for long homopolynucleotides: A
non monotonous dependence of size on temperature, corresponding effects on
cyclization and a plateau in the extension force law. Explicit numerical
results for poly(dA) and poly(rU) are presented.


title:
Multicellular Tumor Spheroid in an off-lattice Voronoi/Delaunay cell
  model

abstract:
  We study multicellular tumor spheroids by introducing a new three-dimensional
agent-based Voronoi/Delaunay hybrid model. In this model, the cell shape varies
from spherical in thin solution to convex polyhedral in dense tissues. The next
neighbors of the cells are provided by a weighted Delaunay triangulation with
in average linear computational complexity. The cellular interactions include
direct elastic forces and cell-cell as well as cell-matrix adhesion. The
spatiotemporal distribution of two nutrients -- oxygen and glucose -- is
described by reaction-diffusion equations. Viable cells consume the nutrients,
which are converted into biomass by increasing the cell size during G_1 phase.
  We test hypotheses on the functional dependence of the uptake rates and use
the computer simulation to find suitable mechanisms for induction of necrosis.
This is done by comparing the outcome with experimental growth curves, where
the best fit leads to an unexpected ratio of oxygen and glucose uptake rates.
The model relies on physical quantities and can easily be generalized towards
tissues involving different cell types. In addition, it provides many features
that can be directly compared with the experiment.


title:
Potential function of simplified protein models for discriminating
  native proteins from decoys: Combining contact interaction and local
  sequence-dependent geometry

abstract:
  An effective potential function is critical for protein structure prediction
and folding simulation. For simplified models of proteins where coordinates of
only $C_\alpha$ atoms need to be specified, an accurate potential function is
important. Such a simplified model is essential for efficient search of
conformational space. In this work, we present a formulation of potential
function for simplified representations of protein structures. It is based on
the combination of descriptors derived from residue-residue contact and
sequence-dependent local geometry. The optimal weight coefficients for contact
and local geometry is obtained through optimization by maximizing margins among
native and decoy structures. The latter are generated by chain growth and by
gapless threading. The performance of the potential function in blind test of
discriminating native protein structures from decoys is evaluated using several
benchmark decoy sets. This potential function have comparable or better
performance than several residue-based potential functions that require in
addition coordinates of side chain centers or coordinates of all side chain
atoms.


title: Dynamics and coding of a biologically-motivated network

abstract:
  A four-node network consisting of a negative loop controlling a positive one
is studied. It models some of the features of the p53 gene network. Using
piecewise linear dynamics with thresholds, the allowed dynamical classes are
fully characterized and coded. The biologically relevant situations are
identified and conclusions drawn concerning the effectiveness of the p53
network as a tumour inhibitor mechanism.


title: An Alternative Model of Amino Acid Replacement

abstract:
  The observed correlations between pairs of homologous protein sequences are
typically explained in terms of a Markovian dynamic of amino acid substitution.
This model assumes that every location on the protein sequence has the same
background distribution of amino acids, an assumption that is incompatible with
the observed heterogeneity of protein amino acid profiles and with the success
of profile multiple sequence alignment. We propose an alternative model of
amino acid replacement during protein evolution based upon the assumption that
the variation of the amino acid background distribution from one residue to the
next is sufficient to explain the observed sequence correlations of homologs.
The resulting dynamical model of independent replacements drawn from
heterogeneous backgrounds is simple and consistent, and provides a unified
homology match score for sequence-sequence, sequence-profile and
profile-profile alignment.


title:
Evolution of Spatially Inhomogeneous Eco-Systems: An Unified Model Based
  Approach

abstract:
  Recently we have extended our the "unified" model of evolutionary ecology to
incorporate the {\it spatial inhomogeneities} of the eco-system and the {\it
migration} of individual organisms from one patch to another within the same
eco-system. In this paper an extension of our recent model is investigated so
as to describe the {\it migration} and {\it speciation} in a more realistic
way.


title: Biological Profiling of Gene Groups utilizing Gene Ontology

abstract:
  Increasingly used high throughput experimental techniques, like DNA or
protein microarrays give as a result groups of interesting, e.g. differentially
regulated genes which require further biological interpretation. With the
systematic functional annotation provided by the Gene Ontology the information
required to automate the interpretation task is now accessible. However, the
determination of statistical significant e.g. molecular functions within these
groups is still an open question. In answering this question, multiple testing
issues must be taken into account to avoid misleading results. Here we present
a statistical framework that tests whether functions, processes or locations
described in the Gene Ontology are significantly enriched within a group of
interesting genes when compared to a reference group. First we define an exact
analytical expression for the expected number of false positives that allows us
to calculate adjusted p-values to control the false discovery rate. Next, we
demonstrate and discuss the capabilities of our approach using publicly
available microarray data on cell-cycle regulated genes. Further, we analyze
the robustness of our framework with respect to the exact gene group
composition and compare the performance with earlier approaches. The software
package GOSSIP implements our method and is made freely available at
http://gossip.gene-groups.net/


title: Phylogenetic invariants for stationary base composition

abstract:
  Changing base composition during the evolution of biological sequences can
mislead some of the phylogenetic inference techniques in current use. However,
detecting whether such a process has occurred may be difficult, since
convergent evolution may lead to similar base frequencies emerging from
different lineages.
  To study this situation, algebraic models of biological sequence evolution
are introduced in which the base composition is fixed throughout evolution.
Basic properties of the associated algebraic varieties are investigated,
including the construction of some phylogenetic invariants.


title: Generalized Poland-Scheraga model for supercoiled DNA

abstract:
  The Poland-Scheraga (PS) model for the helix-coil transition of DNA considers
the statistical mechanics of the thermally induced binding of two complementary
strands of DNA. In this paper, we show how to modify the PS model when a torque
is applied to the extremities of DNA: We propose a simple model for the energy
of twisted DNA and compute the entropy of a loop, subject to angular
constraints (supercoiling). The denaturation curves are shifted towards lower
or higher temperatures depending on the sign of the torque, and the UV
absorption peaks are softened. The properties of supercoiled DNA can be deduced
through the use of a numerical Legendre transform. In the homogeneous case, we
find that for weak supercoiling, the phenomenological quadratic law relating
the torsional energy to the number of unpaired bases is recovered.


title:
Relational patterns of gene expression via nonmetric multidimensional
  scaling analysis

abstract:
  Motivation:Microarray experiments result in large scale data sets that
require extensive mining and refining to extract useful information. We
demonstrate the usefulness of (nonmetric) multidimensional scaling (MDS) method
in analyzing a large number of genes. Applying MDS to the microarray data is
certainly not new, but the existing works are all on small numbers
  (< 100) of points to be analyzed. We have been developing an efficient novel
algorithm for nonmetric multidimensional scaling (nMDS) analysis for very large
data sets as a maximally unsupervised data mining device. We wish to
demonstrate its usefulness in the context of bioinformatics (unraveling
relational patterns among genes from time series data in this paper).
  Results: The Pearson correlation coefficient with its sign flipped is used to
measure the dissimilarity of the gene activities in transcriptional response of
cell-cycle-synchronized human fibroblasts to serum [Iyer {\it et al}., Science
{\bf 283}, 83 (1999)]. These dissimilarity data have been analyzed with our
nMDS algorithm to produce an almost circular relational pattern of the genes.
The obtained pattern expresses a temporal order in the data in this example;
the temporal expression pattern of the genes rotates along this circular
arrangement and is related to the cell cycle. For the data we analyze in this
paper we observe the following. If an appropriate preparation procedure is
applied to the original data set, linear methods such as the principal
component analysis (PCA) could achieve reasonable results, but without data
preprocessing linear methods such as PCA cannot achieve a useful picture.
Furthermore, even with an appropriate data preprocessing, the outcomes of
linear procedures are not as clearcut as those by nMDS without preprocessing.


