title: Global Topological Study of the Protein-protein Interaction Networks

abstract:
  We employed the random graph theory approach to analyze the protein-protein
interaction database DIP (Feb. 2004), for seven species (S. cerevisiae, H.
pylori, E. coli, C. elegans, H. sapiens, M. musculus and D. melanogaster).
Several global topological parameters (such as node connectivity, average
diameter, node connectivity correlation) were used to characterize these
protein-protein interaction networks (PINs). The logarithm of the connectivity
distribution vs. the logarithm of connectivity study indicated that PINs follow
a power law (P(k) ~ k-\gamma) behavior. Using the regression analysis method we
determined that \gamma lies between 1.5 and 2.4, for the seven species.
Correlation analysis provides good evidence supporting the fact that the seven
PINs form a scale-free network. The average diameters of the networks and their
randomized version are found to have large difference. We also demonstrated
that the interaction networks are quite robust when subject to random
perturbation. Average node connectivity correlation study supports the earlier
results that nodes of low connectivity are correlated, whereas nodes of high
connectivity are not directly linked. These results provided some evidence
suggesting such correlation relations might be a general feature of the PINs
across different species.


title: The role of mutation rate in a simple colonization model

abstract:
  We study the effect of mutations in a simple model of colonization, based on
Montecarlo simulations. When the population colonizes the whole available
habitat, a maximum population density is reached, which depends on the mutation
rate. Depending on the values of other parameters, such as selection pressure,
fecundity and mobility, there is an optimal value for the mutation rate for
which the colonization reaches the highest density. We also investigate the
survival probabilities under different conditions and its relation to the
mutation rate.


title: Fluctuation-dissipation theorem and models of learning

abstract:
  Advances in statistical learning theory have resulted in a multitude of
different designs of learning machines. But which ones are implemented by
brains and other biological information processors? We analyze how various
abstract Bayesian learners perform on different data and argue that it is
difficult to determine which learning-theoretic computation is performed by a
particular organism using just its performance in learning a stationary target
(learning curve). Basing on the fluctuation-dissipation relation in statistical
physics, we then discuss a different experimental setup that might be able to
solve the problem.


title: A Barrier Penetration Model for DNA Double Strand Separation

abstract:
  A barrier penetration model has been proposed to explain the spontaneous
melting of the DNA oligomers into two separate single strands whereas the
partially melted intermediate states are shown to be the bound state solution
of the same effective potential that generates the barrier.


title: Stability diagrams for bursting neurons modeled by three-variable maps

abstract:
  We study a simple map as a minimal model of excitable cells. The map has two
fast variables which mimic the behavior of class I neurons, undergoing a
sub-critical Hopf bifurcation. Adding a third slow variable allows the system
to present bursts and other interesting biological behaviors. Bifurcation lines
which locate the excitability region are obtained for different planes in
parameter space.

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


title: Complex dynamics of the biological rhythms: gallbladder and heart cases

abstract:
  A theoretical analysis of the mechanisms underlying the dynamics of
gallbladder and heart pulsation could clarify the question regarding the
classification as chaotic of the associated behaviour, eventually related to a
normal and healthy beat; this analysis is particularly relevant in view of the
control of dynamics bifurcations arising in situations of disease. In this work
is presented a summary of the DFA method applied to gallbladder volume data for
a modest number of healthy and ill patients: the presence of signal correlation
is found in both cases, but the fit shapes differ from some critical values.


title: Inhibition of protein crystallization by evolutionary negative design

abstract:
  In this perspective we address the question: why are proteins seemingly so
hard to crystallize? We suggest that this is because of evolutionary negative
design, i.e. proteins have evolved not to crystallize, because crystallization,
as with any type of protein aggregation, compromises the viability of the cell.
There is much evidence in the literature that supports this hypothesis,
including the effect of mutations on the crystallizability of a protein, the
correlations found in the properties of crystal contacts in bioinformatics
databases, and the positive use of protein crystallization by bacteria and
viruses.


title: Mortality decrease and mathematical limit of longevity

abstract:
  We wish to verify that the mortality deceleration (or decrease) is a
consequence of the bending of the shape parameter at old ages. This
investigation is based upon the Weon model (the Weibull model with an
age-dependent shape parameter) for human survival and mortality curves.
According to the Weon model, we are well able to describe the mortality
decrease after the mortality plateau, including the mortality deceleration.
Furthermore, we are able to simply define the mathematical limit of longevity
by the mortality decrease. From the demographic analysis of the historical
trends in Switzerland (1876-2001) and Sweden (1861-2001), and the most recent
trends in the other eleven developed countries (1996-2001), we confirm that the
bending of the shape parameter after characteristic life is correlated with the
mortality deceleration (or decrease). As a consequence, this bending of the
shape parameters and the mortality deceleration is associated with the
mathematical limit on longevity. These results suggest that the mathematical
limit of longevity can be induced by the mortality deceleration (or decrease)
in nature. These findings will give us a breakthrough for studying the
mortality dynamics at the highest ages.


title: Fine Discrimination of Analog Patterns by Nonlinear Dendritic Inhibition

abstract:
  Recent experiments revealed that a certain class of inhibitory neurons in the
cerebral cortex make synapses not onto cell bodies but at distal parts of
dendrites of the target neurons, mediating highly nonlinear dendritic
inhibition. We propose a novel form of competitive neural network model that
realizes such dendritic inhibition. Contrary to the conventional lateral
inhibition in neural networks, our dendritic inhibition models don't always
show winner-take-all behaviors; instead, they converge to "I don't know" states
when unknown input patterns are presented. We derive reduced two-dimensional
dynamics for the network, showing that a drastic shift of the fixed point from
a winner-take-all state to an "I don't know" state occurs in accordance with
the increase in noise added to the stored patterns. By preventing
misrecognition in such a way, dendritic inhibition networks achieve fine
pattern discrimination, which could be one of the basic computations by
inhibitory connected recurrent neural networks in the brain.


title: Getting DNA twist rigidity from single molecule experiments

abstract:
  We use an elastic rod model with contact to study the extension versus
rotation diagrams of single supercoiled DNA molecules. We reproduce
quantitatively the supercoiling response of overtwisted DNA and, using
experimental data, we get an estimation of the effective supercoiling radius
and of the twist rigidity of B-DNA. We find that unlike the bending rigidity,
the twist rigidity of DNA seems to vary widely with the nature and
concentration of the salt buffer in which it is immerged.


title: Generalized Poland-Scheraga model for DNA hybridization

abstract:
  The Poland-Scheraga (PS) model for the helix-coil transition of DNA considers
the statistical mechanics of the binding (or hybridization) of two
complementary strands of DNA of equal length, with the restriction that only
bases with the same index along the strands are allowed to bind. In this paper,
we extend this model by relaxing these constraints: We propose a generalization
of the PS model which allows for the binding of two strands of unequal lengths
$N_{1}$ and $N_{2}$ with unrelated sequences. We study in particular (i) the
effect of mismatches on the hybridization of complementary strands (ii) the
hybridization of non complementary strands (as resulting from point mutations)
of unequal lengths $N_{1}$ and $N_{2}$. The use of a Fixman-Freire scheme
scales down the computational complexity of our algorithm from
$O(N_{1}^{2}N_{2}^{2})$ to $O(N_{1}N_{2})$.The simulation of complementary
strands of a few kbps yields results almost identical to the PS model. For
short strands of equal or unequal lengths, the binding displays a strong
sensitivity to mutations. This model may be relevant to the experimental
protocol in DNA microarrays, and more generally to the molecular recognition of
DNA fragments. It also provides a physical implementation of sequence
alignments.


title: A model of sympatric speciation through assortative mating

abstract:
  A microscopic model is developed, within the frame of the theory of
quantitative traits, to study both numerically and analytically the combined
effect of competition and assortativity on the sympatric speciation process,
i.e. speciation in the absence of geographical barriers. 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. The effects of finiteness
of population size on survival of coexisting species are also accounted for.
The simulations show that both in the case of flat and ripid static fitness
landscapes, competition and assortativity do exert a synergistic effect on
speciation. We also show that competition acts as a stabilizing force against
extinction due to random sampling in a finite population. Finally, evidence is
shown that speciation can be seen as a phase transition.


title: Can contact potentials reliably predict stability of proteins?

abstract:
  The simplest approximation of interaction potential between amino-acids in
proteins is the contact potential, which defines the effective free energy of a
protein conformation by a set of amino acid contacts formed in this
conformation. Finding a contact potential capable of predicting free energies
of protein states across a variety of protein families will aid protein folding
and engineering in silico on a computationally tractable time-scale. We test
the ability of contact potentials to accurately and transferably (across
various protein families) predict stability changes of proteins upon mutations.
We develop a new methodology to determine the contact potentials in proteins
from experimental measurements of changes in protein thermodynamic stabilities
(ddG) upon mutations. We apply our methodology to derive sets of contact
interaction parameters for a hierarchy of interaction models including
solvation and multi-body contact parameters. We test how well our models
reproduce experimental measurements by statistical tests. We evaluate the
maximum accuracy of predictions obtained by using contact potentials and the
correlation between parameters derived from different data-sets of experimental
ddG values. We argue that it is impossible to reach experimental accuracy and
derive fully transferable contact parameters using the contact models of
potentials. However, contact parameters can yield reliable predictions of ddG
for datasets of mutations confined to specific amino-acid positions in the
sequence of a single protein.


title: Turbulence near cyclic fold bifurcations in birhythmic media

abstract:
  We show that at the onset of a cyclic fold bifurcation, a birhythmic medium
composed of glycolytic oscillators displays turbulent dynamics. By computing
the largest Lyapunov exponent, the spatial correlation function, and the
average transient lifetime, we classify it as a weak turbulence with transient
nature. Virtual heterogeneities generating unstable fast oscillations are the
mechanism of the transient turbulence. In the presence of wavenumber
instability, unstable oscillations can be reinjected leading to stationary
turbulence. We also find similar turbulence in a cell cycle model. These
findings suggest that weak turbulence may be universal in biochemical
birhythmic media exhibiting cyclic fold bifurcations.


