title: A stochastic approach to multi-gene expression dynamics

abstract:
  In the last years, tens of thousands gene expression profiles for cells of
several organisms have been monitored. Gene expression is a complex
transcriptional process where mRNA molecules are translated into proteins,
which control most of the cell functions. In this process, the correlation
among genes is crucial to determine the specific functions of genes. Here, we
propose a novel multi-dimensional stochastic approach to deal with the gene
correlation phenomena. Interestingly, our stochastic framework suggests that
the study of the gene correlation requires only one theoretical assumption
-Markov property- and the experimental transition probability, which
characterizes the gene correlation system. Finally, a gene expression
experiment is proposed for future applications of the model.


title:
Loop-closure events during protein folding: Rationalizing the shape of
  Phi-value distributions

abstract:
  In the past years, the folding kinetics of many small single-domain proteins
has been characterized by mutational Phi-value analysis. In this article, a
simple, essentially parameter-free model is introduced which derives folding
routes from native structures by minimizing the entropic loop-closure cost
during folding. The model predicts characteristic folding sequences of
structural elements such as helices and beta-strand pairings. Based on few
simple rules, the kinetic impact of these structural elements is estimated from
the routes and compared to average experimental Phi-values for the helices and
strands of 15 small, well-characterized proteins. The comparison leads on
average to a correlation coefficient of 0.62 for all proteins with polarized
Phi-value distributions, and 0.74 if distributions with negative average
Phi-values are excluded. The diffuse Phi-value distributions of the remaining
proteins are reproduced correctly. The model shows that Phi-value
distributions, averaged over secondary structural elements, can often be traced
back to entropic loop-closure events, but also indicates energetic preferences
in the case of a few proteins governed by parallel folding processes.


title:
The large-scale logico-chemical structure of a transcriptional
  regulation network

abstract:
  Identity, response to external stimuli, and spatial architecture of a living
system are central topics of molecular biology. Presently, they are largely
seen as a result of the interplay between a gene repertoire and the regulatory
machinery of the cell. At the transcriptional level, the cis-regulatory regions
establish sets of interdependencies between transcription factors and genes,
including other transcription factors. These ``transcription networks'' are too
large to be approached globally with a detailed dynamical model. In this paper,
we describe an approach to this problem that focuses solely on the
compatibility between gene expression patterns and signal integration
functions, discussing calculations carried on the simplest, Boolean,
realization of the model, and a first application to experimental data sets.


title: Graph theoretic analysis of protein interaction networks of eukaryotes

abstract:
  Thanks to recent progress in high-throughput experimental techniques, the
datasets of large-scale protein interactions of prototypical multicellular
species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila
melanogaster, have been assayed. The datasets are obtained mainly by using the
yeast hybrid method, which contains false-positive and false-negative
simultaneously. Accordingly, while it is desirable to test such datasets
through further wet experiments, here we invoke recent developed network theory
to test such high throughput datasets in a simple way. Based on the fact that
the key biological processes indispensable to maintaining life are universal
across eukaryotic species, and the comparison of structural properties of the
protein interaction networks (PINs) of the two species with those of the yeast
PIN, we find that while the worm and the yeast PIN datasets exhibit similar
structural properties, the current fly dataset, though most comprehensively
screened ever, does not reflect generic structural properties correctly as it
is. The modularity is suppressed and the connectivity correlation is lacking.
Addition of interlogs to the current fly dataset increases the modularity and
enhances the occurrence of triangular motifs as well. The connectivity
correlation function of the fly, however, remains distinct under such interlogs
addition, for which we present a possible scenario through an in silico
modeling.


title:
Early events in insulin fibrillization studied by time-lapse atomic
  force microscopy

abstract:
  The importance of understanding the mechanism of protein aggregation into
insoluble amyloid fibrils relies not only on its medical consequences, but also
on its more basic properties of self--organization. The discovery that a large
number of uncorrelated proteins can form, under proper conditions, structurally
similar fibrils has suggested that the underlying mechanism is a general
feature of polypeptide chains. In the present work, we address the early events
preceeding amyloid fibril formation in solutions of zinc--free human insulin
incubated at low pH and high temperature. Aside from being a easy--to--handle
model for protein fibrillation, subcutaneous aggregation of insulin after
injection is a nuisance which affects patients with diabetes. Here, we show by
time--lapse atomic force microscopy (AFM) that a steady-state distribution of
protein oligomers with an exponential tail is reached within few minutes after
heating. This metastable phase lasts for few hours until aggregation into
fibrils suddenly occurs. A theoretical explanation of the oligomer
pre--fibrillar distribution is given in terms of a simple
coagulation--evaporation kinetic model, in which concentration plays the role
of a critical parameter. Due to high resolution and sensitivity of AFM
technique, the observation of a long-lasting latency time should be considered
an actual feature of the aggregation process, and not simply ascribed to
instrumental inefficency. These experimental facts, along with the kinetic
model used, claim for a critical role of thermal concentration fluctuations in
the process of fibril nucleation.


title: Pairwise alignment incorporating dipeptide covariation

abstract:
  Motivation: Standard algorithms for pairwise protein sequence alignment make
the simplifying assumption that amino acid substitutions at neighboring sites
are uncorrelated. This assumption allows implementation of fast algorithms for
pairwise sequence alignment, but it ignores information that could conceivably
increase the power of remote homolog detection. We examine the validity of this
assumption by constructing extended substitution matrixes that encapsulate the
observed correlations between neighboring sites, by developing an efficient and
rigorous algorithm for pairwise protein sequence alignment that incorporates
these local substitution correlations, and by assessing the ability of this
algorithm to detect remote homologies. Results: Our analysis indicates that
local correlations between substitutions are not strong on the average.
Furthermore, incorporating local substitution correlations into pairwise
alignment did not lead to a statistically significant improvement in remote
homology detection. Therefore, the standard assumption that individual residues
within protein sequences evolve independently of neighboring positions appears
to be an efficient and appropriate approximation.


title:
Biodiversity in model ecosystems, I: Coexistence conditions for
  competing species

abstract:
  This is the first of two papers where we discuss the limits imposed by
competition to the biodiversity of species communities. In this first paper we
study the coexistence of competing species at the fixed point of population
dynamic equations. For many simple models, this imposes a limit on the width of
the productivity distribution, which is more severe the more diverse the
ecosystem is (Chesson, 1994). Here we review and generalize this analysis,
beyond the ``mean-field''-like approximation of the competition matrix used in
previous works, and extend it to structured food webs. In all cases analysed,
we obtain qualitatively similar relations between biodiversity and competition:
the narrower the productivity distribution is, the more species can stably
coexist. We discuss how this result, considered together with environmental
fluctuations, limits the maximal biodiversity that a trophic level can host.


title:
Biodiversity in model ecosystems, II: Species assembly and food web
  structure

abstract:
  This is the second of two papers dedicated to the relationship between
population models of competition and biodiversity. Here we consider species
assembly models where the population dynamics is kept far from fixed points
through the continuous introduction of new species, and generalize to such
models thecoexistence condition derived for systems at the fixed point. The
ecological overlap between species with shared preys, that we define here,
provides a quantitative measure of the effective interspecies competition and
of the trophic network topology. We obtain distributions of the overlap from
simulations of a new model based both on immigration and speciation, and show
that they are in good agreement with those measured for three large natural
food webs. As discussed in the first paper, rapid environmental fluctuations,
interacting with the condition for coexistence of competing species, limit the
maximal biodiversity that a trophic level can host. This horizontal limitation
to biodiversity is here combined with either dissipation of energy or growth of
fluctuations, which in our model limit the length of food webs in the vertical
direction. These ingredients yield an effective model of food webs that produce
a biodiversity profile with a maximum at an intermediate trophic level, in
agreement with field studies.


title: Learning intrinsic excitability in medium spiny neurons

abstract:
  We present an unsupervised, local activation-dependent learning rule for
intrinsic plasticity (IP) which affects the composition of ion channel
conductances for single neurons in a use-dependent way. We use a
single-compartment conductance-based model for medium spiny striatal neurons in
order to show the effects of parametrization of individual ion channels on the
neuronal activation function. We show that parameter changes within the
physiological ranges are sufficient to create an ensemble of neurons with
significantly different activation functions. We emphasize that the effects of
intrinsic neuronal variability on spiking behavior require a distributed mode
of synaptic input and can be eliminated by strongly correlated input. We show
how variability and adaptivity in ion channel conductances can be utilized to
store patterns without an additional contribution by synaptic plasticity (SP).
The adaptation of the spike response may result in either "positive" or
"negative" pattern learning. However, read-out of stored information depends on
a distributed pattern of synaptic activity to let intrinsic variability
determine spike response. We briefly discuss the implications of this
conditional memory on learning and addiction.