title:
Rate-dependent propagation of cardiac action potentials in a
  one-dimensional fiber

abstract:
  Action potential duration (APD) restitution, which relates APD to the
preceding diastolic interval (DI), is a useful tool for predicting the onset of
abnormal cardiac rhythms. However, it is known that different pacing protocols
lead to different APD restitution curves (RCs). This phenomenon, known as APD
rate-dependence, is a consequence of memory in the tissue. In addition to APD
restitution, conduction velocity restitution also plays an important role in
the spatiotemporal dynamics of cardiac tissue. We present new results
concerning rate-dependent restitution in the velocity of propagating action
potentials in a one-dimensional fiber. Our numerical simulations show that,
independent of the amount of memory in the tissue, waveback velocity exhibits
pronounced rate-dependence and the wavefront velocity does not. Moreover, the
discrepancy between waveback velocity RCs is most significant for small DI. We
provide an analytical explanation of these results, using a system of coupled
maps to relate the wavefront and waveback velocities. Our calculations show
that waveback velocity rate-dependence is due to APD restitution, not memory.


title: Order independent structural alignment of circularly permuted proteins

abstract:
  Circular permutation connects the N and C termini of a protein and
concurrently cleaves elsewhere in the chain, providing an important mechanism
for generating novel protein fold and functions. However, their in genomes is
unknown because current detection methods can miss many occurances, mistaking
random repeats as circular permutation. Here we develop a method for detecting
circularly permuted proteins from structural comparison. Sequence order
independent alignment of protein structures can be regarded as a special case
of the maximum-weight independent set problem, which is known to be
computationally hard. We develop an efficient approximation algorithm by
repeatedly solving relaxations of an appropriate intermediate integer
programming formulation, we show that the approximation ratio is much better
then the theoretical worst case ratio of $r = 1/4$. Circularly permuted
proteins reported in literature can be identified rapidly with our method,
while they escape the detection by publicly available servers for structural
alignment.


title: Developing optimal nonlinear scoring function for protein design

abstract:
  Motivation. Protein design aims to identify sequences compatible with a given
protein fold but incompatible to any alternative folds. To select the correct
sequences and to guide the search process, a design scoring function is
critically important. Such a scoring function should be able to characterize
the global fitness landscape of many proteins simultaneously.
  Results. To find optimal design scoring functions, we introduce two geometric
views and propose a formulation using mixture of nonlinear Gaussian kernel
functions. We aim to solve a simplified protein sequence design problem. Our
goal is to distinguish each native sequence for a major portion of
representative protein structures from a large number of alternative decoy
sequences, each a fragment from proteins of different fold. Our scoring
function discriminate perfectly a set of 440 native proteins from 14 million
sequence decoys. We show that no linear scoring function can succeed in this
task. In a blind test of unrelated proteins, our scoring function misclassfies
only 13 native proteins out of 194. This compares favorably with about 3-4
times more misclassifications when optimal linear functions reported in
literature are used. We also discuss how to develop protein folding scoring
function.


title: Self consistent proteomic field theory of stochastic gene switches

abstract:
  We present a self-consistent field approximation to the problem of the
genetic switch composed of two mutually repressing/activating genes. The
protein and DNA state dynamics are treated stochastically and on equal footing.
In this approach the mean influence of the proteomic cloud created by one gene
on the action of another is self-consistently computed. Within this
approximation a broad range of stochastic genetic switches may be solved
exactly in terms of finding the probability distribution and its moments. A
much larger class of problems, such as genetic networks and cascades also
remain exactly solvable with this approximation. We discuss in depth certain
specific types of basic switches, which are used by biological systems and
compare their behavior to the expectation for a deterministic switch.


title: Statistics of infections with diversity in the pathogenicity

abstract:
  The statistics of outbreaks in a model for the propagation of meningococcal
diseases is analyzed, taking into account the possibility that the population
is fragmented into weakly connected patches. It is shown that, depending on the
size of of the sample studied, the ratio between the variance and the mean of
infected cases can vary from one (Poisson statistics) to the inverse of the
infection rate.


title:
Simulating the Impact of a Molecular 'Decision-Process' on Cellular
  Phenotype and Multicellular Patterns in Brain Tumors

abstract:
  Experimental evidence indicates that human brain cancer cells proliferate or
migrate, yet do not display both phenotypes at the same time. Here, we present
a novel computational model simulating this cellular decision-process leading
up to either phenotype based on a molecular interaction network of genes and
proteins. The model's regulatory network consists of the epidermal growth
factor receptor (EGFR), its ligand transforming growth factor-a (TGFa), the
downstream enzyme phospholipaseC-gamma (PLCg) and a mitosis-associated response
pathway. This network is activated by autocrine TGFa secretion, and the
EGFR-dependent downstream signaling this step triggers, as well as modulated by
an extrinsic nutritive glucose gradient. Employing a framework of mass action
kinetics within a multiscale agent-based environment, we analyze both the
emergent multicellular behavior of tumor growth and the single-cell molecular
profiles that change over time and space. Our results show that one can indeed
simulate the dichotomy between cell migration and proliferation based solely on
an EGFR decision network. It turns out that these behavioral decisions on the
single cell level impact the spatial dynamics of the entire cancerous system.
Furthermore, the simulation results yield intriguing experimentally testable
hypotheses also on the sub-cellular level such as spatial cytosolic
polarization of PLCg towards an extrinsic chemotactic gradient. Implications of
these results for future works, both on the modeling and experimental side are
discussed.


title: Recurrent epidemics in small world networks

abstract:
  The effect of spatial correlations on the spread of infectious diseases was
investigated using a stochastic SIR (Susceptible-Infective-Recovered) model on
complex networks. It was found that in addition to the reduction of the
effective transmission rate, through the screening of infectives, spatial
correlations may have another major effect through the enhancement of
stochastic fluctuations. As a consequence large populations will have to become
even larger to 'average out' significant differences from the solution of
deterministic models. Furthermore, time series of the (unforced) model provide
patterns of recurrent epidemics with slightly irregular periods and realistic
amplitudes, suggesting that stochastic models together with complex networks of
contacts may be sufficient to describe the long term dynamics of some diseases.
The spatial effects were analysed quantitatively by modelling measles and
pertussis, using a SEIR (Susceptible-Exposed-Infective-Recovered) model. Both
the period and the spatial coherence of the epidemic peaks of pertussis are
well described by the unforced model for realistic values of the parameters.


title:
Physical Schemata Underlying Biological Pattern Formation - Examples,
  Issues and Strategies

abstract:
  Biological systems excel at building spatial structures on scales ranging
from nanometers to kilometers and exhibit temporal patterning from milliseconds
to years. One approach that nature has taken to accomplish this relies on the
harnessing of pattern-forming processes of non-equilibrium physics and
chemistry. For these systems, the study of biological pattern formation starts
with placing a biological phenomenon of interest within the context of the
proper pattern-formation schema and then focusing on the ways in which control
is exerted to adapt the pattern to the needs of the organism. This approach is
illustrated by several examples, notably bacterial colonies (diffusive-growth
schema) and intracellular calcium waves (excitable-media schema).


title:
Characterizing neuromorphologic alterations with additive shape
  functionals

abstract:
  The complexity of a neuronal cell shape is known to be related to its
function. Specifically, among other indicators, a decreased complexity in the
dendritic trees of cortical pyramidal neurons has been associated with mental
retardation. In this paper we develop a procedure to address the
characterization of morphological changes induced in cultured neurons by
over-expressing a gene involved in mental retardation. Measures associated with
the multiscale connectivity, an additive image functional, are found to give a
reasonable separation criterion between two categories of cells. One category
consists of a control group and two transfected groups of neurons, and the
other, a class of cat ganglionary cells. The reported framework also identified
a trend towards lower complexity in one of the transfected groups. Such results
establish the suggested measures as an effective descriptors of cell shape.


title: Competing associations in six-species predator-prey models

abstract:
  We study a set of six-species ecological models where each species has two
predators and two preys. On a square lattice the time evolution is governed by
iterated invasions between the neighboring predator-prey pairs chosen at random
and by a site exchange with a probability Xs between the neutral pairs. These
models involve the possibility of spontaneous formation of different defensive
alliances whose members protect each other from the external invaders. The
Monte Carlo simulations show a surprisingly rich variety of the stable spatial
distributions of species and subsequent phase transitions when tuning the
control parameter Xs. These very simple models are able to demonstrate that the
competition between these associations influences their composition. Sometimes
the dominant association is developed via a domain growth. In other cases
larger and larger invasion processes preceed the prevalence of one of the
stable asociations. Under some conditions the survival of all the species can
be maintained by the cyclic dominance occuring between these associations.