title:
The influence of geometry, surface character and flexibility on the
  permeation of ions and water through biological pores

abstract:
  A hydrophobic constriction site can act as an efficient barrier to ion and
water permeation if its diameter is less than the diameter of an ion's first
hydration shell. This hydrophobic gating mechanism is thought to operate in a
number of ion channels, e.g. the nicotinic receptor, bacterial mechanosensitive
channels (MscL and MscS) and perhaps in some potassium channels (e.g. KcsA,
MthK, and KvAP). Simplified pore models allow one to investigate the primary
characteristics of a conduction pathway, namely its geometry (shape, pore
length, and radius), the chemical character of the pore wall surface, and its
local flexibility and surface roughness. Our extended (ca. 0.1 \mu s) molecular
dynamic simulations show that a short hydrophobic pore is closed to water for
radii smaller than 0.45 nm. By increasing the polarity of the pore wall (and
thus reducing its hydrophobicity) the transition radius can be decreased until
for hydrophilic pores liquid water is stable down to a radius comparable to a
water molecule's radius. Ions behave similarly but the transition from
conducting to non-conducting pores is even steeper and occurs at a radius of
0.65 nm for hydrophobic pores. The presence of water vapour in a constriction
zone indicates a barrier for ion permeation. A thermodynamic model can explain
the behaviour of water in nanopores in terms of the surface tensions, which
leads to a simple measure of "hydrophobicity" in this context. Furthermore,
increased local flexibility decreases the permeability of polar species. An
increase in temperature has the same effect, and we hypothesise that both
effects can be explained by a decrease in the effective solvent-surface
attraction which in turn leads to an increase in the solvent-wall surface free
energy.


title: The spread of disease with birth and death on networks

abstract:
  In this paper, we introduce a modified epidemic model on regular and
scale-free networks respectively. We consider the birth rate $\delta$, cure
rate $\gamma$, infection rate $\lambda$, $\alpha$ from the infectious disease,
and death rate $\beta$ from other factors. Through mean-field analysis, we find
that on regular network there is an epidemic threshold $\lambda_{c}$ dependent
on the parameters $\delta$, $\gamma$, $\alpha$, and $\beta$; while for power
law degree distribution network epidemic threshold is absent in the
thermodynamic limit. The result is the same as that of the standard SIS model.
This reminds us the structure of the networks plays a very important role in
the spreading property of the infectious disease.


title: Long-range correlation in the whole human genome

abstract:
  We calculate the mutual information function for each of the 24 chromosomes
in the human genome. The same correlation pattern is observed regardless the
individual functional features of each chromosome. Moreover, correlations of
different scale length are detected depicting a multifractal scenario. This
fact suggest a unique mechanism of structural evolution. We propose that such a
mechanism could be an expansion-modification dynamical system.


title: Solution of the Quasispecies Model for an Arbitrary Gene Network

abstract:
  In this paper, we study the equilibrium behavior of Eigen's quasispecies
equations for an arbitrary gene network. We consider a genome consisting of $ N
$ genes, so that each gene sequence $ \sigma $ may be written as $ \sigma =
\sigma_1 \sigma_2 ... \sigma_N $. We assume a single fitness peak (SFP) model
for each gene, so that gene $ i $ has some ``master'' sequence $ \sigma_{i, 0}
$ for which it is functioning. The fitness landscape is then determined by
which genes in the genome are functioning, and which are not. The equilibrium
behavior of this model may be solved in the limit of infinite sequence length.
The central result is that, instead of a single error catastrophe, the model
exhibits a series of localization to delocalization transitions, which we term
an ``error cascade.'' As the mutation rate is increased, the selective
advantage for maintaining functional copies of certain genes in the network
disappears, and the population distribution delocalizes over the corresponding
sequence spaces. The network goes through a series of such transitions, as more
and more genes become inactivated, until eventually delocalization occurs over
the entire genome space, resulting in a final error catastrophe. This model
provides a criterion for determining the conditions under which certain genes
in a genome will lose functionality due to genetic drift. It also provides
insight into the response of gene networks to mutagens. In particular, it
suggests an approach for determining the relative importance of various genes
to the fitness of an organism, in a more accurate manner than the standard
``deletion set'' method. The results in this paper also have implications for
mutational robustness and what C.O. Wilke termed ``survival of the flattest.''


title: Performance of networks of artificial neurons: The role of clustering

abstract:
  The performance of the Hopfield neural network model is numerically studied
on various complex networks, such as the Watts-Strogatz network, the
Barab{\'a}si-Albert network, and the neuronal network of the C. elegans.
Through the use of a systematic way of controlling the clustering coefficient,
with the degree of each neuron kept unchanged, we find that the networks with
the lower clustering exhibit much better performance. The results are discussed
in the practical viewpoint of application, and the biological implications are
also suggested.


title: Sublinear Growth of Information in DNA Sequences

abstract:
  We introduce a novel method to analyse complete genomes and recognise some
distinctive features by means of an adaptive compression algorithm, which is
not DNA-oriented. We study the Information Content as a function of the number
of symbols encoded by the algorithm. Preliminar results are shown concerning
regions having a sublinear type of information growth, which is strictly
connected to the presence of highly repetitive subregions that might be
supposed to have a regulatory function within the genome.


title: Gene-history correlation and population structure

abstract:
  Correlation of gene histories in the human genome determines the patterns of
genetic variation (haplotype structure) and is crucial to understanding genetic
factors in common diseases. We derive closed analytical expressions for the
correlation of gene histories in established demographic models for genetic
evolution and show how to extend the analysis to more realistic (but more
complicated) models of demographic structure. We identify two contributions to
the correlation of gene histories in divergent populations: linkage
disequilibrium, and differences in the demographic history of individuals in
the sample. These two factors contribute to correlations at different length
scales: the former at small, and the latter at large scales. We show that
recent mixing events in divergent populations limit the range of correlations
and compare our findings to empirical results on the correlation of gene
histories in the human genome.


title:
Reliably determining which genes have a high posterior probability of
  differential expression: A microarray application of decision-theoretic
  multiple testing

abstract:
  Microarray data are often used to determine which genes are differentially
expressed between groups, for example, between treatment and control groups.
There are methods of determining which genes have a high probability of
differential expression, but those methods depend on the estimation of
probability densities. Theoretical results have shown such estimation to be
unreliable when high-probability genes are identified.
  The genes that are probably differentially expressed can be found using
decision theory instead of density estimation. Simulations show that the
proposed decision-theoretic method is much more reliable than a
density-estimation method. The proposed method is used to determine which genes
to consider differentially expressed between patients with different types of
cancer.
  The proposed method determines which genes have a high probability of
differential expression. It can be applied to data sets that have replicate
microarrays in each of two or more groups of patients or experiments.


title:
HighProbability determines which alternative hypotheses are sufficiently
  probable: Genomic applications include detection of differential gene
  expression

abstract:
  Many genomic experiments, notably microarray experiments seeking to detect
differential gene expression, involve calculating a large number of p-values.
This leads to the multiple testing problem: when the number of null hypotheses
is large, the probability of accepting at least one false alternative
hypothesis is often much greater than the significance level of the tests,
which tends to mislead investigators. Software called HighProbability provides
a simple, fast, reliable solution to the multiple testing problem, with
applications to many areas of bioinformatics. For example, in a microarray
study, HighProbability can determine which genes are probably differentially
expressed. Given a set of p-values not adjusted for multiple testing,
HighProbability determines which ones are low enough to imply a high
probability of the truth of their alternative hypotheses. The set of p-values
may be determined by conventional hypothesis testing or by random permutations
using existing R or S-PLUS software. HighProbability is freely available under
license through http://www.davidbickel.com . Coded in S, HighProbability
currently requires an installation of R or S-PLUS, but the algorithm is short
enough for fast implementation in non-S languages as well.


title:
Global organization of metabolic fluxes in the bacterium, Escherichia
  coli

abstract:
  Cellular metabolism, the integrated interconversion of thousands of metabolic
substrates through enzyme-catalyzed biochemical reactions, is the most
investigated complex intercellular web of molecular interactions. While the
topological organization of individual reactions into metabolic networks is
increasingly well understood, the principles governing their global functional
utilization under different growth conditions pose many open questions. We
implement a flux balance analysis of the E. coli MG1655 metabolism, finding
that the network utilization is highly uneven: while most metabolic reactions
have small fluxes, the metabolism's activity is dominated by several reactions
with very high fluxes. E. coli responds to changes in growth conditions by
reorganizing the rates of selected fluxes predominantly within this high flux
backbone. The identified behavior likely represents a universal feature of
metabolic activity in all cells, with potential implications to metabolic
engineering.


title:
A generalized model of mutation-selection balance with applications to
  aging

abstract:
  A probability model is presented for the dynamics of mutation-selection
balance in a haploid infinite-population infinite-sites setting sufficiently
general to cover mutation-driven changes in full age-specific demographic
schedules. The model accommodates epistatic as well as additive selective
costs. Closed form characterizations are obtained for solutions in finite time,
along with proofs of convergence to stationary distributions and a proof of the
uniqueness of solutions in a restricted case. Examples are given of
applications to the biodemography of aging, including instabilities in current
formulations of mutation accumulation.