title:
Self-organized density patterns of molecular motors in arrays of
  cytoskeletal filaments

abstract:
  The stationary states of systems with many molecular motors are studied
theoretically for uniaxial and centered (aster-like) arrangements of
cytoskeletal filaments using Monte Carlo simulations and a two-state model.
Mutual exclusion of motors from binding sites of the filaments is taken into
account. For small overall motor concentration, the density profiles are
exponential and algebraic in uniaxial and centered filament systems,
respectively. For uniaxial systems, exclusion leads to the coexistence of
regions of high and low densities of bound motors corresponding to motor
traffic jams, which grow upon increasing the overall motor concentration. These
jams are insensitive to the motor behavior at the end of the filament. In
centered systems, traffic jams remain small and an increase in the motor
concentration leads to a flattening of the profile, if the motors move inwards,
and to the build-up of a concentration maximum in the center of the aster if
motors move outwards. In addition to motors density patterns, we also determine
the corresponding patterns of the motor current.


title: On the role of chemical synapses in coupled neurons with noise

abstract:
  We examine the behavior in the presence of noise of an array of Morris-Lecar
neurons coupled via chemical synapses. Special attention is devoted to
comparing this behavior with the better known case of electrical coupling
arising via gap junctions. In particular, our numerical simulations show that
chemical synapses are more efficient than gap junctions in enhancing coherence
at an optimal noise (what is known as array-enhanced coherence resonance): in
the case of (nonlinear) chemical coupling, we observe a substantial increase in
the stochastic coherence of the system, in comparison with (linear) electrical
coupling. We interpret this qualitative difference between both types of
coupling as arising from the fact that chemical synapses only act while the
presynaptic neuron is spiking, whereas gap junctions connect the voltage of the
two neurons at all times. This leads in the electrical coupling case to larger
correlations during interspike time intervals which are detrimental to the
array-enhanced coherence effect. Finally, we report on the existence of a
system-size coherence resonance in this locally coupled system, exhibited by
the average membrane potential of the array.

categories: q-bio.NC cond-mat.other physics.bio-ph q-bio.OT


title: Stochastic gene expression in switching environments

abstract:
  We study a stochastic model proposed recently in the genetic literature to
explain the heterogeneity of cell populations or of gene products. Cells are
located in two colonies, whose sizes fluctuate as birth and migration processes
in switching environments. We prove that there is a range of parameters where
heterogeneity induces a larger mean fitness


title:
Simulations of a mortality plateau in the sexual Penna model for
  biological ageing

abstract:
  The Penna model is a strategy to simulate the genetic dynamics of
age-structured populations, in which the individuals genomes are represented by
bit-strings. It provides a simple metaphor for the evolutionary process in
terms of the mutation accumulation theory. In its original version, an
individual dies due to inherited diseases when its current number of
accumulated mutations, n, reaches a threshold value, T. Since the number of
accumulated diseases increases with age, the probability to die is zero for
very young ages (n < T) and equals 1 for the old ones (n >= T). Here, instead
of using a step function to determine the genetic death age, we test several
other functions that may or may not slightly increase the death probability at
young ages (n < T), but that decreases this probability at old ones. Our
purpose is to study the oldest old effect, that is, a plateau in the mortality
curves at advanced ages. Imposing certain conditions, it has been possible to
obtain a clear plateau using the Penna model. However, a more realistic one
appears when a modified version, that keeps the population size fixed without
fluctuations, is used. We also find a relation between the birth rate, the
age-structure of the population and the death probability.


title:
Release of Brain Mitochondrial Hexokinase by Acidic Proteins and
  Macromolecular Polyanions

abstract:
  Preparations of arachidonic acid binding and non-binding proteins from bovine
brain, four acidic proteins (alpha-casein, phosvitin, beta-lactoglobulin A and
B), the peptide polyglutamate, and two polyanions (heparin, dextran sulfate)
enhanced both basal and glucose 6-phosphate induced solubilization of rat brain
mitochondrial hexokinase (ATP:D-hexose 6-phosphotransferase, EC 2.7.1.1). In
contrast, three other acidic proteins, had little (alpha-lactalbumin) or no
effect (bovine serum albumin, ovalbumin) and five basic proteins inhibited
release of the enzyme. Solubilizing activity therefore appears to require a net
negative charge and one or more of the following structural features: extended
conformation, random coil, and unordered or beta-structure, in the latter case,
as the beta-barrel in the fatty acid binding proteins and beta-lactoglobulins.
It is of interest that a difference of a single negative charge between
beta-lactoglobulin A and B, resulted in a statistically significant difference
in the stimulation of hexokinase release. Possible physiological and
pathological roles of this hexokinase solubilizing effect are discussed
briefly.


title: The Species Abundances Distribution in a new perspective

abstract:
  Studies on distribution, abundance and diversity of species revealed
fascinating universalities in macroecology. Many of these patterns, like the
species-area and range-abundance relationship or the year-to-year fluctuations
in population sizes are expressed as power-law distributions, and indicate thus
scale-invariance. The species abundance distribution (SAD) apparently shows
this scale-free nature only for rare species, and its mathematical form is much
debated. In the present work we propose a new mathematical expression for SAD
which describes reasonable well most of the presently available large-scale
experimental data and the results of the neutral models. This distribution
function leads to an interesting relation between the total number of
individuals, total number of species and the size of the most abundant species
of the meta-community. This novel scaling relation is confirmed by computer
simulations on neutral models.


title:
Transient Information Flow in a Network of Excitatory and Inhibitory
  Model Neurons: Role of Noise and Signal Autocorrelation

abstract:
  We investigate the performance of sparsely-connected networks of
integrate-and-fire neurons for ultra-short term information processing. We
exploit the fact that the population activity of networks with balanced
excitation and inhibition can switch from an oscillatory firing regime to a
state of asynchronous irregular firing or quiescence depending on the rate of
external background spikes.
  We find that in terms of information buffering the network performs best for
a moderate, non-zero, amount of noise. Analogous to the phenomenon of
stochastic resonance the performance decreases for higher and lower noise
levels. The optimal amount of noise corresponds to the transition zone between
a quiescent state and a regime of stochastic dynamics. This provides a
potential explanation on the role of non-oscillatory population activity in a
simplified model of cortical micro-circuits.


title:
Signal buffering in random networks of spiking neurons: microscopic vs.
  macroscopic phenomena

abstract:
  In randomly connected networks of pulse-coupled elements a time-dependent
input signal can be buffered over a short time. We studied the signal buffering
properties in simulated networks as a function of the networks state,
characterized by both the Lyapunov exponent of the microscopic dynamics and the
macroscopic activity derived from mean-field theory. If all network elements
receive the same signal, signal buffering over delays comparable to the
intrinsic time constant of the network elements can be explained by macroscopic
properties and works best at the phase transition to chaos. However, if only 20
percent of the network units receive a common time-dependent signal, signal
buffering properties improve and can no longer be attributed to the macroscopic
dynamics.


title:
Cellular organization by self-organization : mechanisms and models for
  Min protein dynamics

abstract:
  We use the oscillating Min proteins of Escherichia coli as a prototype system
to illustrate the current state and potential of modeling protein dynamics in
space and time. We demonstrate how a theoretical approach has led to striking
new insights into the mechanisms of self-organization in bacterial cells and
indicate how these ideas may be applicable to more complex structure formation
in eukaryotic cells.


title: The use of oscillatory signals in the study of genetic networks

abstract:
  The structure of a genetic network is uncovered by studying its response to
external stimuli (input signals). We present a theory of propagation of an
input signal through a linear stochastic genetic network. It is found that
there are important advantages in using oscillatory signals over step or
impulse signals, and that the system may enter into a pure fluctuation
resonance for a specific input frequency.