title: The architecture of the protein domain universe

abstract:
  Understanding the design of the universe of protein structures may provide
insights into protein evolution. We study the architecture of the protein
domain universe, which has been found to poses peculiar scale-free properties
(Dokholyan et al., Proc. Natl. Acad. Sci. USA 99: 14132-14136 (2002)). We
examine the origin of these scale-free properties of the graph of protein
domain structures (PDUG) and determine that that the PDUG is not modular, i.e.
it does not consist of modules with uniform properties. Instead, we find the
PDUG to be self-similar at all scales. We further characterize the PDUG
architecture by studying the properties of the hub nodes that are responsible
for the scale-free connectivity of the PDUG. We introduce a measure of the
betweenness centrality of protein domains in the PDUG and find a power-law
distribution of the betweenness centrality values. The scale-free distribution
of hubs in the protein universe suggests that a set of specific statistical
mechanics models, such as the self-organized criticality model, can potentially
identify the principal driving forces of molecular evolution. We also find a
gatekeeper protein domain, removal of which partitions the largest cluster into
two large sub-clusters. We suggest that the loss of such gatekeeper protein
domains in the course of evolution is responsible for the creation of new fold
families.


title:
Of sequence and structure: Strategies of protein thermostability in
  evolutionary perspective

abstract:
  In this work we employ various methods of analysis (unfolding simulations and
comparative analysis of structures and sequences of proteomes of thermophilic
organisms) to show that organisms can follow two major strategies of
thermophilic adaptation: (i) General, non-specific, structure-based, when
proteomes of certain thermophilic organisms show significant structural bias
toward proteins of higher compactness. In this case thermostability is achieved
by greater overall number of stabilizing contacts, none of which may be
especially strong, and (ii) Specific, sequence-based, whereby sequence
variations aimed at strengthening specific types of interactions (e.g.
electrostatics) are applied without significantly changing structures of
proteins. The choice of a certain strategy is a direct consequence of
evolutionary history and environmental conditions of particular (hyper)
thermophilic species: ancient hyperthermophilic organisms that directly evolved
in hot environment, pursued mostly structure-based strategy, while later
evolved organisms whose thermophilic adaptation was a consequence of their
recolonization of hot environment, pursued specific, sequence-based strategy of
thermophilic adaptation.


title:
A subjective distance between stimuli: quantifying the metric structure
  of representations

abstract:
  As subjects perceive the sensory world, different stimuli elicit a number of
neural representations. Here, a subjective distance between stimuli is defined,
measuring the degree of similarity between the underlying representations. As
an example, the subjective distance between different locations in space is
calculated from the activity of rodent hippocampal place cells, and lateral
septal cells. Such a distance is compared to the real distance, between
locations. As the number of sampled neurons increases, the subjective distance
shows a tendency to resemble the metrics of real space.


title: Network properties of protein structures

abstract:
  Protein structures can be studied as complex networks of interacting amino
acids. We study proteins of different structural classes from the network
perspective. Our results indicate that proteins, regardless of their structural
class, show small-world network property. Various network parameters offer
insight into the structural organisation of proteins and provide indications of
modularity in protein networks.


title:
Inferring Network Mechanisms: The Drosophila melanogaster Protein
  Interaction Network

abstract:
  Naturally occurring networks exhibit quantitative features revealing
underlying growth mechanisms. Numerous network mechanisms have recently been
proposed to reproduce specific properties such as degree distributions or
clustering coefficients. We present a method for inferring the mechanism most
accurately capturing a given network topology, exploiting discriminative tools
from machine learning. The Drosophila melanogaster protein network is
confidently and robustly (to noise and training data subsampling) classified as
a duplication-mutation-complementation network over preferential attachment,
small-world, and other duplication-mutation mechanisms. Systematic
classification, rather than statistical study of specific properties, provides
a discriminative approach to understand the design of complex networks.


title: Unidentifiable divergence times in rates-across-sites models

abstract:
  The rates-across-sites assumption in phylogenetic inference posits that the
rate matrix governing the Markovian evolution of a character on an edge of the
putative phylogenetic tree is the product of a character-specific scale factor
and a rate matrix that is particular to that edge. Thus, evolution follows
basically the same process for all characters, except that it occurs faster for
some characters than others. To allow estimation of tree topologies and edge
lengths for such models, it is commonly assumed that the scale factors are not
arbitrary unknown constants, but rather unobserved, independent, identically
distributed draws from a member of some parametric family of distributions. A
popular choice is the gamma family. We consider an example of a clock-like tree
with three taxa, one unknown edge length, and a parametric family of scale
factor distributions that contain the gamma family. This model has the property
that, for a generic choice of unknown edge length and scale factor
distribution, there is another edge length and scale factor distribution which
generates data with exactly the same distribution, so that even with infinitely
many data it will be typically impossible to make correct inferences about the
unknown edge length.


title:
Computation of amplification for systems arising from cellular signaling
  pathways

abstract:
  A commonly employed measure of the signal amplification properties of an
input/output system is its induced L2 norm, sometimes also known as "H
infinity" gain. In general, however, it is extremely difficult to compute the
numerical value for this norm, or even to check that it is finite, unless the
system being studied is linear. This paper describes a class of systems for
which it is possible to reduce this computation to that of finding the norm of
an associated linear system. In contrast to linearization approaches, a precise
value, not an estimate, is obtained for the full nonlinear model. The class of
systems that we study arose from the modeling of certain biological
intracellular signaling cascades, but the results should be of wider
applicability.


title: Design of a folding inhibitor of the HIV-1 Protease

abstract:
  Being HIV-1-PR an essential enzyme in the viral life cycle, its inhibition
can control AIDS. Because the folding of single domain proteins, like HIV-1-PR
is controlled by local elementary structures (LES, folding units stabilized by
strongly interacting, highly conserved amino acids) which have evolved over
myriads of generations to recognize and strongly attract each other so as to
make the protein fold fast, we suggest a novel type of HIV-1-PR inhibitors
which interfere with the folding of the protein: short peptides displaying the
same amino acid sequence of that of LES. Theoretical and experimental evidence
for the specificity and efficiency of such inhibitors are presented.


title:
Statistical properties of DNA sequences revisited: the role of inverse
  bilateral symmetry in bacterial chromosomes

abstract:
  Herein it is shown that in order to study the statistical properties of DNA
sequences in bacterial chromosomes it suffices to consider only one half of the
chromosome because they are similar to its corresponding complementary sequence
in the other half. This is due to the inverse bilateral symmetry of bacterial
chromosomes. Contrary to the classical result that DNA coding regions of
bacterial genomes are purely uncorrelated random sequences, here it is shown,
via a renormalization group approach, that DNA random fluctuations of single
bases are modulated by log-periodic variations. Distance series of triplets
display long-range correlations in each half of the intact chromosome and in
intronless protein-coding sequences, or both long-range correlations and
log-periodic modulations along the whole chromosome. Hence scaling analyses of
distance series of DNA sequences have to consider the functional units of
bacterial chromosomes.


title:
All-or-none switching of transcriptional activity on single DNA
  molecules caused by a discrete conformational transition

abstract:
  Recently, it has been confirmed that long duplex DNA molecules with sizes
larger than several tens of kilo-base pairs (kbp), exhibit a discrete
conformational transition from an elongated coil state to a compact globule
state upon the addition of various kinds of chemical species that usually
induce DNA condensation. In this study, we performed a single-molecule
observation on a large DNA, Lambda ZAP II DNA (ca. 41 kbp), in a solution
containing RNA polymerase and substrates along with spermine, a tetravalent
cation, at different concentrations, by use of fluorescence staining of both
DNA and RNA. We found that transcription, or RNA production, is completely
inhibited in the compact state, but is actively performed in the unfolded coil
state. Such an all-or-none effect on transcriptional activity induced by the
discrete conformational transition of single DNA molecules is discussed in
relation to the mechanism of the regulation of large-scale genetic activity.