title: Disorder and fluctuations in nonlinear excitations in DNA

abstract:
  We study the effects of the sequence on the propagation of nonlinear
excitations in simple models of DNA, and how those effects are modified by
noise. Starting from previous results on soliton dynamics on lattices defined
by aperiodic potentials, [F. Dom\'\i nguez-Adame {\em et al.}, Phys. Rev. E
{\bf 52}, 2183 (1995)], we analyze the behavior of lattices built from real DNA
sequences obtained from human genome data. We confirm the existence of
threshold forces, already found in Fibonacci sequences, and of stop positions
highly dependent on the specific sequence. Another relevant conclusion is that
the effective potential, a collective coordinate formalism introduced by
Salerno and Kivshar [Phys. Lett. A {\bf 193}, 263 (1994)] is a useful tool to
identify key regions that control the behaviour of a larger sequence. We then
study how the fluctuations can assist the propagation process by helping the
excitations to escape the stop positions. Our conclusions point out to
improvements of the model which look promising to describe mechanical
denaturation of DNA. Finally, we also consider how randomly distributed energy
focus on the chain as a function of the sequence.

categories: q-bio.BM cond-mat.dis-nn math-ph math.MP nlin.PS q-bio.GN


title: Noise in ecosystems: a short review

abstract:
  Noise, through its interaction with the nonlinearity of the living systems,
can give rise to counter-intuitive phenomena such as stochastic resonance,
noise-delayed extinction, temporal oscillations, and spatial patterns. In this
paper we briefly review the noise-induced effects in three different
ecosystems: (i) two competing species; (ii) three interacting species, one
predator and two preys, and (iii) N-interacting species. The transient dynamics
of these ecosystems are analyzed through generalized Lotka-Volterra equations
in the presence of multiplicative noise, which models the interaction between
the species and the environment. The interaction parameter between the species
is random in cases (i) and (iii), and a periodical function, which accounts for
the environmental temperature, in case (ii). We find noise-induced phenomena
such as quasi-deterministic oscillations, stochastic resonance, noise-delayed
extinction, and noise-induced pattern formation with nonmonotonic behaviors of
patterns areas and of the density correlation as a function of the
multiplicative noise intensity. The asymptotic behavior of the time average of
the \emph{$i^{th}$} population when the ecosystem is composed of a great number
of interacting species is obtained and the effect of the noise on the
asymptotic probability distributions of the populations is discussed.


title:
Calculating Biological Behaviors of Epigenetic States in Phage lambda
  Life Cycle

abstract:
  Gene regulatory network of lambda phage is one the best studied model systems
in molecular biology. More 50 years of experimental study has provided a
tremendous amount of data at all levels: physics, chemistry, DNA, protein, and
function. However, its stability and robustness for both wild type and mutants
has been a notorious theoretical/mathematical problem. In this paper we report
our successful calculation on the properties of this gene regulatory network.
We believe it is of its first kind. Our success is of course built upon
numerous previous theoretical attempts, but following 3 features make our
modeling uniqu:
  1) A new modeling method particular suitable for stability and robustness
study;
  2) Paying a close attention to the well-known difference of in vivo and in
vitro;
  3) Allowing more important role for noise and stochastic effect to play.
  The last two points have been discussed by two of us (Ao and Yin,
cond-mat/0307747), which we believe would be enough to make some of previous
theoretical attempts successful, too. We hope the present work would stimulate
a further interest in the emerging field of gene regulatory network.


title:
An ordinary differential equation model for the multistep transformation
  to cancer

abstract:
  Cancer is viewed as a multistep process whereby a normal cell is transformed
into a cancer cell through the acquisition of mutations. We reduce the
complexities of cancer progression to a simple set of underlying rules that
govern the transformation of normal cells to malignant cells. In doing so, we
derive an ordinary differential equation model that explores how the balance of
angiogenesis, cell death rates, genetic instability, and replication rates give
rise to different kinetics in the development of cancer. The key predictions of
the model are that cancer develops fastest through a particular ordering of
mutations and that mutations in genes that maintain genomic integrity would be
the most deleterious type of mutations to inherit. In addition, we perform a
sensitivity analysis on the parameters included in the model to determine the
probable contribution of each. This paper presents a novel approach to viewing
the genetic basis of cancer from a systems biology perspective and provides the
groundwork for other models that can be directly tied to clinical and molecular
data.


title: Dynamics of mortality in protected populations

abstract:
  Demographic data and recent experiments verify earlier predictions that
mortality has short (few percent of the life span) memory of the previous life
history, may be significantly decreased, reset to its value at a much younger
age, and (until certain age) eliminated. Such mortality dynamics is
demonstrated to be characteristic only of evolutionary unprecedented protected
populations. When conditions improve, their mortality decreases stepwise. At
crossovers the rate of decrease rapidly changes. The crossovers manifest the
edges of the stairs in the universal ladder of rapid mortality adjustment to
changing conditions. Mortality is dominated by the established universal law
which reduces it to few biologically explicit parameters and which is verified
with human and fly mortality data. Specific experiments to test universality of
the law for other animals, and to unravel the mechanism of stepwise life
extension, are suggested.


title: Immortality as a physical problem

abstract:
  Well protected human and laboratory animal populations with abundant
resources are evolutionary unprecedented. Physical approach, which takes
advantage of their extensively quantified mortality, establishes that its
dominant fraction yields the exact law, whose universality from yeast to humans
is unprecedented, and suggests its unusual mechanism. Singularities of the law
demonstrate new kind of stepwise adaptation. The law proves that universal
mortality is an evolutionary byproduct, which at any age is reversible,
independent of previous life history, and may be disposable. Recent experiments
verify these predictions. Life expectancy may be extended, arguably to
immortality, by relatively small and universal biological amendments in the
animals. Indeed, it doubled with improving conditions in humans; increased
2.4-fold with genotype change in Drosophila, and 6-fold (to 430 years in human
terms), with no apparent loss in health and vitality, in nematodes with a small
number of perturbed genes and tissues. The law suggests a physical mechanism of
the universal mortality and its regulation.


title:
A Stochastic Model for the Species Abundance Problem in an Ecological
  Community

abstract:
  We propose a model based on coupled multiplicative stochastic processes to
understand the dynamics of competing species in an ecosystem. This process can
be conveniently described by a Fokker-Planck equation. We provide an analytical
expression for the marginalized stationary distribution. Our solution is found
in excellent agreement with numerical simulations and compares rather well with
observational data from tropical forests.


title: Complementarity principle on human longevity

abstract:
  In recent we introduced, developed and established a new concept, model,
methodology and principle for studying human longevity in terms of demographic
basis. We call the new model the "Weon model", which is a general model
modified from the Weibull model with an age-dependent shape parameter to
describe human survival and mortality curves. We demonstrate the application of
the Weon model to the mortality dynamics and the mathematical limit of
longevity (the mortality rate to be mathematically zero, implying a maximum
longevity) in the Section I. The mathematical limit of longevity can be induced
by the mortality dynamics in nature. As a result, we put forward the
complementarity principle, which explains the recent paradoxical trends that
the mathematical limit decreases as the longevity increases, in the Section II.
Our findings suggest that the human longevity can be limited by the
complementarity principle.


title:
Memorization in a neural network with adjustable transfer function and
  conditional gating

abstract:
  The main problem about replacing LTP as a memory mechanism has been to find
other highly abstract, easily understandable principles for induced plasticity.
In this paper we attempt to lay out such a basic mechanism, namely intrinsic
plasticity. Important empirical observations with theoretical significance are
time-layering of neural plasticity mediated by additional constraints to enter
into later stages, various manifestations of intrinsic neural properties, and
conditional gating of synaptic connections. An important consequence of the
proposed mechanism is that it can explain the usually latent nature of
memories.


title: Large-scale reverse engineering by the Lasso

abstract:
  We perform a reverse engineering from the ``extended Spellman data'',
consisting of 6178 mRNA levels measured by microarrays at 73 instances in four
time series during the cell cycle of the yeast Saccharomyces cerevisae. By
assuming a linear model of the genetic regulatory network, and imposing an
extra constraint (the Lasso), we obtain a unique inference of coupling
parameters. These parameters are transfered into an adjacent matrix, which is
analyzed with respect to topological properties and biological relevance. We
find a very broad distribution of outdegrees in the network, compatible with
earlier findings for biological systems and totally incompatible with a random
graph, and also indications of modules in the network. Finally, we show there
is an excess of genes coding for transcription factors among the genes of
highest outdegrees, a fact which indicates that our approach has biological
relevance.


title:
Can repulsion be induced by attraction: a role of ephrin-B1 in
  retinotectal mapping?

abstract:
  We study a role of EphB receptors and their ligand ephrin-B1 in
dorsal-ventral retinotopic mapping. Earlier studies suggested that ephrin-B1
acts as an attractant for EphB expressing axons. We address the results of the
recent experiment in chick tectum (McLaughlin et al., 2003b) in which axons of
retinal ganglion cells were shown to be repelled by high ephrin-B1 density.
Thus it was proposed that ephrin-B1 might act as both attractant and repellent.
We show that the same axonal behavior may follow from attraction to ephrin-B1
density and axonal competition for space. Therefore, we show how apparent
repulsive interaction can be induced by a combination of attraction to the
target and competitive interactions between axons. We suggest an experimental
test that may distinguish repulsive interaction with the target from repulsion
induced by attraction and competition.


title: A Theoretical Framework for the Analysis of the West Nile Virus Epidemic

abstract:
  We present a model for the growth of West Nile virus in mosquito and bird
populations based on observations of the initial epidemic in the U.S. Increase
of bird mortality as a result of infection, which is a feature of the epidemic,
is found to yield an effect which is observable in principle, viz., periodic
variations in the extent of infection. The vast difference between mosquito and
bird lifespans, another peculiarity of the system, is shown to lead to
interesting consequences regarding delay in the onset of the steady-state
infection. An outline of a framework is provided to treat mosquito diffusion
and bird migration.