title:
Kinetics of target site localization of a protein on DNA: a stochastic
  approach

abstract:
  It is widely recognized that the cleaving rate of a restriction enzyme on
target DNA sequences is several orders of magnitude faster than the maximal one
calculated from the diffusion--limited theory. It was therefore commonly
assumed that the target site interaction of a restriction enzyme with DNA has
to occur via two steps: one--dimensional diffusion along a DNA segment, and
long--range jumps coming from association/dissociation events. We propose here
a stochastic model for this reaction which comprises a series of 1D diffusions
of a restriction enzyme on non-specific DNA sequences interrupted by 3D
excursions in the solution until the target sequence is reached. This model
provides an optimal finding strategy which explains the fast association rate.
Modeling the excursions by uncorrelated random jumps, we recover the expression
of the mean time required for target site association to occur given by Berg &
al. \cite{berg81}, and we explicitly give several physical quantities
describing the stochastic pathway of the enzyme. For competitive target sites
we calculate two quantities: processivity and preference. By comparing these
theoretical expressions to recent experimental data obtained for
\textit{Eco}RV--DNA interaction, we quantify: i) the mean residence time per
binding event of \textit{Eco}RV on DNA for a representative 1D diffusion
coefficient, ii) the average lengths of DNA scanned during the 1D diffusion
(during one binding event and during the overall process), iii) the mean time
and the mean number of visits needed to go from one target site to the other.
Further, we evaluate the dynamics of DNA cleavage with regard to the
probability for the restriction enzyme to perform another 1D diffusion on the
same DNA substrate following a 3D excursion.


title: Functional cartography of complex metabolic networks

abstract:
  High-throughput techniques are leading to an explosive growth in the size of
biological databases and creating the opportunity to revolutionize our
understanding of life and disease. Interpretation of these data remains,
however, a major scientific challenge. Here, we propose a methodology that
enables us to extract and display information contained in complex networks.
Specifically, we demonstrate that one can (i) find functional modules in
complex networks, and (ii) classify nodes into universal roles according to
their pattern of intra- and inter-module connections. The method thus yields a
``cartographic representation'' of complex networks. Metabolic networks are
among the most challenging biological networks and, arguably, the ones with
more potential for immediate applicability. We use our method to analyze the
metabolic networks of twelve organisms from three different super-kingdoms. We
find that, typically, 80% of the nodes are only connected to other nodes within
their respective modules, and that nodes with different roles are affected by
different evolutionary constraints and pressures. Remarkably, we find that
low-degree metabolites that connect different modules are more conserved than
hubs whose links are mostly within a single module.


title: Morphogen Gradient from a Noisy Source

abstract:
  We investigate the effect of time-dependent noise on the shape of a morphogen
gradient in a developing embryo. Perturbation theory is used to calculate the
deviations from deterministic behavior in a simple reaction-diffusion model of
robust gradient formation, and the results are confirmed by numerical
simulation. It is shown that such deviations can disrupt robustness for
sufficiently high noise levels, and the implications of these findings for more
complex models of gradient-shaping pathways are discussed.

categories: q-bio.TO cond-mat.other q-bio.MN q-bio.OT


title:
Optimal Spike-Timing Dependent Plasticity for Precise Action Potential
  Firing

abstract:
  In timing-based neural codes, neurons have to emit action potentials at
precise moments in time. We use a supervised learning paradigm to derive a
synaptic update rule that optimizes via gradient ascent the likelihood of
postsynaptic firing at one or several desired firing times. We find that the
optimal strategy of up- and downregulating synaptic efficacies can be described
by a two-phase learning window similar to that of Spike-Timing Dependent
Plasticity (STDP). If the presynaptic spike arrives before the desired
postsynaptic spike timing, our optimal learning rule predicts that the synapse
should become potentiated. The dependence of the potentiation on spike timing
directly reflects the time course of an excitatory postsynaptic potential. The
presence and amplitude of depression of synaptic efficacies for reversed spike
timing depends on how constraints are implemented in the optimization problem.
Two different constraints, i.e., control of postsynaptic rates or control of
temporal locality,are discussed.


title: Modelling butterfly wing eyespot patterns

abstract:
  Eyespots are concentric motifs with contrasting colours on butterfly wings.
Eyespots have intra- and inter-specific visual signalling functions with
adaptive and selective roles. We propose a reaction-diffusion model that
accounts for eyespot development. The model considers two diffusive morphogens
and three non-diffusive pigment precursors. The first morphogen is produced in
the focus and determines the differentiation of the first eyespot ring. A
second morphogen is then produced, modifying the chromatic properties of the
wing background pigment precursor, inducing the differentiation of a second
ring. The model simulates the general structural organisation of eyespots,
their phenotypic plasticity and seasonal variability, and predicts effects from
microsurgical manipulations on pupal wings as reported in the literature.


title:
Spectral representation: analyzing single-unit activity in
  extracellularly recorded neuronal data without spike sorting

abstract:
  One step in the conventional analysis of extracellularly recorded neuronal
data is spike sorting, which separates electrical signal into action potentials
from different neurons. Because spike sorting involves human judgment, it can
be subjective and time intensive, particularly for large sets of neurons. Here
we propose a simple, automated way to construct alternative representations of
neuronal activity, called spectral representation (SR). In this approach,
neuronal spikes are mapped to a discrete space of spike- waveform features and
time. Spectral representation enables us to find single-unit stimulus related
changes in neuronal activity without spike sorting. We tested the ability of
this method to predict stimuli using both simulated data and experimental data
from an auditory mapping study in anesthetized marmoset monkeys. We find that
our approach produces more accurate classification of stimuli than spike sorted
data for both simulated and experimental conditions. Furthermore, this method
lends itself to automated analysis of extracellularly recorded neuronal
ensembles. Additionally, we suggest ways in which these representations can be
readily extended to assist in spike sorting and the evaluation of single-neuron
peri-stimulus time histograms.


title: A new model for the immune clonal networks

abstract:
  This paper deals with a new model for clonal network dynamics. We describe in
detail this model and derive special equations governing immune system dynamics
based on the general gradient type principles that can be inherent to a wide
class of real living objects. A special clonal network is modeled by two
symmetric projector matrix variables simultaneously taking into account both
asymmetry of the interaction to each other and adaptation states that can be
realized owing to possible idiotypic clonal suppresions. We perform computer
simulations of the model dynamics for some simple cases of relatively low
dimension, paying special attention to the dynamics of amounts of activated
receptor strings within clonal network.


title: The reaction-diffusion approach to morphogenesis

abstract:
  Morphogenesis is the ensemble of processes that determines form, shape and
patterns in organisms. Based on a reaction-diffusion theoretical setting and
some prototype reaction schemes, we make a review of the models and experiments
that support possible mechanisms of morphogenesis. We present specific case
studies from chemistry (Belousov-Zhabotinsky reaction) and biology (formation
of wing eyespots patterns in butterflies). We show the importance of
conservation laws in the establishment of patterning in biological systems, and
their relevance to explain phenotypic plasticity in living organisms. Mass
conservation introduces a memory effect in biological development and
phenotypic plasticity in patterns of living organisms can be explained by
differences on the initial conditions occurring during development.


title:
Harvesting in a resource dependent age structured Leslie type population
  model

abstract:
  We analyse the effect of harvesting in a resource dependent age structured
population model, deriving the conditions for the existence of a stable steady
state as a function of fertility coefficients, harvesting mortality and
carrying capacity of the resources. Under the effect of proportional harvest,
we give a sufficient condition for a population to extinguish, and we show that
the magnitude of proportional harvest depends on the resources available to the
population. We show that the harvesting yield can be periodic, quasi-periodic
or chaotic, depending on the dynamics of the harvested population. For
populations with large fertility numbers, small harvesting mortality leads to
abrupt extinction, but larger harvesting mortality leads to controlled
population numbers by avoiding over consumption of resources. Harvesting can be
a strategy in order to stabilise periodic or quasi-periodic oscillations in the
number of individuals of a population.


title: Helices in Biomolecules

abstract:
  Identical objects, regularly assembled, form a helix, which is the principal
motif of nucleic acids, proteins, and viral capsids.


title:
DNA looping in gene regulation: from the assembly of macromolecular
  complexes to the control of transcriptional noise

abstract:
  The formation of DNA loops by proteins and protein complexes that bind at
distal DNA sites plays a central role in many cellular processes, such as
transcription, recombination, and replication. Here we review the basic
thermodynamic concepts underlying the assembly of macromolecular complexes on
looped DNA and the effects that this process has in the properties of gene
regulation. Beyond the traditional view of DNA looping as a mechanism to
increase the affinity of regulatory molecules for their cognate sites, recent
developments indicate that DNA looping can also lead to the suppression of
cell-to-cell variability, the control of transcriptional noise, and the
activation of cooperative interactions on demand.