title: Epitope analysis for influenza vaccine design

abstract:
  Until now, design of the annual influenza vaccine has relied on phylogenetic
or whole-sequence comparisons of the viral coat proteins hemagglutinin and
neuraminidase, with vaccine effectiveness assumed to correlate monotonically to
the vaccine-influenza sequence difference. We use a theory from statistical
mechanics to quantify the non-monotonic immune response that results from
antigenic drift in the epitopes of the hemagglutinin and neuraminidase
proteins. The results explain the ineffectiveness of the 2003--2004 influenza
vaccine in the United States and provide an accurate measure by which to
optimize the effectiveness of future annual influenza vaccines.


title:
Monte Carlo Simulation and Statistical Analysis of Genetic Information
  Coding

abstract:
  The rules that specify how the information contained in DNA codes amino
acids, is called "the genetic code". Using a simplified version of the Penna
nodel, we are using computer simulations to investigate the importance of the
genetic code and the number of amino acids in Nature on population dynamics. We
find that the genetic code is not a random pairing of codons to amino acids and
the number of amino acids in Nature is an optimum under mutations.


title:
5,6-dihydroxyindole-2-carboxylic acid (DHICA): a First Principles
  Density-Functional Study

abstract:
  We report first principles density functional calculations for
5,6-dihydroxyindole-2-carboxylic acid (DHICA) and several reduced forms. DHICA
and 5,6-dihydroxyindole (DHI) are believed to be the basic building blocks of
the eumelanins. Our results show that carboxylation has a significant effect on
the physical properties of the molecules. In particular, the relative
stabilities and the HOMO-LUMO gaps (calculated with the $\Delta$SCF method) of
the various redox forms are strongly affected. We predict that, in contrast to
DHI, the density of unpaired electrons, and hence the ESR signal, in DHICA is
negligibly small.

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


title:
Collective Dynamics of Active Elements: Task Allocation and Pheromone
  Trailing

abstract:
  Collective behavior of active elements inspired by mass of biological
organisms is addressed. Especially, two topics are focused on among amazing
behaviors performed by colony of ants. First, task allocation phenomena are
treated from the viewpoint of proportion regulation of population between
different states. Using a dynamical model consisting of elements and external
``stock materials'', adaptability against various disturbances is numerically
studied. In addition, a dynamical model for a colony ants interacting via two
kind of pheromones is studied, in which simulated ants, as a mass, are shown to
make an efficient foraging flexibly varying the foraging tactics according to
feeding schedules. Finally, experiments are performed with robots moving in
virtual pheromone fields simulated by CG and CCD camera feedback system. Trail
formation processes are demonstrated by this multi-robot system.


title: A microscopic model of evolution of recombination

abstract:
  We study the evolution of recombination using a microscopic model developed
within the frame of the theory of quantitative traits. Two components of
fitness are considered: a static one that describes adaptation to environmental
factors not related to the population itself, and a dynamic one that accounts
for interactions between organisms e.g. competition. We focus on the dynamics
of colonization of an empty niche. As competition is a function of the
population, selection pressure rapidly changes in time. The simulations show
that both in the case of flat and steep static fitness landscapes,
recombination provides a high velocity of movement in the phenotypic space thus
allowing recombinants to colonize the highest fitness regions earlier than non
recombinants that are often driven to extinction. The stabilizing effects of
competition and assortativity are also discussed. Finally, the analysis of
phase diagrams shows that competition is the key factor for the evolution of
recombination, while assortativity plays a significant role only in small
populations.


title: Cooperation driven by mutations in multi-person Prisoner's Dilemma

abstract:
  The n-person Prisoner's Dilemma is a widely used model for populations where
individuals interact in groups. The evolutionary stability of populations has
been analysed in the literature for the case where mutations in the population
may be considered as isolated events. For this case, and assuming simple
trigger strategies and many iterations per game, we analyse the rate of
convergence to the evolutionarily stable populations. We find that for some
values of the payoff parameters of the Prisoner's Dilemma this rate is so low
that the assumption, that mutations in the population are infrequent on that
timescale, is unreasonable. Furthermore, the problem is compounded as the group
size is increased. In order to address this issue, we derive a deterministic
approximation of the evolutionary dynamics with explicit, stochastic mutation
processes, valid when the population size is large. We then analyse how the
evolutionary dynamics depends on the following factors: mutation rate, group
size, the value of the payoff parameters, and the structure of the initial
population. In order to carry out the simulations for groups of more than just
a few individuals, we derive an efficient way of calculating the fitness
values. We find that when the mutation rate per individual and generation is
very low, the dynamics is characterised by populations which are evolutionarily
stable. As the mutation rate is increased, other fixed points with a higher
degree of cooperation become stable. For some values of the payoff parameters,
the system is characterised by (apparently) stable limit cycles dominated by
cooperative behaviour. The parameter regions corresponding to high degree of
cooperation grow in size with the mutation rate, and in number with the group
size.


title: Probabilistic pathway representation of cognitive information

abstract:
  We present for mental processes the program of mathematical mapping which has
been successfully realized for physical processes. We emphasize that our
project is not about mathematical simulation of brain's functioning as a
complex physical system, i.e., mapping of physical and chemical processes in
the brain on mathematical spaces. The project is about mapping of purely mental
processes on mathematical spaces. We present various arguments -- philosophic,
mathematical, information, and neurophysiological -- in favor of the $p$-adic
model of mental space. $p$-adic spaces have structures of hierarchic trees and
in our model such a tree hierarchy is considered as an image of neuronal
hierarchy. Hierarchic neural pathways are considered as fundamental units of
information processing. As neural pathways can go through whole body, the
mental space is produced by the whole neural system. Finally, we develop
Probabilistic Neural Pathway Model in that Mental States are represented by
probability distributions on mental space.

categories: q-bio.NC cond-mat.dis-nn math.DS quant-ph


title: Probing vibrational energy relaxation in proteins using normal modes

abstract:
  Vibrational energy relaxation (VER) of a selected mode in cytochrome c
(hemeprotein) in vacuum is studied using two theoretical approaches: One is the
equilibrium simulation approach with quantum correction factors, and the other
is the reduced model approach which describes the protein as an ensemble of
normal modes coupled with nonlinear coupling elements. Both methods result in
estimates of VER time (sub ps) for a CD stretching mode in the protein at room
temperature, that are in accord with the experimental data of Romesberg's
group. The applicability of the two methods is examined through a discussion of
the validity of Fermi's golden rule on which the two methods are based.


title:
Medium effects on the selection of sequences folding into stable
  proteins in a simple model

abstract:
  We study the medium effects on the selection of sequences in protein folding
by taking account of the surface potential in HP-model. Our analysis on the
proportion of H and P monomers in the sequences gives a direct interpretation
that the lowly designable structures possess small average gap. The numerical
calculation by means of our model exhibits that the surface potential enhances
the average gap of highly designable structures. It also shows that a most
stable structure may be no longer the most stable one if the medium parameters
changed.


title:
Sequence-dependent B-A transitions in DNA in silico: Electrostatic
  condensation mechanism

abstract:
  Dynamics of the polymorphic A<->B transitions in DNA is compared for two
polypurine sequences, poly(dA).poly(dT) and poly(dG).poly(dC), long known to
exhibit contrasting properties in experiments. In free molecular dynamics
simulations reversible transitions are induced by changing the size of a water
drop around DNA neutralized by Na ions. In poly(dG).poly(dC) the B<->A
transitions are easy, smooth and perfectly reversible. In contrast, a B->A
transition in poly(dA).poly(dT) dodecamer fragment could not be obtained even
though its A-form is stable under low hydration. Normal B->A transitions are
observed, however, in long poly(dA).poly(dT) stretches flanked by GC pairs. An
intermediate range of hydration numbers is identified where opposite
transitions are observed in the two dodecamer fragments, namely, A->B in
poly(dA).poly(dT) and B->A in poly(dG).poly(dC). With hydration numbers close
to the stability limit of the B-form, the two sequences exhibit qualitatively
different counterion distributions, with a characteristic accumulation of Na
ions next to the opening of the minor groove in poly(dA).poly(dT). This
difference can explain an increased persistence of poly(dA).poly(dT) DNA
towards A-form in crystalline and amorphous fibers as compared to solution
conditions. The good overall agreement with experimental data corroborates the
general role of the electrostatic condensation mechanism in the A/B
polymorphism in DNA.