title: Edge vulnerability in neural and metabolic networks

abstract:
  Biological networks, such as cellular metabolic pathways or networks of
corticocortical connections in the brain, are intricately organized, yet
remarkably robust toward structural damage. Whereas many studies have
investigated specific aspects of robustness, such as molecular mechanisms of
repair, this article focuses more generally on how local structural features in
networks may give rise to their global stability. In many networks the failure
of single connections may be more likely than the extinction of entire nodes,
yet no analysis of edge importance (edge vulnerability) has been provided so
far for biological networks. We tested several measures for identifying
vulnerable edges and compared their prediction performance in biological and
artificial networks. Among the tested measures, edge frequency in all shortest
paths of a network yielded a particularly high correlation with vulnerability,
and identified inter-cluster connections in biological but not in random and
scale-free benchmark networks. We discuss different local and global network
patterns and the edge vulnerability resulting from them.


title:
Robustness, Stability and Efficiency of Phage lambda Gene Regulatory
  Network: Dynamical Structure Analysis

abstract:
  Based on our physical and biological studies we have recently developed a
mathematical framework for the analysis of nonlnear dynamics. We call this
framework the dynamical structure analysis. It has four dynamical elements:
potential landscape, transverse matrix, descendant matrix, and stochastic
drive. In particular, the importance and the existence of the potential
landscape is emphasized.
  The dynamical structure analysis is illustrated in detail by the study of
stability, robustness, and efficiency of the simplest gene regulatory network
of phage lambda.


title: Complementarity between survival and mortality

abstract:
  Accurate demographic functions help scientists define and understand
longevity. We summarize a new demographic model, the Weon model, and show the
application to the demographic data for Switzerland (1876-2002). Particularly,
the Weon model simply defines the maximum longevity, which is induced in nature
by the mortality dynamics. In this study, we reconsider the definition of the
maximum longevity and the effectiveness for longevity by the combined effect of
the survival and mortality functions. The results suggest that the mortality
function should be zero at the maximum longevity, since the density function is
zero but the survival function is not zero. Furthermore, the effectiveness for
longevity can be maximized at the characteristic life by the complementarity
between the survival and mortality functions, which suggests that there may be
two parts of rectangularization for longevity. The historical trends for
Switzerland (1876-2002) implies that there may be a fundamental limiting force
to restrict the increase of the effectiveness. As a result, it seems that the
density function is essential to define and understand the mortality dynamics,
the maximum longevity, the effectiveness for longevity, the paradigm of
rectangularization and the historical trends of the effectiveness by the
complementarity between the survival and mortality functions.


title: The Importance of DNA Repair in Tumor Suppression

abstract:
  The transition from a normal to cancerous cell requires a number of highly
specific mutations that affect cell cycle regulation, apoptosis,
differentiation, and many other cell functions. One hallmark of cancerous
genomes is genomic instability, with mutation rates far greater than those of
normal cells. In microsatellite instability (MIN tumors), these are often
caused by damage to mismatch repair genes, allowing further mutation of the
genome and tumor progression. These mutation rates may lie near the error
catastrophe found in the quasispecies model of adaptive RNA genomes, suggesting
that further increasing mutation rates will destroy cancerous genomes. However,
recent results have demonstrated that DNA genomes exhibit an error threshold at
mutation rates far lower than their conservative counterparts. Furthermore,
while the maximum viable mutation rate in conservative systems increases
indefinitely with increasing master sequence fitness, the semiconservative
threshold plateaus at a relatively low value. This implies a paradox, wherein
inaccessible mutation rates are found in viable tumor cells. In this paper, we
address this paradox, demonstrating an isomorphism between the conservatively
replicating (RNA) quasispecies model and the semiconservative (DNA) model with
post-methylation DNA repair mechanisms impaired. Thus, as DNA repair becomes
inactivated, the maximum viable mutation rate increases smoothly to that of a
conservatively replicating system on a transformed landscape, with an upper
bound that is dependent on replication rates. We postulate that inactivation of
post-methylation repair mechanisms are fundamental to the progression of a
tumor cell and hence these mechanisms act as a method for prevention and
destruction of cancerous genomes.


title:
Vibrational energy relaxation (VER) of a CD stretching mode in
  cytochrome c

abstract:
  We first review how to determine the rate of vibrational energy relaxation
(VER) using perturbation theory. We then apply those theoretical results to the
problem of VER of a CD stretching mode in the protein cytochrome c. We model
cytochrome c in vacuum as a normal mode system with the lowest-order anharmonic
coupling elements. We find that, for the ``lifetime'' width parameter $\gamma=3
\sim 30$ cm$^{-1}$, the VER time is $0.2 \sim 0.3$ ps, which agrees rather well
with the previous classical calculation using the quantum correction factor
method, and is consistent with spectroscopic experiments by Romesberg's group.
We decompose the VER rate into separate contributions from two modes, and find
that the most significant contribution, which depends on the ``lifetime'' width
parameter, comes from those modes most resonant with the CD vibrational mode.


title: Mathematical Structure of Evolutionary Theory

abstract:
  Here we postulate three laws which form a mathematical framework to capture
the essence of Darwinian evolutionary dynamics. The second law is most
quantitative and is explicitly expressed by a unique form of stochastic
differential equation. A precise definition of Wright's adaptive landscape is
given and a new and consistent interpretation of Fisher's fundamental theorem
of natural selection is provided. Based on a recently discovered theorem the
generality of the proposed laws is illustrated by an explicit demonstration of
their equivalence to a general conventional non-equilibrium dynamics
formulation. The proposed laws provide a coherence framework to discuss several
current evolutionary problems, such as speciation and stability, and gives a
firm base for the application of statistical physics tools in Darwinian
dynamics.

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


title: Efficient local strategies for vaccination and network attack

abstract:
  We study how a fraction of a population should be vaccinated to most
efficiently top epidemics. We argue that only local information (about the
neighborhood of specific vertices) is usable in practice, and hence we consider
only local vaccination strategies. The efficiency of the vaccination strategies
is investigated with both static and dynamical measures. Among other things we
find that the most efficient strategy for many real-world situations is to
iteratively vaccinate the neighbor of the previous vaccinee that has most links
out of the neighborhood.


title: Intelligent encoding and economical communication in the visual stream

abstract:
  The theory of computational complexity is used to underpin a recent model of
neocortical sensory processing. We argue that encoding into reconstruction
networks is appealing for communicating agents using Hebbian learning and
working on hard combinatorial problems, which are easy to verify. Computational
definition of the concept of intelligence is provided. Simulations illustrate
the idea.


title: Altruism may arise from individual selection

abstract:
  The fact that humans cooperate with non-kin in large groups, or with people
they will never meet again, is a long-standing evolutionary puzzle with
profound implications. Cooperation is linked to altruism, the capacity to
perform costly acts that confer benefits on others. Theoretical approaches had
so far disregarded costly acts that do not yield future benefits for the
altruist, either directly or indirectly. Recently, strong reciprocity, i.e.,
the predisposition to cooperate with others and to punish non-cooperators at
personal cost, has been proposed as a schema for understanding altruism in
humans. While behavioral experiments support the existence of strong
reciprocity, its evolutionary origins remain unclear: group and cultural
selection are generally invoked to compensate for the negative effects that
reciprocity is assumed to have on individuals. Here we show, by means of an
agent-based model inspired on the Ultimatum Game, that selection acting on
individuals capable of other-regarding behavior can give rise to strong
reciprocity. The results, consistent with the existence of neural correlates of
fairness, are in good agreement with observations on humans and monkeys.

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


title:
A Machine Learning Strategy to Identity Exonic Splice Enhancers in Human
  Protein-coding Sequence

abstract:
  Background: Exonic splice enhancers are sequences embedded within exons which
promote and regulate the splicing of the transcript in which they are located.
A class of exonic splice enhancers are the SR proteins, which are thought to
mediate interactions between splicing factors bound to the 5' and 3' splice
sites. Method and results: We present a novel strategy for analysing
protein-coding sequence by first randomizing the codons used at each position
within the coding sequence, then applying a motif-based machine learning
algorithm to compare the true and randomized sequences. This strategy
identified a collection of motifs which can successfully discriminate between
real and randomized coding sequence, including -- but not restricted to --
several previously reported splice enhancer elements. As well as successfully
distinguishing coding exons from randomized sequences, we show that our model
is able to recognize non-coding exons. Conclusions: Our strategy succeeded in
detecting signals in coding exons which seem to be orthogonal to the sequences'
primary function of coding for proteins. We believe that many of the motifs
detected here may represent binding sites for previously unrecognized proteins
which influence RNA splicing. We hope that this development will lead to
improved knowledge of exonic splice enhancers, and new developments in the
field of computational gene prediction.


title: Adaptivity and `Per learning'

abstract:
  One of the key points addressed by Per Bak in his models of brain function
was that biological neural systems must be able not just to learn, but also to
adapt--to quickly change their behaviour in response to a changing environment.
I discuss this in the context of various simple learning rules and adaptive
problems, centred around the Chialvo-Bak `minibrain' model [Neurosci. 90 (1999)
1137--1148].

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


title:
A Dynamical Similarity Approach to the Foundations of Complexity and
  Coordination in Multiscale Systems

abstract:
  I review a number of cognate issues that, taken together, pertain to the
creation of a non-reductionistic theory of multiscale coordination and present
one candidate theory based on the principle of dynamical similarity.


title: On the stability of Murray's testosterone model

abstract:
  We prove the global asymptotic stability of a well-known delayed
negative-feedback model of testosterone dynamics, which has been proposed as a
model of oscillatory behavior. We establish stability (and hence the
impossibility of oscillations) even in the presence of delays of arbitrary
length.


title: Base sequence dependent sliding of proteins on DNA

abstract:
  The possibility that the sliding motion of proteins on DNA is influenced by
the base sequence through a base pair reading interaction, is considered.
Referring to the case of the T7 RNA-polymerase, we show that the protein should
follow a noise-influenced sequence-dependent motion which deviate from the
standard random walk usually assumed. The general validity and the implications
of the results are discussed.


title:
Identifying the role that individual animals play in their social
  network

abstract:
  Techniques recently developed for the analysis of human social networks are
applied to the social network of bottlenose dolphins living in Doubtful Sound,
New Zealand. We identify communities and subcommunities within the dolphin
population and present evidence that sex- and age-related homophily play a role
in the formation of clusters of preferred companionship. We also identify
brokers who act as links between subcommunities and who appear to be crucial to
the social cohesion of the population as a whole. The network is found to be
similar to human social networks in some respects but different in some others
such as the level of assortative mixing by degree within the population. This
difference elucidates some of the means by which the network formed and
evolves.