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


title:
Evolutionarily conserved human targets of adenosine to inosine RNA
  editing

abstract:
  A-to-I RNA editing by ADARs is a post-transcriptional mechanism for expanding
the proteomic repertoire. Genetic recoding by editing was so far observed for
only a few mammalian RNAs that are predominantly expressed in nervous tissues.
However, as these editing targets fail to explain the broad and severe
phenotypes of ADAR1 knockout mice, additional targets for editing by ADARs were
always expected. Using comparative genomics and expressed sequence analysis, we
identified and experimentally verified four additional candidate human
substrates for ADAR-mediated editing: FLNA, BLCAP, CYFIP2 and IGFBP7.
Additionally, editing of three of these substrates was verified in the mouse
while two of them were validated in chicken. Interestingly, none of these
substrates encodes a receptor protein but two of them are strongly expressed in
the CNS and seem important for proper nervous system function. The editing
pattern observed suggests that some of the affected proteins might have altered
physiological properties leaving the possibility that they can be related to
the phenotypes of ADAR1 knockout mice.


title: Fluctuations in models of biological macroevolution

abstract:
  Fluctuations in diversity and extinction sizes are discussed and compared for
two different, individual-based models of biological coevolution. Both models
display power-law distributions for various quantities of evolutionary
interest, such as the lifetimes of individual species, the quiet periods
between evolutionary upheavals larger than a given cutoff, and the sizes of
extinction events. Time series of the diversity and measures of the size of
extinctions give rise to flicker noise. Surprisingly, the power-law behaviors
of the probability densities of quiet periods in the two models differ, while
the distributions of the lifetimes of individual species are the same.


title: Complete structure of topographic maps in ephrin-A deficient mice

abstract:
  Axons of retinal ganglion cells establish orderly projections to the superior
colliculus of the midbrain. Axons of neighboring cells terminate proximally in
the superior colliculus thus forming a topographically precise representation
of the visual world. Coordinate axes are encoded in retina and in the target
through graded expression of chemical labels. Mapping based on chemical labels
alone does not yield required specificity of connections. Additional sharpening
is provided by electrical activity, which is correlated between neighboring
axons. Here we propose a quantitative model which allows combining the effects
of chemical labels and correlated activity in a single approach. Using this
model we study a complete structure of two-dimensional topographic maps in
mutant mice, in which one of the labels, encoding horizontal retinal coordinate
(ephrin-A), is reduced/eliminated. We show that topographic maps in ephrin-A
deficient mice display granular structure, with the regions of smooth mapping
separated by linear discontinuities reminiscent of fractures observed in the
maps of preferred orientation. We also demonstrate the presence of point
singularities in topographic maps.


title:
SARS oubreaks in Ontario, Hong Kong and Singapore: the role of diagnosis
  and isolation as a control mechanism

abstract:
  In this article we use global and regional data from the SARS epidemic in
conjunction with a model of susceptible, exposed, infective, diagnosed, and
recovered classes of people (``SEIJR'') to extract average properties and rate
constants for those populations. The model is fitted to data from the Ontario
(Toronto) in Canada, Hong Kong in China and Singapore outbreaks and predictions
are made based on various assumptions and observations, including the current
effect of isolating individuals diagnosed with SARS. The epidemic dynamics for
Hong Kong and Singapore appear to be different from the dynamics in Toronto,
Ontario. Toronto shows a very rapid increase in the number of cases between
March 31st and April 6th, followed by a {\it significant} slowing in the number
of new cases. We explain this as the result of an increase in the diagnostic
rate and in the effectiveness of patient isolation after March 26th. Our best
estimates are consistent with SARS eventually being contained in Toronto,
although the time of containment is sensitive to the parameters in our model.
It is shown that despite the empirically modeled heterogeneity in transmission,
SARS' average reproductive number is 1.2, a value quite similar to that
computed for some strains of influenza \cite{CC2}. Although it would not be
surprising to see levels of SARS infection higher than ten per cent in some
regions of the world (if unchecked), lack of data and the observed
heterogeneity and sensitivity of parameters prevent us from predicting the
long-term impact of SARS.


title:
Symmetry and Dynamics in living organisms: The self-similarity principle
  governs gene expression dynamics

abstract:
  The ambitious and ultimate research purpose in Systems Biology is the
understanding and modelling of the cell's system. Although a vast number of
models have been developed in order to extract biological knowledge from
complex systems composed of basic elements as proteins, genes and chemical
compounds, a need remains for improving our understanding of dynamical features
of the systems (i.e., temporal-dependence).
  In this article, we analyze the gene expression dynamics (i.e., how the genes
expression fluctuates in time) by using a new constructive approach. This
approach is based on only two fundamental ingredients: symmetry and the Markov
property of dynamics. First, by using experimental data of human and yeast gene
expression time series, we found a symmetry in short-time transition
probability from time $t$ to time $t+1$. We call it self-similarity symmetry
(i.e., surprisingly, the gene expression short-time fluctuations contain a
repeating pattern of smaller and smaller parts that are like the whole, but
different in size). Secondly, the Markov property of dynamics reflects that the
short-time fluctuation governs the full-time behaviour of the system. Here, we
succeed in reconstructing naturally the global behavior of the observed
distribution of gene expression (i.e., scaling-law) and the local behaviour of
the power-law tail of this distribution, by using only these two ingredients:
symmetry and the Markov property of dynamics. This approach may represent a
step forward toward an integrated image of the basic elements of the whole
cell.


title:
Universal collective fluctuations in gene expression dynamics from yeast
  to human

abstract:
  In this work, the dynamics of fluctuations in gene expression time series is
investigated. By using collected data of gene expression from yeast and human
organisms, we found that the fluctuations of gene expression level and its
average value over time are strongly correlated and obey a scaling law. As this
feature is found in yeast and human organisms, it suggests that probably this
coupling is a common dynamical organizing property of all living systems. To
understand these observations, we propose a stochastic model which can explain
these collective fluctuations, and predict the scaling exponent. Interestingly,
our results indicate that the observed scaling law emerges from the
self-similarity symmetry embedded in gene expression fluctuations.


title: Robustness in Gene Circuits: Clustering of Functional Responses

abstract:
  In contrast to engineering applications, in which the structure of control
laws are designed to satisfy prescribed function requirements, in biology it is
often necessary to infer gene-circuit function from incomplete data on
gene-circuit structure. By using the feed-forward loop as a model system, this
paper introduces a technique for classifying gene-circuit function given
gene-circuit structure. In simulations performed on a comprehensive set of
models that span a broad range of parameter space, some designs are robust,
producing one unique type of functional response regardless of parameter
selection. Other designs may exhibit a variety of functional responses,
depending upon parameter values. We conclude that, although some feed-forward
loop models have designs that lend themselves to unique function inference,
others have designs for which the function type may be uncertain.


title:
The Basic Reproductive Number of Ebola and the Effects of Public Health
  Measures: The Cases of Congo and Uganda

abstract:
  Despite improved control measures, Ebola remains a serious public health risk
in African regions where recurrent outbreaks have been observed since the
initial epidemic in 1976. Using epidemic modeling and data from two
well-documented Ebola outbreaks (Congo 1995 and Uganda 2000), we estimate the
number of secondary cases generated by an index case in the absence of control
interventions ($R_0$). Our estimate of $R_0$ is 1.83 (SD 0.06) for Congo (1995)
and 1.34 (SD 0.03) for Uganda (2000). We model the course of the outbreaks via
an SEIR (susceptible-exposed-infectious-removed) epidemic model that includes a
smooth transition in the transmission rate after control interventions are put
in place. We perform an uncertainty analysis of the basic reproductive number
$R_0$ to quantify its sensitivity to other disease-related parameters. We also
analyze the sensitivity of the final epidemic size to the time interventions
begin and provide a distribution for the final epidemic size. The control
measures implemented during these two outbreaks (including education and
contact tracing followed by quarantine) reduce the final epidemic size by a
factor of 2 relative the final size with a two-week delay in their
implementation.


title: Controlled DNA compaction within chromatin: the tail-bridging effect

abstract:
  We study the mechanism underlying the attraction between nucleosomes, the
fundamental packaging units of DNA inside the chromatin complex. We introduce a
simple model of the nucleosome, the eight-tail colloid, consisting of a charged
sphere with eight oppositely charged, flexible, grafted chains that represent
the terminal histone tails. We demonstrate that our complexes are attracted via
the formation of chain bridges and that this attraction can be tuned by
changing the fraction of charged monomers on the tails. This suggests a
physical mechanism of chromatin compaction where the degree of DNA condensation
can be controlled via biochemical means, namely the acetylation and
deacetylation of lysines in the histone tails.