title:
Does telomere elongation in cloned organisms lead to a longer lifespan
  if cancer is considered ?

abstract:
  ... By additionally considering a two-mutation model for carcinogenesis and
indefinite proliferation by the activation of telomerase, we demonstrate that
the risk of dying doe to cancer can outweigh the positive effect of longer
telomeres on the longevity.


title: Analysis of evolution through competitive selection

abstract:
  Recent studies of in vitro evolution of DNA via protein binding indicate that
the evolution behavior is qualitatively different in different parameter
regimes. I here present a general theory that is valid for a wide range of
parameters, and which reproduces and extends previous results. Specifically,
the mean-field theory of a general translation-invariant model can be reduced
to the basic diffusion equation with a dynamic boundary condition. The simple
analytical form yields both quantitatively accurate predictions and valuable
insight into the principles involved. In particular, I introduce a cutoff
criterion for finite populations that illustrates both of these qualities.


title: Mathematics, Biology, and Physics: Interactions and Interdependence

abstract:
  This paper traces the seminal roles that physicists and mathematicians have
played in the conceptual development of the biological sciences in the past,
and especially in the 19th and 20th centuries.


title:
Periodic Oscillations of Blood Cell Populations in Chronic Myelogenous
  Leukemia

abstract:
  We develop some techniques to prove analytically the existence and stability
of long period oscillations of stem cell populations in the case of periodic
chronic myelogenous leukemia. Such a periodic oscillation $p_\infty $ can be
analytically constructed when the hill coefficient involved in the nonlinear
feedback is infinite, and we show it is possible to obtain a contractive
returning map (for the semiflow defined by the modeling functional differential
equation) in a closed and convex cone containing $p_\infty $ when the hill
coefficient is large, and the fixed point of such a contractive map gives the
long period oscillation previously observed both numerically and
experimentally.


title: Oscillations in a maturation model of blood cell production

abstract:
  In this paper we use a continuous model to describe the development of a
single cell lineage following the committal of stem cells. Three separate
controls are implemented in the model, namely the proliferative control of stem
cells, the proliferative control of developing blast cells, and the peripheral
control of stem cell committal by circulating blood cell density. We show that
variation of parameters in all three control systems can cause oscillations,
and that the characters of these oscillations are very different. This allows
us some potential insight into the mechanisms that may be operative in some of
the dynamic blood diseases like cyclical neutropenia and periodic chronic
myelogenous leukemia.


title:
A neural mechanism for binaural pitch perception via ghost stochastic
  resonance

abstract:
  We present a physiologically plausible binaural mechanism for the perception
of the pitch of complex sounds via ghost stochastic resonance. In this scheme,
two neurons are driven by noise and different periodic signal each (with
frequencies f1=kf0 and f2=(k+1)f0, where k>1), and their outputs (plus noise)
are applied synaptically to a third neuron. Our numerical results, using the
Morris-Lecar neuron model with chemical synapses explicity considered, show
that intermediate noise levels enhance the response of the third neuron at
frequencies close to f0, as in the cases previously described of ghost
resonance. For the case of inharmonic combinations of inputs (both frequencies
shifted by the same amount Df) noise is also seen to enhance the response of
the third neuron at a frequency fr with also shift linearly with Df. In
addition, we show that similar resonances can be observed as a function of the
synaptic time constant. The suggested ghost-resonance-based stochastic
mechanism can thus arise either at the peripheral level or at a higher level of
neural processing in the perception of the pitch


title:
Oligomerization of amyloid Abeta peptides using hydrogen bonds and
  hydrophobicity forces

abstract:
  The 16-22 amino acid fragment of the beta-amyloid peptide associated with the
Alzheimer's disease, Abeta, is capable of forming amyloid fibrils. Here we
study the aggregation mechanism of Abeta(16-22) peptides by unbiased
thermodynamic simulations at the atomic level for systems of one, three and six
Abeta(16-22) peptides. We find that the isolated Abeta(16-22) peptide is mainly
a random coil in the sense that both the alpha-helix and beta-strand contents
are low, whereas the three- and six-chain systems form aggregated structures
with a high beta-sheet content. Furthermore, in agreement with experiments on
Abeta(16-22) fibrils, we find that large parallel beta-sheets are unlikely to
form. For the six-chain system, the aggregated structures can have many
different shapes, but certain particularly stable shapes can be identified.


title:
Pattern formation within Escherichia coli: diffusion, membrane
  attachment, and self-interaction of MinD molecules

abstract:
  In E. coli, accurate cell division depends upon the oscillation of Min
proteins from pole to pole. We provide a model for the polar localization of
MinD based only on diffusion, a delay for nucleotide exchange, and different
rates of attachment to the bare membrane and the occupied membrane. We derive
analytically the probability density, and correspondingly the length scale, for
MinD attachment zones. Our simple analytical model illustrates the processes
giving rise to the observed localization of cellular MinD zones.


title:
Observations of magnetic field induced contraction of fission yeast
  cells using optical projection microscopy

abstract:
  The charges in live cells interact with or produce electric fields, which
results in enormous dielectric responses, flexoelectricity, and related
phenomena. Here we report on a contraction of schizosacchraoymces pombe
(fission yeast) cells induced by magnetic fields, as observed using a phase
sensitive projection image technique. Unlike electric fields, magnetic fields
only act on moving charges. The observed behavior is quite remarkable, and may
result from a contractile Lorentz force acting on diamagnetic screening
currents. This would indicate extremely high intracellular charge mobilities.
Besides, we observed a large electro - optical response from fission yeast
cells.


title:
Latent periodicity of serine-threonine and tyrosine protein kinases and
  another protein families

abstract:
  We identified latent periodicity in catalytic domains of approximately 85% of
serine/threonine and tyrosine protein kinases. Similar results were obtained
for other 22 protein domains. We also designed the method of noise
decomposition, which is aimed to distinguish between different periodicity
types of the same period length. The method is to be used in conjunction with
the cyclic profile alignment, and this combination is able to reveal
structure-related or function-related patterns of latent periodicity. Possible
origins of the periodic structure of protein kinase active sites are discussed.
Summarizing, we presume that latent periodicity is the common property of many
catalytic protein domains.


title: Enzyme as a thermal resonance pump

abstract:
  We found latent periodicity of 150 protein families now. We suppose that
latent periodicity can determine a spectrum of resonance oscillations in
proteins.


title: Dependence of RNA secondary structure on the energy model

abstract:
  We analyze a microscopic RNA model, which includes two widely used models as
limiting cases, namely it contains terms for bond as well as for stacking
energies. We numerically investigate possible changes in the qualitative and
quantitative behaviour while going from one model to the other; in particular
we test, whether a transition occurs, when continuously moving from one model
to the other. For this we calculate various thermodynamic quantities, both at
zero temperature as well as at finite temperatures. All calculations can be
done efficiently in polynomial time by a dynamic programming algorithm. We do
not find a sign for transition between the models, but the critical exponent
$\nu$ of the correlation length, describing the phase transition in all models
to an ordered low-temperature phase, seems to depend continuously on the model.
Finally, we apply the epsilon-Coupling method, to study low excitations. The
exponent $\theta$ describing the energy-scaling of the excitations seems to
depend not much on the energy model.


title:
SUMO Substrates and Sites Prediction Combining Pattern Recognition and
  Phylogenetic Conservation

abstract:
  Small Ubiquitin-related modifier (SUMO) proteins are widely expressed in
eukaryotic cells, which are reversibly coupled to their substrates by motif
recognition, called sumoylation. Two interesting questions are 1) how many
potential SUMO substrates may be included in mammalian proteomes, such as human
and mouse, 2) and given a SUMO substrate, can we recognize its sumoylation
sites? To answer these two questions, previous prediction systems of SUMO
substrates mainly adopted the pattern recognition methods, which could get high
sensitivity with relatively too many potential false positives. So we use
phylogenetic conservation between mouse and human to reduce the number of
potential false positives.