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


title: Simon-Ando Decomposability and Fitness Landscapes

abstract:
  In this paper, we investigate fitness landscapes (under point mutation and
recombination) from the standpoint of whether the induced evolutionary dynamics
have a "fast-slow" time scale associated with the differences in relaxation
time between local quasi-equilibria and the global equilibrium. This dynamical
behavior has been formally described in the econometrics literature in terms of
the spectral properties of the appropriate operator matrices by Simon and Ando
(1961), and we use the relations they derive to ask which fitness functions and
mutation/recombination operators satisfy these properties. It turns out that
quite a wide range of landscapes satisfy the condition (at least trivially)
under point mutation given a sufficiently low mutation rate, while the property
appears to be difficult to satisfy under genetic recombination. In spite of the
fact that Simon-Ando decomposability can be realized over fairly wide range of
parameters, it imposes a number of restrictions on which landscape
partitionings are possible. For these reasons, the Simon-Ando formalism doesn't
appear to be applicable to other forms of decomposition and aggregation of
variables that are important in evolutionary systems.


title:
The perception of melodic consonance: an acoustical and
  neurophysiological explanation based on the overtone series

abstract:
  The melodic consonance of a sequence of tones is explained using the overtone
series: the overtones form "flow lines" that link the tones melodically; the
strength of these flow lines determines the melodic consonance. This hypothesis
admits of psychoacoustical and neurophysiological interpretations that fit well
with the place theory of pitch perception. The hypothesis is used to create a
model for how the auditory system judges melodic consonance, which is used to
algorithmically construct melodic sequences of tones.


title:
Statistical analysis of the distribution of amino acids in Borrelia
  burgdorferi genome under different genetic codes

abstract:
  The genetic code is considered to be universal. In order to test if some
statistical properties of the coding bacterial genome were due to inherent
properties of the genetic code, we compared the autocorrelation function, the
scaling properties and the maximum entropy of the distribution of distances of
amino acids in sequences obtained by translating protein-coding regions from
the genome of Borrelia burgdorferi, under different genetic codes. Overall our
results indicate that these properties are very stable to perturbations made by
altering the genetic code. We also discuss the evolutionary likely implications
of the present results.


title: Graphic requirements for multistationarity

abstract:
  We discuss properties which must be satisfied by a genetic network in order
for it to allow differentiation.
  These conditions are expressed as follows in mathematical terms. Let $F$ be a
differentiable mapping from a finite dimensional real vector space to itself.
The signs of the entries of the Jacobian matrix of $F$ at a given point $a$
define an interaction graph, i.e. a finite oriented finite graph $G(a)$ where
each edge is equipped with a sign. Ren\'e Thomas conjectured twenty years ago
that, if $F$ has at least two non degenerate zeroes, there exists $a$ such that
$G(a)$ contains a positive circuit. Different authors proved this in special
cases, and we give here a general proof of the conjecture. In particular, we
get this way a necessary condition for genetic networks to lead to
multistationarity, and therefore to differentiation.
  We use for our proof the mathematical literature on global univalence, and we
show how to derive from it several variants of Thomas' rule, some of which had
been anticipated by Kaufman and Thomas.


title: The protein folding network

abstract:
  The conformation space of a 20-residue antiparallel $\beta$-sheet peptide,
sampled by molecular dynamics simulations, is mapped to a network.
Conformations are nodes of the network, and the transitions between them are
links. The conformation space network describes the significant free energy
minima and their dynamic connectivity without projections into arbitrarily
chosen reaction coordinates. As previously found for the Internet and the
World-Wide Web as well as for social and biological networks, the conformation
space network is scale-free and contains highly connected hubs like the native
state which is the most populated free energy basin. Furthermore, the native
basin exhibits a hierarchical organization which is not found for a random
heteropolymer lacking a predominant free-energy minimum. The network topology
is used to identify conformations in the folding transition state ensemble, and
provides a basis for understanding the heterogeneity of the transition state
and denaturated state ensemble as well as the existence of multiple pathway


title: Demographic trajectories for supercentenarians

abstract:
  A fundamental question in aging research concerns the demographic
trajectories at the highest ages, especially for supercentenarians (persons
aged 110 or more). We wish to demonstrate that the Weon model enables
scientists to describe the demographic trajectories for supercentenarians. We
evaluate the average survival data from the modern eight countries and the
valid and complete data for supercentenarians from the International Database
on Longevity (Robine and Vaupel, (2002) North American Actuarial Journal 6,
54-63). The results suggest that the Weon model predicts the maximum longevity
to exist around ages 120-130, which indicates that there is an intrinsic limit
to human longevity, and that the Weon model allows the best possible
description of the demographic trajectories for supercentenarians.


title: The Triplet Genetic Code had a Doublet Predecessor

abstract:
  Information theoretic analysis of genetic languages indicates that the
naturally occurring 20 amino acids and the triplet genetic code arose by
duplication of 10 amino acids of class-II and a doublet genetic code having
codons NNY and anticodons $\overleftarrow{\rm GNN}$. Evidence for this scenario
is presented based on the properties of aminoacyl-tRNA synthetases, amino acids
and nucleotide bases.


title:
Mean field theory for a balanced hypercolumn model of orientation
  selectivity in primary visual cortex

abstract:
  We present a complete mean field theory for a balanced state of a simple
model of an orientation hypercolumn. The theory is complemented by a
description of a numerical procedure for solving the mean-field equations
quantitatively. With our treatment, we can determine self-consistently both the
firing rates and the firing correlations, without being restricted to specific
neuron models. Here, we solve the analytically derived mean-field equations
numerically for integrate-and-fire neurons. Several known key properties of
orientation selective cortical neurons emerge naturally from the description:
Irregular firing with statistics close to -- but not restricted to -- Poisson
statistics; an almost linear gain function (firing frequency as a function of
stimulus contrast) of the neurons within the network; and a contrast-invariant
tuning width of the neuronal firing. We find that the irregularity in firing
depends sensitively on synaptic strengths. If Fano factors are bigger than 1,
then they are so for all stimulus orientations that elicit firing. We also find
that the tuning of the noise in the input current is the same as the tuning of
the external input, while that for the mean input current depends on both the
external input and the intracortical connectivity.


title:
Extreme Value Distribution Based Gene Selection Criteria for
  Discriminant Microarray Data Analysis Using Logistic Regression

abstract:
  One important issue commonly encountered in the analysis of microarray data
is to decide which and how many genes should be selected for further studies.
For discriminant microarray data analyses based on statistical models, such as
the logistic regression models, gene selection can be accomplished by a
comparison of the maximum likelihood of the model given the real data,
$\hat{L}(D|M)$, and the expected maximum likelihood of the model given an
ensemble of surrogate data with randomly permuted label, $\hat{L}(D_0|M)$.
Typically, the computational burden for obtaining $\hat{L}(D_0|M)$ is immense,
often exceeding the limits of computing available resources by orders of
magnitude. Here, we propose an approach that circumvents such heavy
computations by mapping the simulation problem to an extreme-value problem. We
present the derivation of an asymptotic distribution of the extreme-value as
well as its mean, median, and variance. Using this distribution, we propose two
gene selection criteria, and we apply them to two microarray datasets and three
classification tasks for illustration.


title: Alternative Splicing and Genomic Stability

abstract:
  Alternative splicing allows an organism to make different proteins in
different cells at different times, all from the same gene. In a cell that uses
alternative splicing, the total length of all the exons is much shorter than in
a cell that encodes the same set of proteins without alternative splicing. This
economical use of exons makes genes more stable during reproduction and
development because a genome with a shorter exon length is more resistant to
harmful mutations. Genomic stability may be the reason why higher vertebrates
splice alternatively. For a broad class of alternatively spliced genes, a
formula is given for the increase in their stability.


title:
Evolutionary ecology in-silico:evolving foodwebs, migrating population
  and speciation

abstract:
  We have generalized our ``unified'' model of evolutionary ecology by taking
into account the possible movements of the organisms from one ``patch'' to
another within the same eco-system. We model the spatial extension of the
eco-system (i.e., the geography) by a square lattice where each site
corresponds to a distinct ``patch''. A self-organizing hierarchical food web
describes the prey-predator relations in the eco-system. The same species at
different patches have identical food habits but differ from each other in
their reproductive characteristic features. By carrying out computer
simulations up to $10^9$ time steps, we found that, depending on the values of
the set of parameters, the distribution of the lifetimes of the species can be
either exponential or a combination of power laws. Some of the other features
of our ``unified'' model turn out to be robust against migration of the
organisms.


title: Population growth and control in stochastic models of cancer development

abstract:
  We study the joint effect of thermal bath fluctuations and an external noise
tuning activity of cytotoxic cells on the triggered immune response in a
growing cancerous tissue. The immune response is assumed to be primarily
mediated by effector cells that develop a cytotoxic activity against the
abnormal tissue. The kinetics of such a reaction is represented by an
enzymatic-like Michaelis-Menten two step process. Effective free-energy surface
for the process is further parametrized by the fluctuating energy barrier
between the states of high and low concentration of cancerous cells. By
analyzing the far from equilibrium escape problem across the fluctuating
potential barrier, we determine condtions of the most efficient decay kinetics
of the cancer cell-population in the presence of dichotomously fluctuating
concentration of cytotoxic cells.