title:
Comparative Analysis of the Saccharomyces cerevisiae and Caenorhabditis
  elegans Protein Interaction Network

abstract:
  Protein interaction networks aim to summarize the complex interplay of
proteins in an organism. Early studies suggested that the position of a protein
in the network determines its evolutionary rate but there has been considerable
disagreement as to what extent other factors, such as protein abundance, modify
this reported dependence.
  We compare the genomes of Saccharomyces cerevisiae and Caenorhabditis elegans
with those of closely related species to elucidate the recent evolutionary
history of their respective protein interaction networks. Interaction and
expression data are studied in the light of a detailed phylogenetic analysis.
The underlying network structure is incorporated explicitly into the
statistical analysis.
  The increased phylogenetic resolution, paired with high-quality interaction
data, allows us to resolve the way in which protein interaction network
structure and abundance of proteins affect the evolutionary rate. We find that
expression levels are better predictors of the evolutionary rate than a
protein's connectivity. Detailed analysis of the two organisms also shows that
the evolutionary rates of interacting proteins are not sufficiently similar to
be mutually predictive.
  It appears that meaningful inferences about the evolution of protein
interaction networks require comparative analysis of reasonably closely related
species. The signature of protein evolution is shaped by a protein's abundance
in the organism and its function and the biological process it is involved in.
Its position in the interaction networks and its connectivity may modulate this
but they appear to have only minor influence on a protein's evolutionary rate.


title: New symmetry in nucleotide sequences

abstract:
  Information valuable words are the strings with the significant deviation of
real frequency from the expected one. The expected frequency is determined
through the maximum entropy principle of the reconstructed (extended) frequency
dictionary of strings composed from the shorter words. The information valuable
words are found to be the complementary palindromes: they are read equally in
opposite directions, if nucleotides are changed for the complementary ones (A
<--> T; C <--> G) in one of them. Some properties of such symmetric words are
discussed.


title:
Role-similarity based functional prediction in networked systems:
  Application to the yeast proteome

abstract:
  We propose a general method to predict functions of vertices where: 1. The
wiring of the network is somehow related to the vertex functionality. 2. A
fraction of the vertices are functionally classified. The method is influenced
by role-similarity measures of social network analysis. The two versions of our
prediction scheme is tested on model networks were the functions of the
vertices are designed to match their network surroundings. We also apply these
methods to the proteome of the yeast Saccharomyces cerevisiae and find the
results compatible with more specialized methods.


title: On the Statistical Law of Life

abstract:
  In this paper we derive a statistical law of Life. It governs the probability
of death, or complementary of survival, of the living organisms. We have
deduced such a law coupling the widely used Weibull statistics, developed for
describing the distribution of the strength of solids, with the universal model
for ontogenetic growth only recently proposed by West and co-authors. The main
idea presented in this paper is that cracks can propagate in solids and cause
their failure as sick cells in living organisms can cause their death. Making a
rough analogy, living organisms are found to behave as growing mechanical
components under cyclic, i.e., fatigue, loadings and composed by a dynamic
evolutionary material that, as an ineluctable fate, deteriorates. The
implications on biological scaling laws are discussed. As an example of
application, we apply such a statistical law to large data collections on human
deaths due to cancer of various types recorded in Italy: a relevant agreement
is observed.


title:
Study the effects of metallic ions on the combination of DNA and
  histones with molecular combing technique

abstract:
  The effects of monovalent (Na+, K+) and divalent (Mg2+, Ca2+, Mn2+) ions on
the interaction between DNA and histone are studied using the molecular combing
technique. Lamda-DNA molecules and DNA-histone complexes incubated with metal
cations (Na+, K+, Mg2+, Ca2+, Mn2+) are stretched on hydrophobic surfaces, and
directly observed by fluorescence microscopy. The results indicate that when
these cations are added into the DNA solution, the fluorescence intensities of
the stained DNA are reduced differently. The monovalent cations (Na+, K+)
inhibit binding of histone to DNA. The divalent cations (Mg2+, Ca2+, Mn2+)
enhance significantly the binding of histone to DNA and the binding of the
DNA-histone complex to the hydrophobic surface. Mn2+ also induces condensation
and aggregation of the DNA-histone complex.


title:
Non-Maxwellian velocity distribution and anomalous diffusion of {\it in
  vitro} kidney cells

abstract:
  This manuscript uses a statistical mechanical approach to study the effect of
the adhesion, through MOCA protein, on cell locomotion. The MOCA protein
regulates cell-cell adhesion, and we explore its potential role in the cell
movement. We present a series of statistical descriptions of the motion in
order to characterize the cell movement, and found that MOCA affects the
statistical scenario of cell locomotion. In particular, we observe that MOCA
enhances the tendency of joint motion, inhibits super-diffusion, and decreases
overall cell motion. These facts are compatible with the hypothesis that the
cells move faster in a less cohesive environment. Furthermore, we observe that
velocity distribution tails are longer than those predicted by
Maxwell-Boltzmann in all cases studied here, indicating that cell movement is
more complex than that of a liquid.

categories: q-bio.CB cond-mat.other q-bio.OT q-bio.SC


title: Estimation of protein folding probability from equilibrium simulations

abstract:
  The assumption that similar structures have similar folding probabilities
($p_{fold}$) leads naturally to a procedure to evaluate $p_{fold}$ for every
snapshot saved along an equilibrium folding-unfolding trajectory of a
structured peptide or protein. The procedure utilizes a structurally
homogeneous clustering and does not require any additional simulation. It can
be used to detect multiple folding pathways as shown for a three-stranded
antiparallel $\beta$-sheet peptide investigated by implicit solvent molecular
dynamics simulations.


title: Sociophysics Simulations III: Retirement Demography

abstract:
  This third part of the lecture series deals with the question: Who will pay
for your retirement? For Western Europe the answer may be ``nobody'', but for
Algeria the demography looks more promising.


title: Simulation of stem cell survival in small crypts

abstract:
  Monte Carlo simulations of the number of stem cells in human colon crypts
allow for fluctuations which kill the population after sufficiently long times.


title: Functional Dynamics of PDZ Binding Domains: A Normal Mode Analysis

abstract:
  PDZ (Post-synaptic density-95/discs large/zonula occludens-1) domains are
relatively small (80 to 120 residues) protein binding modules central in the
organization of receptor clusters and in the association of cellular proteins.
Their main function is to bind C-terminals of selected proteins that are
recognized through specific amino-acids in their carboxyl end. Binding is
associated with a deformation of the PDZ native structure and is responsible
for dynamical changes in regions not in direct contact with the target. We
investigate how this deformation is related to the harmonic dynamics of the PDZ
structure and show that one low-frequency collective normal mode, characterized
by the concerted movements of different secondary structures, is involved in
the binding process. Our results suggest that even minimal structural changes
are responsible of communication between distant regions of the protein, in
agreement with recent Nuclear Magnetic Resonance (NMR) experiments. Thus PDZ
domains are a very clear example of how collective normal modes are able to
characterize the relation between function and dynamics of proteins, and to
provide indications on the precursors of binding/unbonding events.


title:
Probabilistic methods for predicting protein functions in
  protein-protein interaction networks

abstract:
  We discuss probabilistic methods for predicting protein functions from
protein-protein interaction networks. Previous work based on Markov Randon
Fields is extended and compared to a general machine-learning theoretic
approach. Using actual protein interaction networks for yeast from the MIPS
database and GO-SLIM function assignments, we compare the predictions of the
different probabilistic methods and of a standard support vector machine. It
turns out that, with the currently available networks, the simple methods based
on counting frequencies perform as well as the more sophisticated approaches.


title: Inhibitory synchrony as a mechanism for attentional gain modulation

abstract:
  Recordings from area V4 of monkeys have revealed that when the focus of
attention is on a visual stimulus within the receptive field of a cortical
neuron, two distinct changes can occur: The firing rate of the neuron can
change and there can be an increase in the coherence between spikes and the
local field potential in the gamma-frequency range (30-50 Hz). The hypothesis
explored here is that these observed effects of attention could be a
consequence of changes in the synchrony of local interneuron networks. We
performed computer simulations of a Hodgkin-Huxley type neuron driven by a
constant depolarizing current, I, representing visual stimulation and a
modulatory inhibitory input representing the effects of attention via local
interneuron networks. We observed that the neuron's firing rate and the
coherence of its output spike train with the synaptic inputs was modulated by
the degree of synchrony of the inhibitory inputs. The model suggest that the
observed changes in firing rate and coherence of neurons in the visual cortex
could be controlled by top-down inputs that regulated the coherence in the
activity of a local inhibitory network discharging at gamma frequencies.