title: How to compute using globally coupled oscillators

abstract:
  Synchronization is known to play a vital role within many highly connected
neural systems such as the olfactory systems of fish and insects. In this paper
we show how one can robustly and effectively perform practical computations
using small perturbations to a very simple globally coupled network of coupled
oscillators. Computations are performed by exploiting the spatio-temporal
dynamics of a robust attracting heteroclinic network (also referred to as
`winnerless competition' dynamics). We use different cluster synchronization
states to encode memory states and use this to design a simple multi-base
counter. The simulations indicate that this gives a robust computational system
exploiting the natural dynamics of the system.


title: Thermodynamic Prediction of Protein Neutrality

abstract:
  We present a simple theory that uses thermodynamic parameters to predict the
probability that a protein retains the wildtype structure after one or more
random amino acid substitutions. Our theory predicts that for large numbers of
substitutions the probability that a protein retains its structure will decline
exponentially with the number of substitutions, with the severity of this
decline determined by properties of the structure. Our theory also predicts
that a protein can gain extra robustness to the first few substitutions by
increasing its thermodynamic stability. We validate our theory with simulations
on lattice protein models and by showing that it quantitatively predicts
previously published experimental measurements on subtilisin and our own
measurements on variants of TEM1 beta-lactamase. Our work unifies observations
about the clustering of functional proteins in sequence space, and provides a
basis for interpreting the response of proteins to substitutions in protein
engineering applications.


title: Hidden symmetries in primary sequences of small alpha proteins

abstract:
  Proteins have regular tertiary structures but irregular amino acid sequences.
This made it very difficult to decode the structural information in the protein
sequences. Here we demonstrate that many small alpha protein domains have
hidden sequence symmetries characteristic of their pseudo-symmetric tertiary
structures. We also present a modified method of recurrent plot to reveal this
kind of the hidden sequence symmetry. The results may enable us understand
parts of the relations between protein sequences and their tertiary structures,
i.e, how the primary sequence of a protein determines its tertiary structure.


title:
Design Principle of Gene Expression Used by Human Stem Cells;
  Implication for Pluripotency

abstract:
  Human embryonic stem cells (ESC) are undifferentiated and are endowed with
the capacities of self renewal and pluripotential differentiation. Adult stem
cells renew their own tissue, but whether they can trans-differentiate to other
tissues is still controversial. To understand the genetic program that
underlies the pluripotency of stem cells, we compared the transcription profile
of ESC with that of progenitor/stem cells of human hematopoietic and
keratinocytic origins, along with their mature cells to be viewed as snapshots
along tissue differentiation. ESC gene profile show higher complexity with
significantly more highly expressed genes than adult cells. We hypothesize that
ESC use a strategy of expressing genes that represent various differentiation
pathways and selection of only a few for continuous expression upon
differentiation to a particular target. Such a strategy may be necessary for
the pluripotency of ESC. The progenitors of either hematopoietic or
keratinocytic cells also follow the same design principle. Using advanced
clustering, we show that many of the ESC expressed genes are turned off in the
progenitors/stem cells followed by a further downregulation in adult tissues.
Concomitantly, genes specific to the target tissue are upregulated towards
matured cells of skin or blood.


title: Outcome signature genes in breast cancer: is there a unique set?

abstract:
  Motivation: Predicting the metastatic potential of primary malignant tissues
has direct bearing on choice of therapy. Several microarray studies yielded
gene sets whose expression profiles successfully predicted survival (Ramaswamy
et al 2003; Sorlie et al 2001; van't Veer et al 2003). Nevertheless, the
overlap between these gene sets is almost zero. Such small overlaps were
observed also in other complex diseases (Lossos et al 2003; Miklos and Maleszka
2004), and the variables that could account for the differences had evoked a
wide interest. One of the main open questions in this context is whether the
disparity can be attributed only to trivial reasons such as different
technologies, different patients and different types of analysis. Results: To
answer this question we concentrated on one single breast cancer dataset, and
analyzed it by one single method, the one which was used by van't Veer et al to
produce a set of outcome predictive genes. We showed that in fact the resulting
set of genes is not unique; it is strongly influenced by the subset of patients
used for gene selection. Many equally predictive lists could have been produced
from the same analysis. Three main properties of the data explain this
sensitivity: (a) many genes are correlated with survival; (b) the differences
between these correlations are small; (c) the correlations fluctuate strongly
when measured over different subsets of patients. A possible biological
explanation for these properties is discussed.


title: FSSP to SCOP and CATH (F2CS) Prediction Server

abstract:
  Summary: The F2CS server provides access to the software, F2CS2.00, that
implements an automated prediction method of SCOP and CATH classifications of
proteins, based on their FSSP Z-scores (Getz et al., 2002), Availability: Free,
at http://www.weizmann.ac.il/physics/complex/compphys/f2cs/. Contact:
eytan.domany@weizmann.ac.il Supplementary information: The site contains links
to additional figures and tables.


title:
Functional immunomics: Microarray analysis of IgG autoantibody
  repertoires predicts the future response of NOD mice to an inducer of
  accelerated diabetes

abstract:
  One's present repertoire of antibodies encodes the history of one's past
immunological experience. Can the present autoantibody repertoire be consulted
to predict resistance or susceptibility to the future development of an
autoimmune disease? Here we developed an antigen microarray chip and used
bioinformatic analysis to study a model of type 1 diabetes developing in
non-obese diabetic (NOD) male mice in which the disease was accelerated and
synchronized by exposing the mice to cyclophosphamide at 4 weeks of age. We
obtained sera from 19 individual mice, treated the mice to induce
cyclophosphamide-accelerated diabetes (CAD), and found, as expected, that 9
mice became severely diabetic while 10 mice permanently resisted diabetes. We
again obtained serum from each mouse afterCAD induction. We then analyzed the
patterns of antibodies in the individualmice to 266 different antigens spotted
on the antigen chip. We identified a select panel of 27 different antigens (10%
of the array) that revealed a pattern of IgG antibody reactivity in the pre-CAD
serathat discriminated between the mice resistant or susceptible to CAD with
100% sensitivity and 82% specificity (p=0.017). Surprisingly, the set of IgG
antibodies that was informative before CAD induction did not separate the
resistant and susceptible groups after the onset of CAD; new antigens became
criticalfor post-CAD repertoire discrimination. Thus, at least for a model
disease, present antibody repertoires can predict future disease; predictive
and diagnostic repertoires can differ; and decisive information about immune
system behavior can be mined by bioinformatic technology. Repertoires matter.


title: Breaking records in the evolutionary race

abstract:
  We explore some aspects of the relationship between biological evolution
processes and the mathematical theory of records. For Eigen's quasispecies
model with an uncorrelated fitness landscape, we show that the evolutionary
trajectories traced out by a population initially localized at a randomly
chosen point in sequence space can be described in close analogy to record
dynamics, with two complications. First, the increasing number of genotypes
that become available with increasing distance from the starting point implies
that fitness records are more frequent than for the standard case of
independent, identically distributed random variables. Second, fitness records
can be bypassed, which strongly reduces the number of genotypes that take part
in an evolutionary trajectory. For exponential and Gaussian fitness
distributions, this number scales with sequence length $N$ as $\sqrt{N}$, and
it is of order unity for distributions with a power law tail. This is in strong
contrast to the number of records, which is of order $N$ for any fitness
distribution.


title:
Quantifying the relevance of different mediators in the human immune
  cell network

abstract:
  Immune cells coordinate their efforts for the correct and efficient
functioning of the immune system (IS). Each cell type plays a distinct role and
communicates with other cell types through mediators such as cytokines,
chemokines and hormones, among others, that are crucial for the functioning of
the IS and its fine tuning. Nevertheless, a quantitative analysis of the
topological properties of an immunological network involving this complex
interchange of mediators among immune cells is still lacking. Here we present a
method for quantifying the relevance of different mediators in the immune
network, which exploits a definition of centrality based on the concept of
efficient communication. The analysis, applied to the human immune system,
indicates that its mediators significantly differ in their network relevance.
We found that cytokines involved in innate immunity and inflammation and some
hormones rank highest in the network, revealing that the most prominent
mediators of the IS are molecules involved in these ancestral types of defence
mechanisms highly integrated with the adaptive immune response, and at the
interplay among the nervous, the endocrine and the immune systems.