title: A Biological Coevolution Model with Correlated Individual-Based Dynamics

abstract:
  We study the effects of interspecific correlations in a biological
coevolution model in which organisms are represented by genomes of bitstrings.
We present preliminary results for this model, indicating that these
correlations do not significantly affect the statistical behavior of the
system.


title:
The dauer mutation of the caenorhabditis elegans, simulated with the
  Penna and the Stauffer model

abstract:
  Two ageing models were analysed whether they can confirm that the dauer
mutation of the nematode helps to preserve the species. As a result the Penna
model shows that populations with dauer larvae survive bad environmental
conditions, whereas populations without it die out. In the Stauffer model the
advantage of the dauer mutation for the survival is only given under certain
conditions.


title: Variations in Substitution Rate in Human and Mouse Genomes

abstract:
  We present a method to quantify spatial fluctuations of the substitution rate
on different length scales throughout genomes of eukaryotes. The fluctuations
on large length scales are found to be predominantly a consequence of a
coarse-graining effect of fluctuations on shorter length scales. This is
verified for both the mouse and the human genome. We also found that both
species show similar standard deviation of fluctuations even though their mean
substitution rate differs by a factor of two. Our method furthermore allows to
determine time-resolved substitution rate maps from which we can compute
auto-correlation functions in order to quantify how fast the spatial
fluctuations in substitution rate change in time.


title:
Clustering under the line graph transformation: Application to reaction
  network

abstract:
  Many real networks can be understood as two complementary networks with two
kind of nodes. This is the case of metabolic networks where the first network
has chemical compounds as nodes and the second one has nodes as reactions. The
second network can be related to the first one by a technique called line graph
transformation (i.e., edges in an initial network are transformed into nodes).
Recently, the main topological properties of the metabolic networks have been
properly described by means of a hierarchical model. In our work, we apply the
line graph transformation to a hierarchical network and the clustering
coefficient $C(k)$ is calculated for the transformed network, where $k$ is the
node degree. While $C(k)$ follows the scaling law $C(k)\sim k^{-1.1}$ for the
initial hierarchical network, $C(k)$ scales weakly as $k^{0.08}$ for the
transformed network. These results indicate that the reaction network can be
identified as a degree-independent clustering network.


title: Towards comparative theoretical neuroanatomy of the cerebral cortex

abstract:
  Despite differences in brain sizes and cognitive niches among mammals, their
cerebral cortices posses many common features and regularities. These
regularities have been a subject of experimental investigation in neuroanatomy
for the last 100 years. It is believed that such studies may provide clues
about cortical design principles and perhaps function. However, on a
theoretical side there has been little interest, until recently, in studying
quantitatively these regularities. This article reviews some attempts in this
direction with an emphasis on neuronal connectivity. It is suggested that the
brain development is influenced by different, conflicting in outcome,
functional/biochemical constraints. Because of these conflicting constraints,
it is hypothesized that the architecture of the cerebral cortex is shaped by
some global optimization plan.


title:
Green's Function Reaction Dynamics: a new approach to simulate
  biochemical networks at the particle level and in time and space

abstract:
  Biochemical networks are the analog computers of life. They allow living
cells to control a large number of biological processes, such as gene
expression and cell signalling. In biochemical networks, the concentrations of
the components are often low. This means that the discrete nature of the
reactants and the stochastic character of their interactions have to be taken
into account. Moreover, the spatial distribution of the components can be of
crucial importance. However, the current numerical techniques for simulating
biochemical networks either ignore the particulate nature of matter or treat
the spatial fluctuations in a mean-field manner. We have developed a new
technique, called Green's Function Reaction Dynamics (GFRD), that makes it
possible to simulate biochemical networks at the particle level and in both
time and space. In this scheme, a maximum time step is chosen such that only
single particles or pairs of particles have to be considered. For these
particles, the Smoluchowski equation can be solved analytically using Green's
functions. The main idea of GFRD is to exploit the exact solution of the
Smoluchoswki equation to set up an event-driven algorithm. This allows GFRD to
make large jumps in time when the particles are far apart from each other.
Here, we apply the technique to a simple model of gene expression. The
simulations reveal that the scheme is highly efficient. Under biologically
relevant conditions, GFRD is up to six orders of magnitude faster than
conventional particle-based techniques for simulating biochemical networks in
time and space.


title:
Hypothesis: Is percolative clustering an emerging paradigm in
  protein-protein interactions ?

abstract:
  The evolution, regulation and sustenance of biological complexity is
determined by protein-protein interaction network that is filled with dynamic
events. Recent experimental evidences point out that clustering of proteins has
a vital role in many cellular processes. Upsurge in fluorescence imaging
methods has given a new spin to our ability to probe protein interactions in
cellular and sub-cellular compartments. Despite the increasing detection
sensitivity, quantitative information that can be obtained from these imaging
methods is limited. This is primarily due to (i) the difficulty in tracking the
problem analytically and (ii) limitations in spatio-temporal resolution that
can be achieved in interrogating living cells in real time. A novel point of
view based on diffusion-driven percolative clustering is proposed here that can
plausibly shed more light on the complex issues of protein-protein
interactions. Since this model is open to computational analysis, it is
quantitative in its premise. Besides being able to analyze the phenomenon, the
power of any model is gauged by its ability to predict interesting and novel
features of the phenomenon itself, which can subsequently be tested by
additional experiments. To this end, an experimental assay based on
fluorescence lifetime imaging is proposed to verify the validity of the
percolation model.


title: Actin Polymerization Kinetics, Cap Structure and Fluctuations

abstract:
  Polymerization of actin proteins into dynamic structures is essential to
eukaryotic cell life. This has motivated a large body of in vitro experiments
measuring polymerization kinetics of individual filaments. Here we model these
kinetics, accounting for all relevant steps revealed by experiment:
polymerization, depolymerization, random ATP hydrolysis and release of
phosphate (Pi). We relate filament growth rates to the dynamics of ATP-actin
and ADP-Pi-actin caps which develop at filament ends. At the critical
concentration of the barbed end, c_crit, we find a short ATP cap and a long
fluctuation-stabilized ADP-Pi cap. We show that growth rates and the critical
concentration at the barbed end are intimately related to cap structure and
dynamics. Fluctuations in filament lengths are described by the length
diffusion coefficient, D. Recently Fujiwara et al. [Nature Cell Biol. (2002) 4,
666] and Kuhn and Pollard [Biohys. J. (2005) 88, 1387] observed large length
fluctuations slightly above c_crit, provoking speculation that growth may
proceed by oligomeric rather than monomeric on-off events. For the single
monomer growth process we find that $D$ exhibits a pronounced peak below
c_crit}, due to filaments alternating between capped and uncapped states, a
mild version of the dynamic instability of microtubules. Fluctuations just
above c_crit are enhanced but much smaller than those reported experimentally.
Future measurements of D as a function of concentration can help identify the
origin of the observed fluctuations.

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


title: Searching low-energy conformations of two elastin sequences

abstract:
  The three-dimensional structures of two common repeat motifs
Val$^1$-Pro$^2$-Gly$^3$-Val$^4$-Gly$^5$ and
Val$^1$-Gly$^2$-Val$^3$-Pro$^4$-Gly$^5$-Val$^6$-Gly$^7$-Val$^8$-Pro$^9$ of
tropoelastin are investigated by using the multicanonical simulation procedure.
By minimizing the energy structures along the trajectory the thermodynamically
most stable low-energy microstates of the molecule are determined. The
structural predictions are in good agreement with X-ray diffraction
experiments.


title: Bifurcation analysis of a model of the budding yeast cell cycle

abstract:
  We study the bifurcations of a set of nine nonlinear ordinary differential
equations that describe the regulation of the cyclin-dependent kinase that
triggers DNA synthesis and mitosis in the budding yeast, Saccharomyces
cerevisiae. We show that Clb2-dependent kinase exhibits bistability (stable
steady states of high or low kinase activity). The transition from low to high
Clb2-dependent kinase activity is driven by transient activation of
Cln2-dependent kinase, and the reverse transition is driven by transient
activation of the Clb2 degradation machinery. We show that a four-variable
model retains the main features of the nine-variable model. In a three-variable
model exhibiting birhythmicity (two stable oscillatory states), we explore
possible effects of extrinsic fluctuations on cell cycle progression.


title: Information Processing in Brain Microtubules

abstract:
  Models of the mind are based on the possibility of computing in brain
microtubules. From this point of view, information processing is the
fundamental issue for understanding the brain mechanisms that produce
consciousness. The cytoskeleton polymers could store and process information
through their dynamic coupling mediated by mechanical energy. We analyze the
problem of information transfer and storage in brain microtubules, considering
them as a communication channel. We discuss the implications of assuming that
consciousness is generated by the subneuronal process.


title: Stochastic evolution and multifractal classification of prokaryotes

abstract:
  We introduce a model for simulating mutation of prokaryote DNA sequences.
Using that model we can then evaluated traditional techniques like parsimony
and maximum likelihood methods for computing phylogenetic relationships. We
also use the model to mimic large scale genomic changes, and use this to
evaluate multifractal and related information theory techniques which take into
account these large changes in determining phylogenetic relationships.


title: Fluctuations and noise in cancer development

abstract:
  This paper explores fluctuations and noise in various facets of cancer
development. The three areas of particular focus are the stochastic progression
of cells to cancer, fluctuations of the tumor size during treatment, and noise
in cancer cell signalling. We explore the stochastic dynamics of tumor growth
and response to treatment using a Markov model, and fluctutions in tumor size
in response to treatment using partial differential equations. We also explore
noise within gene networks in cancer cells, and noise in inter-cell signalling.