title:
Long-term evolution of an ecosystem with spontaneous periodicity of mass
  extinctions

abstract:
  Twenty years ago, after analysing palaeontological data, Raup and Sepkoski
suggested that mass extinctions on Earth appear cyclically in time with a
period of approximately 26 million years (My). To explain the 26My period, a
number of proposals were made involving, e.g., astronomical effects, increased
volcanic activity, or the Earth's magnetic field reversal, none of which,
however, has been confirmed. Here we study a spatially extended discrete model
of an ecosystem and show that the periodicity of mass extinctions might be a
natural feature of the ecosystem's dynamics and not the result of a periodic
external perturbation. In our model, periodic changes of the diversity of an
ecosystem and some of its other characteristics are induced by the coevolution
of species. In agreement with some palaeontological data, our results show that
the longevity of a species depends on the evolutionary stage at which the
species is created. Possible further tests of our model are also discussed.


title:
Comments on "Structural dynamics and resonance in plants with nonlinear
  stiffness"

abstract:
  We make comments on the paper by Miller [{\it J. Theor. Biol.} {\bf 234}
(2005) 511].


title: Spontaneous flow transition in active polar gels

abstract:
  We study theoretically the effects of confinement on active polar gels such
as the actin network of eukaryotic cells. Using generalized hydrodynamics
equations derived for active gels, we predict, in the case of quasi
one-dimensional geometry, a spontaneous flow transition from a homogeneously
polarized immobile state for small thicknesses, to a perturbed flowing state
for larger thicknesses. The transition is not driven by an external field but
by the activity of the system. We suggest several possible experimental
realizations.


title:
Computational Methods and Results for Structured Multiscale Models of
  Tumor Invasion

abstract:
  We present multiscale models of cancer tumor invasion with components at the
molecular, cellular, and tissue levels. We provide biological justifications
for the model components, present computational results from the model, and
discuss the scientific-computing methodology used to solve the model equations.
The models and methodology presented in this paper form the basis for
developing and treating increasingly complex, mechanistic models of tumor
invasion that will be more predictive and less phenomenological. Because many
of the features of the cancer models, such as taxis, aging and growth, are seen
in other biological systems, the models and methods discussed here also provide
a template for handling a broader range of biological problems.


title:
Altruistic behavior pays, or the importance of fluctuations in
  evolutionary game theory

abstract:
  Human behavior is one of the main problems for evolution, as it is often the
case that human actions are disadvantageous for the self and advantageous for
other people. Behind this puzzle are our beliefs about rational behavior, based
on game theory. Here we show that by going beyond the standard game-theoretical
conventions, apparently altruistic behavior can be understood as
self-interested. We discuss in detail an example related to the so called
Ultimatum game and illustrate the appearance of altruistic behavior induced by
fluctuations. In addition, we claim that in general settings, fluctuations play
a very relevant role, and we support this claim by considering a completely
different example, namely the Stag-Hunt game.


title:
Variable selection from random forests: application to gene expression
  data

abstract:
  Random forest is a classification algorithm well suited for microarray data:
it shows excellent performance even when most predictive variables are noise,
can be used when the number of variables is much larger than the number of
observations, and returns measures of variable importance. Thus, it is
important to understand the performance of random forest with microarray data
and its use for gene selection.
  We first show the effects of changes in parameters of random forest on the
prediction error. Then we present an approach for gene selection that uses
measures of variable importance and error rate, and is targeted towards the
selection of small sets of genes. Using simulated and real microarray data, we
show that the gene selection procedure yields small sets of genes while
preserving predictive accuracy.
  Availability: All code is available as an R package, varSelRF, from CRAN,
http://cran.r-project.org/src/contrib/PACKAGES.html, or from the supplementary
material page.
  Supplementary information:
http://ligarto.org/rdiaz/Papers/rfVS/randomForestVarSel.html


title: Species Abundances Distribution in Neutral Community Models

abstract:
  An analytical approximation is derived for the Zero Sum Multinomial
distribution which gives the Species Abundance Distribution in Neutral
Community Models. The obtained distribution function describes well computer
simulation results on the model, and leads to an interesting relation between
the total number of individuals, total number of species and the size of the
most abundant species of the considered metacommunity. Computer simulations on
neutral community models, proves also the validity of this scaling relation.


title: Nucleation and the transition state of the SH3 domain

abstract:
  We present a verified computational model of the SH3 domain transition state
(TS) ensemble. This model was built for three separate SH3 domains using
experimental s in all-atom protein folding simulations. While averaging over
all conformations incorrectly considers non-TS conformations as transition
states, quantifying structures as pre-TS, TS, and post-TS by measurement of
their transmission coefficient (pfold, or probability to fold) allows for
rigorous conclusions regarding the structure of the folding nucleus and a full
mechanistic analysis of the folding process. Through analysis of the TS, we
observe a highly polarized nucleus in which many residues are solvent-exposed.
Mechanistic analysis suggests the hydrophobic core forms largely after an early
nucleation step. SH3 presents an ideal system for studying the
nucleation-condensation mechanism and highlights the synergistic relationship
between experiment and simulation in the study of protein folding.


title: Computational Theory of Biological Function I

abstract:
  This series presents an approach to mathematical biology which makes precise
the function of biological molecules. Because biological systems compute, the
theory is a general purpose computer language. I build a language for
efficiently representing the function of protein-like molecules in a cell. The
first paper only presents the kinematic part of the formalism, but this is
already useful for representing large-scale protein networks. The full
formalism allows us to investigate the properties of protein interaction
models, ultimately yielding an estimate of the random-access memory of the
proteins, a measure of their capacity for computation.


title: Mechanical unfolding of RNA hairpins

abstract:
  Mechanical unfolding trajectories, generated by applying constant force in
optical tweezer experiments, show that RNA hairpins and the P5abc subdomain of
the group I intron unfold reversibly. We use coarse-grained Go-like models for
RNA hairpins to explore forced-unfolding over a broad range of temperatures. A
number of predictions that are amenable to experimental tests are made. At the
critical force the hairpin jumps between folded and unfolded conformations
without populating any discernible intermediates. The phase diagram in the
force-temperature (f,T) plane shows that the hairpin unfolds by an all-or-none
process. The cooperativity of the unfolding transition increases dramatically
at low temperatures. Free energy of stability, obtained from time averages of
mechanical unfolding trajectories, coincide with ensemble averages which
establishes ergodicity. The hopping time between the the native basin of
attraction (NBA) and the unfolded basin increases dramatically along the phase
boundary. Thermal unfolding is stochastic whereas mechanical unfolding occurs
in "quantized steps" with great variations in the step lengths. Refolding
times, upon force quench, from stretched states to the NBA is "at least an
order of magnitude" greater than folding times by temperature quench. Upon
force quench from stretched states the NBA is reached in at least three stages.
In the initial stages the mean end-to-end distance decreases nearly
continuously and only in the last stage there is a sudden transition to the
NBA. Because of the generality of the results we propose that similar behavior
should be observed in force quench refolding of proteins.


title: Quantifying Influenza Vaccine Efficacy and Antigenic Distance

abstract:
  We introduce a new measure of antigenic distance between influenza A vaccine
and circulating strains. The measure correlates well with efficacies of the
H3N2 influenza A component of the annual vaccine between 1971 and 2004, as do
results of a theory of the immune response to influenza following vaccination.
This new measure of antigenic distance is correlated with vaccine efficacy to a
greater degree than are current state-of-the-art phylogenetic sequence analyzes
or ferret antisera inhibition assays. We suggest that this new measure of
antigenic distance be used in the design of the annual influenza vaccine and in
the interpretation of vaccine efficacy monitoring.


title: Extracellular-to-intracellular signal transfer via G-proteins

abstract:
  We look at the problem of signal transduction by extracellular agonist
binding to a receptor protein at the membrane (sensor) via binding of
G-proteins (effectors) to a highly integrative target molecule, such as the
second messenger cAMP (target). We explore the effects of binding times,
effector assignment and effector pool size on the shape of the output signal
under different input scenarios. We conclude that low rates of information
transfer may sometimes coincide with a high probability or efficiency of
plasticity induction.