title:
Replica exchange molecular dynamics simulations of amyloid peptide
  aggregation

abstract:
  The replica exchange molecular dynamics (REMD) approach is applied to four
oligomeric peptide systems. At physiologically relevant temperature values REMD
samples conformation space and aggregation transitions more efficiently than
constant temperature molecular dynamics (CTMD). During the aggregation process
the energetic and structural properties are essentially the same in REMD and
CTMD. A condensation stage toward disordered aggregates precedes the
$\beta$-sheet formation. Two order parameters, borrowed from anisotropic fluid
analysis, are used to monitor the aggregation process. The order parameters do
not depend on the peptide sequence and length and therefore allow to compare
the amyloidogenic propensity of different peptides.


title:
Topology of biological networks and reliability of information
  processing

abstract:
  Biological systems rely on robust internal information processing: Survival
depends on highly reproducible dynamics of regulatory processes. Biological
information processing elements, however, are intrinsically noisy (genetic
switches, neurons, etc.). Such noise poses severe stability problems to system
behavior as it tends to desynchronize system dynamics (e.g. via fluctuating
response or transmission time of the elements). Synchronicity in parallel
information processing is not readily sustained in the absence of a central
clock. Here we analyze the influence of topology on synchronicity in networks
of autonomous noisy elements. In numerical and analytical studies we find a
clear distinction between non-reliable and reliable dynamical attractors,
depending on the topology of the circuit. In the reliable cases, synchronicity
is sustained, while in the unreliable scenario, fluctuating responses of single
elements can gradually desynchronize the system, leading to non-reproducible
behavior. We find that the fraction of reliable dynamical attractors strongly
correlates with the underlying circuitry. Our model suggests that the observed
motif structure of biological signaling networks is shaped by the biological
requirement for reproducibility of attractors.


title:
The Shift-Match Number and String Matching Probabilities for Binary
  Sequences

abstract:
  We define the ``shift-match number'' for a binary string and we compute the
probability of occurrence of a given string as a subsequence in longer strings
in terms of its shift-match number. We thus prove that the string matching
probabilities depend not only on the length of shorter strings, but also on the
equivalence class of the shorter string determined by its shift-match number.


title:
Stability of evolutionarily stable strategies in discrete replicator
  dynamics with time delay

abstract:
  We construct two models of discrete-time replicator dynamics with time delay.
In the social-type model, players imitate opponents taking into account average
payoffs of games played some units of time ago. In the biological-type model,
new players are born from parents who played in the past. We consider
two-player games with two strategies and a unique mixed evolutionarily stable
strategy. We show that in the first type of dynamics, it is asymptotically
stable for small time delays and becomes unstable for big ones when the
population oscillates around its stationary state. In the second type of
dynamics, however, evolutionarily stable strategy is asymptotically stable for
any size of a time delay.


title: A model for the accidental catalysis of protein unfolding in vivo

abstract:
  Activated processes such as protein unfolding are highly sensitive to
heterogeneity in the environment. We study a highly simplified model of a
protein in a random heterogeneous environment, a model of the in vivo
environment. It is found that if the heterogeneity is sufficiently large the
total rate of the process is essentially a random variable; this may be the
cause of the species-to-species variability in the rate of prion protein
conversion found by Deleault et al. [Nature, 425 (2003) 717].


title:
Equilibrium selection in evolutionary games with random matching of
  players

abstract:
  We discuss stochastic dynamics of populations of individuals playing games.
Our models possess two evolutionarily stable strategies: an efficient one,
where a population is in a state with the maximal payoff (fitness) and a
risk-dominant one, where players are averse to risks. We assume that
individuals play with randomly chosen opponents (they do not play against
average strategies as in the standard replicator dynamics). We show that the
long-run behavior of a population depends on its size and the mutation level.


title: Characterizing large scale base composition structures of genomes

abstract:
  Intermittent density fluctuations of nucleotide molecules (adenine, guanine,
cytosine and thymine) along DNA sequences are studied in the framework of a
hierarchical structure (HS) model originally proposed for the study of fully
developed turbulence [She and Leque, Phys. Rev. Lett. 72}, 336 (1994)]. Large
scale (10^3 < \ell < 10^5 bp) base density fluctuation is shown to satisfy the
HS similarity. The derived values of a HS parameter $\beta$ from a large number
of genome data (including Bacteria, Archaea, human chromosomes and viruses)
characterize different biological properties such as strand symmetry,
phylogenetic relations and horizontal gene transfer. It is suggested that the
HS analysis offers a useful quantitative description for heterogeneity,
sequence complexity and large scale structures of genomes.


title: Evolutionary and asymptotic stability in symmetric multi-player games

abstract:
  We provide a classification of symmetric three-player games with two
strategies and investigate evolutionary and asymptotic stability (in the
replicator dynamics) of their Nash equilibria. We discuss similarities and
differences between two-player and multi-player games. In particular, we
construct examples which exhibit a novel behavior not found in two-player
games.


title:
Representation of protein structure based on frequency distributions of
  oriented cycles in contact graphs

abstract:
  We present a statistical approach to protein structure by introducing a
representation of protein folds based on simple observables defined as
frequencies of oriented cycles in contact graphs. Motivated by the idea that
these cycles may form a code of the entire protein structure we investigate its
Shannon entropy. The latter shows a characteristic transitory behavior when
traced over different values of the geometric threshold $t$ which defines
protein residues in contact. To account for this observation, we propose a
non-linear mechanical model-- formulated as a Hamiltonian system in which $t$
is regarded as a continuous parameter-- that allows to identify the behavior of
the Shannon entropy as a first-order phase transition between a disordered and
an ordered phase of the proposed mechanical system. The transition itself
reflects the formation of protein structure when represented in terms of
contact graph cycles, and it is identified as an example of a fragmentation
transition known from several other statistical systems without a proper
thermodynamic limit. Some interesting implications follow from our model
including chirality, broken $t$-symmetry and one-dimensionality. Although
defined from purely structural considerations, we further show that for native
protein structures these observables follow some of the quantitative rules that
are typically valid for amino acid types in protein sequences. Moreover, this
relation between polypeptide structures and their amino acid sequences suggests
a specific protein design alphabet.


title:
Water and molecular chaperones act as weak links of protein folding
  networks: energy landscape and punctuated equilibrium changes point towards a
  game theory of proteins

abstract:
  Water molecules and molecular chaperones efficiently help the protein folding
process. Here we describe their action in the context of the energy and
topological networks of proteins. In energy terms water and chaperones were
suggested to decrease the activation energy between various local energy minima
smoothing the energy landscape, rescuing misfolded proteins from conformational
traps and stabilizing their native structure. In kinetic terms water and
chaperones may make the punctuated equilibrium of conformational changes less
punctuated and help protein relaxation. Finally, water and chaperones may help
the convergence of multiple energy landscapes during protein-macromolecule
interactions. We also discuss the possibility of the introduction of protein
games to narrow the multitude of the energy landscapes when a protein binds to
another macromolecule. Both water and chaperones provide a diffuse set of
rapidly fluctuating weak links (low affinity and low probability interactions),
which allow the generalization of all these statements to a multitude of
networks.


title:
Relevant distance between two different instances of the same potential
  energy in protein folding

abstract:
  In the context of complex systems and, particularly, of protein folding, a
physically meaningful distance is defined which allows to make useful
statistical statements about the way in which energy differences are modified
when two different instances of the same potential-energy function are used.
When the two instances arise from the fact that different algorithms or
different approximations are used, the distance herein defined may be used to
evaluate the relative accuracy of the two methods. When the difference is due
to a change in the free parameters of which the potential depends on, the
distance can be used to quantify, in each region of parameter space, the
robustness of the modeling to such a change and this, in turn, may be used to
assess the significance of a parameters' fit. Both cases are illustrated with a
practical example: the study of the Poisson-based solvation energy in the
Trp-Cage protein (PDB code 1L2Y).