title: Mutual information for examining correlations in DNA

abstract:
  This paper examines two methods for finding whether long-range correlations
exist in DNA: a fractal measure and a mutual information technique. We evaluate
the performance and implications of these methods in detail. In particular we
explore their use comparing DNA sequences from a variety of sources. Using
software for performing in silico mutations, we also consider evolutionary
events leading to long range correlations and analyse these correlations using
the techniques presented. Comparisons are made between these virtual sequences,
randomly generated sequences, and real sequences. We also explore correlations
in chromosomes from different species.


title:
Lever-arm and Washboard-potential theories jointly account for Myosin II
  dynamics

abstract:
  We address the controversial hot question concerning the validity of the
loose-coupling versus the lever-arm models in the actomyosin dynamics by
re-interpreting and extending the washboard potential model proposed by some of
us in a previous paper. In the new theory, a loose-coupling mechanism co-exists
with the deterministic lever-arm model. The synergetic action of a random
component, originating from the harnessed thermal energy, and of the
power-stroke generated by the lever-arm classical mechanism is seen to yield an
excellent fit of the set of data obtained in T. Yanagida's laboratory on the
sliding of Myosin II heads on actin filaments under various load conditions.
Our theoretical arguments are complemented by accurate numerical simulations,
and the robustness of theory is tested via different combination of parameters
and potential profiles.


title:
Mathematical Analysis and Simulations of the Neural Circuit for
  Locomotion in Lamprey

abstract:
  We analyze the dynamics of the neural circuit of the lamprey central pattern
generator (CPG). This analysis provides insights into how neural interactions
form oscillators and enable spontaneous oscillations in a network of damped
oscillators, which were not apparent in previous simulations or abstract phase
oscillator models. We also show how the different behaviour regimes
(characterized by phase and amplitude relationships between oscillators) of
forward/backward swimming, and turning, can be controlled using the neural
connection strengths and external inputs.


title:
Importance of chirality and reduced flexibility of protein side chains:
  A study with square and tetrahedral lattice models

abstract:
  In simple models side chains are often represented implicitly (e.g., by
spin-states) or simplified as one atom. We study side chain effects using
square lattice and tetrahedral lattice models, with explicitly side chains of
two atoms. We distinguish effects due to chirality and effects due to side
chain flexibilities, since residues in proteins are L-residues, and their side
chains adopt different rotameric states. Short chains are enumerated
exhaustively. For long chains, we sample effectively rare events (eg, compact
conformations) and obtain complete pictures of ensemble properties of these
models at all compactness region. We find that both chirality and reduced side
chain flexibility lower the folding entropy significantly for globally compact
conformations, suggesting that they are important properties of residues to
ensure fast folding and stable native structure. This corresponds well with our
finding that natural amino acid residues have reduced effective flexibility, as
evidenced by analysis of rotamer libraries and side chain rotatable bonds. We
further develop a method calculating the exact side-chain entropy for a given
back bone structure. We show that simple rotamer counting often underestimates
side chain entropy significantly, and side chain entropy does not always
correlate well with main chain packing. Among compact backbones with maximum
side chain entropy, helical structures emerges as the dominating
configurations. Our results suggest that side chain entropy may be an important
factor contributing to the formation of alpha helices for compact
conformations.


title: Stacking and Hydrogen Bonding. DNA Cooperativity at Melting

abstract:
  By taking into account base-base stacking interactions we improve the
Generalized Model of Polypeptide Chain (GMPC). Based on a one-dimensional
Potts-like model with many-particle interactions, the GMPC describes the
helix-coil transition in both polypeptides and polynucleotides. In the
framework of the GMPC we show that correctly introduced nearest-neighbor
stacking interactions against the background of hydrogen bonding lead to
increased stability (melting temperature) and, unexpectedly, to decreased
cooperativity (maximal correlation length). The increase in stability is
explained as due to an additional stabilizing interaction (stacking) and the
surprising decrease in cooperativity is seen as a result of mixing of
contributions of hydrogen bonding and stacking.


title: Reconstruction of protein structures from a vectorial representation

abstract:
  We show that the contact map of the native structure of globular proteins can
be reconstructed starting from the sole knowledge of the contact map's
principal eigenvector, and present an exact algorithm for this purpose. Our
algorithm yields a unique contact map for all 221 globular structures of
PDBselect25 of length $N \le 120$. We also show that the reconstructed contact
maps allow in turn for the accurate reconstruction of the three-dimensional
structure. These results indicate that the reduced vectorial representation
provided by the principal eigenvector of the contact map is equivalent to the
protein structure itself. This representation is expected to provide a useful
tool in bioinformatics algorithms for protein structure comparison and
alignment, as well as a promising intermediate step towards protein structure
prediction.


title: Effects of Noise in a Cortical Neural Model

abstract:
  Recently Segev et al. (Phys. Rev. E 64,2001, Phys.Rev.Let. 88, 2002) made
long-term observations of spontaneous activity of in-vitro cortical networks,
which differ from predictions of current models in many features. In this paper
we generalize the EI cortical model introduced in a previous paper (S.Scarpetta
et al. Neural Comput. 14, 2002), including intrinsic white noise and analyzing
effects of noise on the spontaneous activity of the nonlinear system, in order
to account for the experimental results of Segev et al.. Analytically we can
distinguish different regimes of activity, depending from the model parameters.
Using analytical results as a guide line, we perform simulations of the
nonlinear stochastic model in two different regimes, B and C. The Power
Spectrum Density (PSD) of the activity and the Inter-Event-Interval (IEI)
distributions are computed, and compared with experimental results. In regime B
the network shows stochastic resonance phenomena and noise induces aperiodic
collective synchronous oscillations that mimic experimental observations at 0.5
mM Ca concentration. In regime C the model shows spontaneous synchronous
periodic activity that mimic activity observed at 1 mM Ca concentration and the
PSD shows two peaks at the 1st and 2nd harmonics in agreement with experiments
at 1 mM Ca. Moreover (due to intrinsic noise and nonlinear activation function
effects) the PSD shows a broad band peak at low frequency. This feature,
observed experimentally, does not find explanation in the previous models.
Besides we identify parametric changes (namely increase of noise or decreasing
of excitatory connections) that reproduces the fading of periodicity found
experimentally at long times, and we identify a way to discriminate between
those two possible effects measuring experimentally the low frequency PSD.


title: Modeling Interactome: Scale-Free or Geometric?

abstract:
  Networks have been used to model many real-world phenomena to better
understand the phenomena and to guide experiments in order to predict their
behavior. Since incorrect models lead to incorrect predictions, it is vital to
have a correct model. As a result, new techniques and models for analyzing and
modeling real-world networks have recently been introduced. One example of
large and complex networks involves protein-protein interaction (PPI) networks.
We demonstrate that the currently popular scale-free model of PPI networks
fails to fit the data in several respects. We show that a random geometric
model provides a much more accurate model of the PPI data.


title:
Active Brownian Particle and Random Walk Theories of the Motions of
  Zooplankton: Application to Experiments with Swarms of Daphnia

abstract:
  Active Brownian Particles are self-propelled particles that move in a
dissipative medium subject to random forces, or noise . Additionally, they can
be confined by an external field and/or they can interact with one another. The
external field may actually be an attractive marker, for example a light field
(as in the experiment) or an energy potential or a chemical gradient (as in the
theory). The potential energy can also be the result of interparticle
attractive and/or repulsive forces summed over all particles (a mean field
potential). Four, qualitatively different motions of the particles are
possible: at small particle density their motions are approximately independent
of one another subject only to the external field and the noise, which results
in moving randomly through or performing rotational motions about a central
point in space. At increasing densities interactions play an important role and
individuals form a swarm performing several types of self-organized collective
motion. We apply this model for the description of zooplankton Daphnia swarms.
In the case of the zooplankton Daphnia (and probably many other aquatic animals
that form similar motions as well) this vortex is hydrodynamical but motivated
by the self-propelled motion of the individuals. Similar vortex-type motions
have been observed for other creatures ranging in size from bacteria to flocks
of birds and schools of fish. However, our experiment with Daphnia is unique in
that all four motions can be observed in controlled laboratory conditions with
the same animal. Moreover, the theory, presented in both continuous
differential equation and random walk forms, offers a quantitative, physically
based explanation of the four motions.


title:
Partly melted DNA conformations obtained with a probability peak finding
  method

abstract:
  Peaks in the probabilities of loops or bubbles, helical segments, and
unzipping ends in melting DNA are found in this article using a peak finding
method that maps the hierarchical structure of certain energy landscapes. The
peaks indicate the alternative conformations that coexist in equilibrium and
the range of their fluctuations. This yields a representation of the
conformational ensemble at a given temperature, which is illustrated in a
single diagram called a stitch profile. This article describes the methodology
and discusses stitch profiles vs. the ordinary probability profiles using the
phage lambda genome as an example.


title:
On the effect of fluctuating recombination rates on the decorrelation of
  gene histories in the human genome

abstract:
  We show how to incorporate fluctuations of the recombination rate along the
chromosome into standard gene-genealogical models for the decorrelation of gene
histories. This enables us to determine how small-scale fluctuations
(Poissonian hot-spot model) and large-scale variations [Kong et al. (2002)] of
the recombination rate influence this decorrelation. We find that the
empirically determined large-scale variations of the recombination rate give
rise to a significantly slower decay of correlations compared to the standard,
unstructured gene-genealogical model assuming constant recombination rate. A
model with long-range recombination-rate variations and with demographic
structure (divergent population) is found to be consistent with the empirically
observed slow decorrelation of gene histories. Conversely, we show that
small-scale recombination-rate fluctuations do not alter the large-scale
decorrelation of gene histories.