title:
Predicting Secondary Structures, Contact Numbers, and Residue-wise
  Contact Orders of Native Protein Structure from Amino Acid Sequence by
  Critical Random Networks

abstract:
  Prediction of one-dimensional protein structures such as secondary structures
and contact numbers is useful for the three-dimensional structure prediction
and important for the understanding of sequence-structure relationship. Here we
present a new machine-learning method, critical random networks (CRNs), for
predicting one-dimensional structures, and apply it, with position-specific
scoring matrices, to the prediction of secondary structures (SS), contact
numbers (CN), and residue-wise contact orders (RWCO). The present method
achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients
of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS
prediction is comparable to other state-of-the-art methods, and that of the CN
prediction is a significant improvement over previous methods. We give a
detailed formulation of critical random networks-based prediction scheme, and
examine the context-dependence of prediction accuracies. In order to study the
nonlinear and multi-body effects, we compare the CRNs-based method with a
purely linear method based on position-specific scoring matrices. Although not
superior to the CRNs-based method, the surprisingly good accuracy achieved by
the linear method highlights the difficulty in extracting structural features
of higher order from amino acid sequence beyond that provided by the
position-specific scoring matrices.


title:
Studies on European beech (Fagus sylvatica L.). Part 1: Variations of
  wood colour parameters

abstract:
  Colour parameters of European beech were measured using CIELab system. 103
logs from 87 trees in 9 sites were cut into boards to study the variations of
wood colour parameters. Both site and tree effect on colour were observed.
Patterns of red heartwood occurrence were defined. When excepting red heartwood
there was still a highly significant effect of site and tree; differences
remained after veneer processing. Axial variations were small, except very near
the pith or in red heartwood, suggesting possible early selection at periphery
under colour criteria. Red heartwood is darker, redder and more yellow than
normal peripheral wood.


title: Study of a model for the folding of a small protein

abstract:
  We describe the results obtained from an improved model for protein folding.
We find that a good agreement with the native structure of a 46 residue long,
five-letter protein segment is obtained by carefully tuning the parameters of
the self-avoiding energy. In particular we find an improved free-energy
profile. We also compare the efficiency of the multidimensional replica
exchange method with the widely used parallel tempering.


title: Application of Random Matrix Theory to Biological Networks

abstract:
  We show that spectral fluctuation of interaction matrices of yeast a core
protein interaction network and a metabolic network follows the description of
the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT).
Furthermore, we demonstrate that while the global biological networks evaluated
belong to GOE, removal of interactions between constituents transitions the
networks to systems of isolated modules described by the Poisson statistics of
RMT. Our results indicate that although biological networks are very different
from other complex systems at the molecular level, they display the same
statistical properties at large scale. The transition point provides a new
objective approach for the identification of functional modules.


title: On the Genealogy of Populations: Trees, Branches and Offsprings

abstract:
  We consider a neutral haploid population whose generations are not
overlapping and whose size is large and constantly of $N$ individuals. Any
generation is replaced by a new one and any individual has a single parent. We
do not choose the stochastic rule which assigns the number of offsprings to any
individual since results do not depend on the details of the dynamics, and, as
a consequence, the model is parameter free. The genealogical tree is very
complex, and distances between individuals (number of generations from the
common ancestor) are distributed according to probability density which remains
random in the thermodynamic limit (large population). We give a theoretical and
numerical description of this distribution and we also consider the dynamical
aspects of the problem describing the time evolution of the maximum and mean
distances in a single population.


title: Elastic properties of grafted microtubules

abstract:
  We use single-particle tracking to study the elastic properties of single
microtubules grafted to a substrate. Thermal fluctuations of the free
microtubule's end are recorded, in order to measure position distribution
functions from which we calculate the persistence length of microtubules with
contour lengths between 2.6 and 48 micrometers. We find the persistence length
to vary by more than a factor of 20 over the total range of contour lengths.
Our results support the hypothesis that shearing between protofilaments
contributes significantly to the mechanics of microtubules.


title: Principles in the Evolution of Metabolic Networks

abstract:
  Understanding design principles of complex cellular organization is one of
the major challenges in biology. Recent analysis of the large-scale cellular
organization has revealed the scale-free nature and robustness of metabolic and
protein networks. However, the underlying evolutional process that creates such
a cellular organization is not fully elucidated. To approach this problem, we
analyzed the metabolic networks of 126 organisms, whose draft or complete
genome sequences have been published. This analysis has revealed that the
evolutional process of metabolic networks follows the same and surprisingly
simple principles in Archaea, Bacteria and Eukaryotes; where highly linked
metabolites change their chemical links more dynamically than less linked
metabolites. Here we demonstrate that this rich-travel-more mechanism rather
than the previously proposed rich-get-richer mechanism can generate the
observed scale-free organization of metabolic networks. These findings
illustrate universal principles in evolution of metabolic networks and suggest
marked flexibility of metabolic network throughout evolution.


title: Free energy adopted stochastic optimization protein folding

abstract:
  Optimal structure of proteins is described by linear stochastic differential
equation with mean decrease of free energy and volatility. Structure
determining strategy is given by a twin of stochastic variables for which
empirical conditions are not postulated. Optimal structure determination will
be deformed to be adoptive to trading strategy employing martingale property
where stochastic integral w.r.t. analytical solution of stochastic differential
equation will be employed.


title: Ubiquity of Log-normal Distributions in Intra-cellular Reaction Dynamic

abstract:
  The discovery of two fundamental laws concerning cellular dynamics with
recursive growth is reported. First, the chemical abundances measured over many
cells are found to obey a log-normal distribution and second, the relationship
between the average and standard deviation of the abundances is found to be
linear. The ubiquity of the laws is explored both theoretically and
experimentally. First by means of a model with a catalytic reaction network,
the laws are shown to appear near the critical state with efficient
self-reproduction. Second by measuring distributions of fluorescent proteins in
bacteria cells the ubiquity of log-normal distribution of protein abundances is
confirmed. Relevance of these findings to cellular function and biological
plasticity is briefly discussed.


title:
Morphological complex networks: Can individual morphology determine the
  general connectivity and dynamics of networks?

abstract:
  This article discusses how the individual morphological properties of basic
objects (e.g. neurons, molecules and aggregates), jointly with their particular
spatial distribution, can determine the connectivity and dynamics of systems
composed by those objects. This problem is characterized as a particular case
of the more general shape and function paradigm, which emphasizes the interplay
between shape and function in nature and evolution. Five key issues are
addressed: (a) how to measure shapes; (b) how to obtain stochastic models of
classes of shapes; (c) how to simulate morphologically realistic systems of
multiple objects; (d) how to characterize the connectivity and topology of such
systems in terms of complex network concepts and measurements; and (e) how the
dynamics of such systems can be ultimately affected, and even determined, by
the individual morphological features of the basic objects. Although emphasis
is placed on neuromorphic systems, the presented concepts and methods are
useful also for several other multiple object systems, such as protein-protein
interaction, tissues, aggregates and polymers.


title: A nonlocal continuum model for biological aggregation

abstract:
  We construct a continuum model for biological aggregations in which
individuals experience long-range social attraction and short range dispersal.
For the case of one spatial dimension, we study the steady states analytically
and numerically. There exist strongly nonlinear states with compact support and
steep edges that correspond to localized biological aggregations, or clumps.
These steady state clumps are approached through a dynamic coarsening process.
In the limit of large population size, the clumps approach a constant density
swarm with abrupt edges. We use energy arguments to understand the nonlinear
selection of clump solutions, and to predict the internal density in the large
population limit. The energy result holds in higher dimensions as well, and is
demonstrated via numerical simulations in two dimensions.


title:
Brush Effects on DNA Chips: Thermodynamics, Kinetics and Design
  Guidlines

abstract:
  In biology experiments, oligonucleotide microarrays are contacted with a
solution of long nucleic acid (NA) targets. The hybridized probes thus carry
long tails. When the surface density of the oligonucleotide probes is high
enough, the progress of hybridization leads to the formation of a
polyelectrolyte brush due to mutual crowding of the NA tails. The free energy
penalty associated with the brush modifies both the hybridization isotherms and
the rate equations: the attainable hybridization is lowered significantly as is
the hybridization rate. While the equilibrium hybridization fraction, $x_{eq}$,
is low, the hybridization follows a Langmuir type isotherm, $x_{eq}/(1-x_{eq})
= c_t K$ where $c_t$ is the target concentration and $K$ is the equilibrium
constant smaller than its bulk value by a factor $(n/N)^{2/5}$ due to wall
effects where $n$ and $N$ denote the number of bases in the probe and the
target. At higher $x_{eq}$, when the brush is formed, the leading correction is
$x_{eq}/(1-x_{eq}) = c_t K \exp [ - const' (x_{eq}^{2/3} - x_B^{2/3})]$ where
$x_B$ corresponds to the onset of the brush regime. The denaturation rate
constant in the two regimes are identical. However, the hybridization rate
constant in the brush regime is lower, the leading correction being $\exp [-
const' (x^{2/3} - x_B^{2/3})]$.