title: Intensity Coding in Two-Dimensional Excitable Neural Networks

abstract:
  In the light of recent experimental findings that gap junctions are essential
for low level intensity detection in the sensory periphery, the
Greenberg-Hastings cellular automaton is employed to model the response of a
two-dimensional sensory network to external stimuli. We show that excitable
elements (sensory neurons) that have a small dynamical range are shown to give
rise to a collective large dynamical range. Therefore the network transfer
(gain) function (which is Hill or Stevens law-like) is an emergent property
generated from a pool of small dynamical range cells, providing a basis for a
"neural psychophysics". The growth of the dynamical range with the system size
is approximately logarithmic, suggesting a functional role for electrical
coupling. For a fixed number of neurons, the dynamical range displays a maximum
as a function of the refractory period, which suggests experimental tests for
the model. A biological application to ephaptic interactions in olfactory nerve
fascicles is proposed.

categories: q-bio.NC cond-mat.dis-nn cond-mat.stat-mech nlin.CG nlin.PS physics.bio-ph q-bio.TO


title: A more comprehensive formulation of evolutionary equations

abstract:
  As mathematical model for the evolutionary equations of species the
masterequation is choiced. Two formulations will be demonstrated to include the
changes of parameters into the masterequation - that is, on the one hand, the
formation of a second masterequation for the development of parameters, and, on
the other hand, the use of the Wigner-distribution to describe the development
of parameters. Moreover, the Wigner-distribution is used to describe morphic
fields and involved in the theorie of selforganization.


title: Exons, introns and DNA thermodynamics

abstract:
  The genes of eukaryotes are characterized by protein coding fragments, the
exons, interrupted by introns, i.e. stretches of DNA which do not carry any
useful information for the protein synthesis. We have analyzed the melting
behavior of randomly selected human cDNA sequences obtained from the genomic
DNA by removing all introns. A clear correspondence is observed between exons
and melting domains. This finding may provide new insights in the physical
mechanisms underlying the evolution of genes.


title: Probabilistic pairwise sequence alignment

abstract:
  We describe an new algorithm for visualizing an alignment of biological
sequences according to a probabilistic model of evolution. The resulting data
array is readily interpreted by the human eye and amenable to digital image
techniques. We present examples using mRNA sequences from mouse and rat: three
cytochromes, Rattus norvegicus Cyp2a1, Cyp2a2, (Medline: 90212624) and Mus
musculus Cyp2a12 (Medline: 93249380); and two zinc finger proteins, Mus
musculus zfp111 and zfp235 (Medline: 22683274). The underlying evolutionary
model is derived from one proposed by Thorne, Kishino, and Felsenstein and
improved by Hein and others. The demonstration implementation aligns two
sequences using time and memory quadratic in the mean sequence length. The
algorithm is extensible, after Hein, to multiple sequences. We mention a basic
method to reduce time and memory demands.


title: High-gain nonlinear observer for simple genetic regulation process

abstract:
  High-gain nonlinear observers occur in the nonlinear automatic control theory
and are in standard usage in chemical engineering processes. We apply such a
type of analysis in the context of a very simple one-gene regulation circuit.
In general, an observer combines an analytical differential-equation-based
model with partial measurement of the system in order to estimate the
non-measured state variables. We use one of the simplest observers, that of
Gauthier et al., which is a copy of the original system plus a correction term
which is easy to calculate. For the illustration of this procedure, we employ a
biological model, recently adapted from Goodwin's old book by De Jong, in which
one plays with the dynamics of the concentrations of the messenger RNA coding
for a given protein, the protein itself, and a single metabolite. Using the
observer instead of the metabolite, it is possible to rebuild the non-measured
concentrations of the mRNA and the protein


title: The dissipative brain

abstract:
  I review the dissipative quantum model of brain and discuss its recent
developments related with the role of entanglement, quantum noise and chaos.
Some comments on consciousness in the frame of the dissipative model are also
presented. Dissipation seems to account for the medial character of
consciousness, for its being in the present (the Now), its un-dividable unity,
its intrinsic subjectivity (autonomy). Finally, essential features of a
conscious artificial device, if ever one can construct it, are briefly
commented upon, also in relation to a device able to exhibit mistakes in its
behavior. The name I give to such a hypothetical device is Spartacus.


title: A modular Fibonacci sequence in proteins

abstract:
  Protein-fragment seqlets typically feature about 10 amino acid residue
positions that are fixed to within conservative substitutions but usually
separated by a number of prescribed gaps with arbitrary residue content. By
quantifying a general amino acid residue sequence in terms of the associated
codon number sequence, we have found a precise modular Fibonacci sequence in a
continuous gap-free 10-residue seqlet with either 3 or 4 conservative amino
acid substitutions. This modular Fibonacci sequence is genuinely biophysical,
for it occurs nine times in the SWISS-Prot/TrEMBL database of natural proteins.


title: Critical Scale-invariance in Healthy Human Heart Rate

abstract:
  We demonstrate the robust scale-invariance in the probability density
function (PDF) of detrended healthy human heart rate increments, which is
preserved not only in a quiescent condition, but also in a dynamic state where
the mean level of heart rate is dramatically changing. This scale-independent
and fractal structure is markedly different from the scale-dependent PDF
evolution observed in a turbulent-like, cascade heart rate model. These results
strongly support the view that healthy human heart rate is controlled to
converge continually to a critical state.


title: 1/f Scaling in Heart Rate Requires Antagonistic Autonomic Control

abstract:
  We present the first systematic evidence for the origins of 1/f-type temporal
scaling in human heart rate. The heart rate is regulated by the activity of two
branches of the autonomic nervous system: the parasympathetic (PNS) and the
sympathetic (SNS) nervous systems. We examine alterations in the scaling
property when the balance between PNS and SNS activity is modified, and find
that the relative PNS suppression by congestive heart failure results in a
substantial increase in the Hurst exponent H towards random walk scaling
$1/f^{2}$ and a similar breakdown is observed with relative SNS suppression by
primary autonomic failure. These results suggest that 1/f scaling in heart rate
requires the intricate balance between the antagonistic activity of PNS and
SNS.


title:
Model of the early development of thalamo-cortical connections and area
  patterning via signaling molecules

abstract:
  The mammalian cortex is divided into architectonic and functionally distinct
areas. There is growing experimental evidence that their emergence and
development is controlled by both epigenetic and genetic factors. The latter
were recently implicated as dominating the early cortical area specification.
In this paper, we present a theoretical model that explicitly considers the
genetic factors and that is able to explain several sets of experiments on
cortical area regulation involving transcription factors Emx2 and Pax6, and
fibroblast growth factor FGF8. The model consists of the dynamics of thalamo-
cortical connections modulated by signaling molecules that are regulated
genetically, and by axonal competition for neocortical space. The model can
make predictions and provides a basic mathematical framework for the early
development of the thalamo-cortical connections and area patterning that can be
further refined as more experimental facts become known.


title: Chemical models of genetic toggle switches

abstract:
  We study by mean-field analysis and stochastic simulations chemical models
for genetic toggle switches formed from pairs of genes that mutually repress
each other. In order to determine the stability of the genetic switches, we
make a connection with reactive flux theory and transition state theory. The
switch stability is characterised by a well defined lifetime $\tau$. We find
that $\tau$ grows exponentially with the mean number $\Nmean$ of transcription
factor molecules involved in the switching. In the regime accessible to direct
numerical simulations, the growth law is well characterised by
$\tau\sim\Nmean{}^{\alpha}\exp(b\Nmean)$, where $\alpha$ and $b$ are
parameters. The switch stability is decreased by phenomena that increase the
noise in gene expression, such as the production of multiple copies of a
protein from a single mRNA transcript (shot noise), and fluctuations in the
number of proteins produced per transcript. However, robustness against
biochemical noise can be drastically enhanced by arranging the transcription
factor binding domains on the DNA such that competing transcription factors
mutually exclude each other on the DNA. We also elucidate the origin of the
enhanced stability of the exclusive switch with respect to that of the general
switch: while the kinetic prefactor is roughly the same for both switches, the
`barrier' for flipping the switch is significantly higher for the exclusive
switch than for the general switch.


title: Can Neural Networks Recognize Parts?

abstract:
  We have demonstrated neural networks can recognize parts by visual images.
Input signals are gray scale photographs of objects consisting of some parts
and output signals are their shapes. By training neural networks by a few set
of images, without any supervision they become to be able to recognize the
boundary between parts.