title: Pulse-coupled resonate-and-fire models

abstract:
  We analyze two pulse-coupled resonate-and-fire neurons. Numerical simulation
reveals that an anti-phase state is an attractor of this model. We can
analytically explain the stability of anti-phase states by means of a return
map of firing times, which we propose in this paper. The resultant stability
condition turns out to be quite simple. The phase diagram based on our theory
shows that there are two types of anti-phase states. One of these cannot be
seen in coupled integrate-and-fire models and is peculiar to resonate-and-fire
models. The results of our theory coincide with those of numerical simulations.


title:
Modulation of Base Specific Mutation and Recombination Rates Enables
  Functional Adaptation within the Context of the Genetic Code

abstract:
  The persistence of life requires populations to adapt at a rate commensurate
with the dynamics of their environment. Successful populations that inhabit
highly variable environments have evolved mechanisms to increase the likelihood
of successful adaptation. We introduce a $64 \times 64$ matrix to quantify
base-specific mutation potential, analyzing four different replicative systems,
error-prone PCR, mouse antibodies, a nematode, and Drosophila. Mutational
tendencies are correlated with the structural evolution of proteins. In systems
under strong selective pressure, mutational biases are shown to favor the
adaptive search of space, either by base mutation or by recombination. Such
adaptability is discussed within the context of the genetic code at the levels
of replication and codon usage.


title: Correlations in the T Cell Response to Altered Peptide Ligands

abstract:
  The vertebrate immune system is a wonder of modern evolution. Occasionally,
however, correlations within the immune system lead to inappropriate
recruitment of preexisting T cells against novel viral diseases. We present a
random energy theory for the correlations in the naive and memory T cell immune
responses. The non-linear susceptibility of the random energy model to
structural changes captures the correlations in the immune response to mutated
antigens. We show how the sequence-level diversity of the T cell repertoire
drives the dynamics of the immune response against mutated viral antigens.


title: Statistical analysis of Gene and Intergenic DNA Sequences

abstract:
  Much of the on-going statistical analysis of DNA sequences is focused on the
estimation of characteristics of coding and non-coding regions that would
possibly allow discrimination of these regions. In the current approach, we
concentrate specifically on genes and intergenic regions. To estimate the level
and type of correlation in these regions we apply various statistical methods
inspired from nonlinear time series analysis, namely the probability
distribution of tuplets, the Mutual Information and the Identical Neighbour
Fit. The methods are suitably modified to work on symbolic sequences and they
are first tested for validity on sequences obtained from well--known simple
deterministic and stochastic models. Then they are applied to the DNA sequence
of chromosome 1 of {\em arabidopsis thaliana}. The results suggest that
correlations do exist in the DNA sequence but they are weak and that intergenic
sequences tend to be more correlated than gene sequences. The use of
statistical tests with surrogate data establish these findings in a rigorous
statistical manner.


title: Introduction to new demographic model for humans

abstract:
  The Gompertz model since 1825 has significantly contributed to interpretation
of ageing in biological and social sciences. However, in modern research
findings, it is clear that the Gompertz model is not successful to describe the
whole demographic trajectories. In this letter, a new demographic model is
introduced especially to describe human demographic trajectories, for example,
for Sweden (2002). The new model is derived from the Weibull model with an
age-dependent shape parameter, which seems to indicate the dynamical aspects of
biological systems for longevity. We will discuss the origin of the
age-dependent shape parameter. Finally, the new model presented here has
significant potential to change our understanding of definition of maximum
longevity.


title: Ultimate limit to human longevity

abstract:
  Are there limits to human longevity? We suggest a new demographic model to
describe human demographic trajectories. Specifically, the model mathematically
defines the limits of longevity. Through the demographic analysis of trends for
Sweden (between 1751 and 2002), Switzerland (between 1876 and 2002) and Japan
(between 1950 and 1999), which are the longest-lived countries, we would like
to demonstrate whether or not there is the ultimate limit to longevity. We
analyse the trends of new demographic indicators, the characteristic life and
the shape parameter, and calculate the mathematical limits of longevity. We
find out the surprising phenomenon that the mathematical limits of longevity
decrease as the longevity tendency increases in recent decades. These
paradoxical trends will be explained by the complementarity of longevity, which
is attributable to the nature of biological systems for longevity. According to
the regression analysis, the ultimate limit for humans is estimated to be
approximately 124 years, which may be considered to be the biological limit for
humans.


title:
Metabolic Rate Calibrates the Molecular Clock: Reconciling Molecular and
  Fossil Estimates of Evolutionary Divergence

abstract:
  Observations that rates of molecular evolution vary widely within and among
lineages have cast doubts upon the existence of a single molecular clock.
Differences in the timing of evolutionary events estimated from genetic and
fossil evidence have raised further questions about the existence of molecular
clocks and their use. Here we present a model of nucleotide substitution that
combines new theory on metabolic rate with the now classic neutral theory of
molecular evolution. The model quantitatively predicts rate heterogeneity, and
reconciles differences in molecular- and fossil-estimated dates of evolutionary
events. Model predictions are supported by extensive data from mitochondrial
and nuclear genomes. By accounting for the effects of body size and temperature
on metabolic rate, a single molecular clock explains heterogeneity in rates of
nucleotide substitution in different genes, taxa, and thermal environments.
This model suggests that there is indeed a general molecular clock, as
originally proposed by Zuckerkandl and Pauling, but that it ticks at a constant
substitution rate per unit mass-specific metabolic energy rather than per unit
time. More generally, the model suggests that body size and temperature combine
to control the overall rate of evolution through their effects on metabolism.


title: Modeling Vortex Swarming In Daphnia

abstract:
  Based on experimental observations in \textit{Daphnia}, we introduce an
agent-based model for the motion of single and swarms of animals. Each agent is
described by a stochastic equation that also considers the conditions for
active biological motion. An environmental potential further reflects local
conditions for \textit{Daphnia}, such as attraction to light sources. This
model is sufficient to describe the observed cycling behavior of single
\textit{Daphnia}. To simulate vortex swarming of many \textit{Daphnia}, i.e.
the collective rotation of the swarm in one direction, we extend the model by
considering avoidance of collisions. Two different ansatzes to model such a
behavior are developed and compared. By means of computer simulations of a
multi-agent system we show that local avoidance - as a special form of
asymmetric repulsion between animals - leads to the emergence of a vortex
swarm. The transition from uncorrelated rotation of single agents to the vortex
swarming as a function of the swarm size is investigated. Eventually, some
evidence of avoidance behavior in \textit{Daphnia} is provided by comparing
experimental and simulation results for two animals.


title: Scale-Free topologies and Activatory-Inhibitory interactions

abstract:
  A simple model of activatory-inhibitory interactions controlling the activity
of agents (substrates) through a "saturated response" dynamical rule in a
scale-free network is thoroughly studied. After discussing the most remarkable
dynamical features of the model, namely fragmentation and multistability, we
present a characterization of the temporal (periodic and chaotic) fluctuations
of the quasi-stasis asymptotic states of network activity. The double (both
structural and dynamical) source of entangled complexity of the system temporal
fluctuations, as an important partial aspect of the Correlation
Structure-Function problem, is further discussed to the light of the numerical
results, with a view on potential applications of these general results.


title:
Comparison of tRNA and rRNA Phylogenies in Proteobacteria: Implications
  for the Frequency of Horizontal Gene Transfer

abstract:
  The current picture of bacterial evolution is based largely on studies of 16S
rRNA. However, this is just one gene. It is known that horizontal gene transfer
can occur between bacterial species, although the frequency and implications of
this are not fully understood. If horizontal transfer were frequent, there
would be no single evolutionary tree for bacteria because each gene would
follow a different tree. We carried out phylogenetic analyses of rRNA and tRNA
genes from Proteobacteria (a diverse group for which many complete genome
sequences are available) using RNA-specific phylogenetic methods that account
for the conservation of the secondary structure. We compared trees for 16S rRNA
and 23S rRNA with those derived from concatenated alignments of 29 tRNA genes
that are found in all the genomes studied. The tRNA genes are scattered
throughout the genomes, and would not follow the same evolutionary history if
horizontal transfer were frequent. Nevertheless, the tRNA tree is consistent
with the rRNA tree in most respects. Minor differences can almost all be
attributed to uncertainty or unreliability of the phylogenetic method. We
therefore conclude that tRNA genes give a coherent picture of the phylogeny of
the organisms, and that horizontal transfer of tRNAs is too rare to obscure the
signal of the organismal tree. Some tRNA genes are not present in all the
genomes. We discuss possible explanations for the observed patterns of presence
and absence of genes: these involve gene deletion, gene duplication, and
mutations in the tRNA anticodons.


title:
RNA-based Phylogenetic Methods: Application to Mammalian Mitochondrial
  RNA Sequences

abstract:
  The PHASE software package allows phylogenetic tree construction with a
number of evolutionary models designed specifically for use with RNA sequences
that have conserved secondary structure. Evolution in the paired regions of
RNAs occurs via compensatory substitutions, hence changes on either side of a
pair are correlated. Accounting for this correlation is important for
phylogenetic inference because it affects the likelihood calculation. In the
present study we use the complete set of tRNA and rRNA sequences from 69
complete mammalian mitochondrial genomes. The likelihood calculation uses two
evolutionary models simultaneously for different parts of the sequence: a
paired-site model for the paired sites and a single-site model for the unpaired
sites. We use Bayesian phylogenetic methods and a Markov chain Monte Carlo
algorithm is used to obtain the most probable trees and posterior probabilities
of clades. The results are well resolved for almost all the important branches
on the mammalian tree. They support the arrangement of mammalian orders within
the four supra-ordinal clades that have been identified by studies of much
larger data sets mainly comprising nuclear genes. Groups such as the hedgehogs
and the murid rodents, which have been problematic in previous studies with
mitochondrial proteins, appear in their expected position with the other
members of their order. Our choice of genes and evolutionary model appears to
be more reliable and less subject to biases caused by variation in base
composition than previous studies with mitochondrial genomes.