title: Metabolic Network Modelling: Including Stochastic Effects

abstract:
  We propose to model the dynamics of metabolic networks from a systems biology
point of view by four dynamical structure elements: potential function,
transverse matrix, degradation matrix, and stochastic force. These four
elements are balanced to determine the network dynamics, which gives arise to a
special stochastic differential equation supplemented by a relationship between
the stochastic force and the degradation matrix. Important network behaviors
can be obtained from the potential function without explicitly solving for the
time-dependent solution. The existence of such a potential function suggests a
global optimization principle, and the existence stochastic force corresponds
natural to the hierarchical structure in metabolic networks. We provide
theoretical evidences to justify our proposal by discussing its connections to
others large-scale biochemical systems approaches, such as the network
thermodynamics theory, biochemical systems theory, metabolic control analysis,
and flux balance analysis. Experimental data displaying stochasticity are also
pointed out.


title: Electronic Transport in DNA

abstract:
  We study the electronic properties of DNA by way of a tight-binding model
applied to four particular DNA sequences. The charge transfer properties are
presented in terms of localisation lengths, crudely speaking the length over
which electrons travel. Various types of disorder, including random potentials,
are employed to account for different real environments. We have performed
calculations on poly(dG)-poly(dC), telomeric-DNA, random-ATGC DNA and
lambda-DNA. We find that random and lambda-DNA have localisation lengths
allowing for electron motion among a few dozen base pairs only. A novel
enhancement of localisation lengths is observed at particular energies for an
increasing binary backbone disorder. We comment on the possible biological
relevance of sequence dependent charge transfer in DNA.


title: Geometrical constraints in a gene network model and pattern formation

abstract:
  A fundamental task in developmental biology is to identify the mechanisms
which drive morphogenesis. In many cases, pattern formation is driven by the
positional information determined by both the gradient of maternal factors and
hard-wired mechanisms embedded in the genome. Alternative mechanisms of
positional information that contribute to patterning are the influence of
signals derived from surrounding tissues. In this paper, we show that the
interplay of geometrical constraints imposed by tissue shapes and hard-wired
mechanisms, computationally implemented by a gene network model, can able to
induce stable complex patterns. The rise of these patterns depends strongly on
the geometrical constraints such as the shape of the surrounding tissues.


title: Computer Simulations to Study Sympatric Speciation Processes

abstract:
  We perform simulations based on the Penna model for biological ageing, now
with the purpose of studying sympatric speciation, that is, the division of a
single species into two or more populations, reproductively isolated, but
without any physical barrier separating them. For that we introduce a new kind
of competition among the individuals, using a modified Verhulst factor. The new
competition depends on some specific phenotypic characteristic of each
individual, which is represented by a pair of bitstrings. These strings are
read in parallel and have no age structure. In this way, each individual genome
consists of two parts. The first one has an age-structure and is related to the
appearance of inherited diseases; the second part is not structured and takes
into account the competition for the available resources. We also introduce
sexual selection into the model, making use of another non-structured and
independent pair of bitstrings.
  In this thesis we present three different models; two of them use, besides
the competition, a sudden change in the ecology to obtain speciation. They were
motivated by the speciation process observed in the Darwin finches, a family of
birds that inhabits the Galapagos Islands, and also by that observed in the
cichlids, a family of fish that lives in the Nicaragua Lakes and in the Vitoria
Lake, in Africa. The third model does not use any ecological change: sympatric
speciation is obtained depending only on the strength of competition among
individuals with similar phenotypic characteristics.


title:
A methodology for determining amino-acid substitution matrices from set
  covers

abstract:
  We introduce a new methodology for the determination of amino-acid
substitution matrices for use in the alignment of proteins. The new methodology
is based on a pre-existing set cover on the set of residues and on the
undirected graph that describes residue exchangeability given the set cover.
For fixed functional forms indicating how to obtain edge weights from the set
cover and, after that, substitution-matrix elements from weighted distances on
the graph, the resulting substitution matrix can be checked for performance
against some known set of reference alignments and for given gap costs. Finding
the appropriate functional forms and gap costs can then be formulated as an
optimization problem that seeks to maximize the performance of the substitution
matrix on the reference alignment set. We give computational results on the
BAliBASE suite using a genetic algorithm for optimization. Our results indicate
that it is possible to obtain substitution matrices whose performance is either
comparable to or surpasses that of several others, depending on the particular
scenario under consideration.


title:
L-selectin mediated leukocyte tethering in shear flow is controlled by
  multiple contacts and cytoskeletal anchorage facilitating fast rebinding
  events

abstract:
  L-selectin mediated tethers result in leukocyte rolling only above a
threshold in shear. Here we present biophysical modeling based on recently
published data from flow chamber experiments (Dwir et al., J. Cell Biol. 163:
649-659, 2003) which supports the interpretation that L-selectin mediated
tethers below the shear threshold correspond to single L-selectin carbohydrate
bonds dissociating on the time scale of milliseconds, whereas L-selectin
mediated tethers above the shear threshold are stabilized by multiple bonds and
fast rebinding of broken bonds, resulting in tether lifetimes on the timescale
of $10^{-1}$ seconds. Our calculations for cluster dissociation suggest that
the single molecule rebinding rate is of the order of $10^4$ Hz. A similar
estimate results if increased tether dissociation for tail-truncated L-selectin
mutants above the shear threshold is modeled as diffusive escape of single
receptors from the rebinding region due to increased mobility. Using computer
simulations, we show that our model yields first order dissociation kinetics
and exponential dependence of tether dissociation rates on shear stress. Our
results suggest that multiple contacts, cytoskeletal anchorage of L-selectin
and local rebinding of ligand play important roles in L-selectin tether
stabilization and progression of tethers into persistent rolling on endothelial
surfaces.


title: Dynamics of conduction blocks in a model of paced cardiac tissue

abstract:
  We study numerically the dynamics of conduction blocks using a detailed
electrophysiological model. We find that this dynamics depends critically on
the size of the paced region. Small pacing regions lead to stationary
conduction blocks while larger pacing regions can lead to conduction blocks
that travel periodically towards the pacing region. We show that this
size-dependence dynamics can lead to a novel arrhythmogenic mechanism.
Furthermore, we show that the essential phenomena can be captured in a much
simpler coupled-map model.

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


title: Statistical modeling of primary Ewing tumours of the bone

abstract:
  This short technical paper advocates a bootstrapping algorithm from which we
can form a statistically reliable opinion based on limited clinically observed
data, regarding whether an osteo-hyperplasia could actually be a case of
Ewing's osteosarcoma. The basic premise underlying our methodology is that a
primary bone tumour, if it is indeed Erwing's osteosarcoma, cannot increase in
volume beyond some critical limit without showing metastasis. We propose a
statistical method to extrapolate such critical limit to primary tumour volume.
Our model does not involve any physiological variables but rather is entirely
based on time series observations of increase in primary tumour volume from the
point of initial detection to the actual detection of metastases.


title:
Design of HIV-1-PR inhibitors which do not create resistance: blocking
  the folding of single monomers

abstract:
  One of the main problems of drug design is that of optimizing the
drug--target interaction. In the case in which the target is a viral protein
displaying a high mutation rate, a second problem arises, namely the eventual
development of resistance. We wish to suggest a scheme for the design of
non--conventional drugs which do not face any of these problems and apply it to
the case of HIV--1 protease. It is based on the knowledge that the folding of
single--domain proteins, like e.g. each of the monomers forming the HIV--1--PR
homodimer, is controlled by local elementary structures (LES), stabilized by
local contacts among hydrophobic, strongly interacting and highly conserved
amino acids which play a central role in the folding process. Because LES have
evolved over myriads of generations to recognize and strongly interact with
each other so as to make the protein fold fast as well as to avoid aggregation
with other proteins, highly specific (and thus little toxic) as well as
effective folding--inhibitor drugs suggest themselves: short peptides (or
eventually their mimetic molecules), displaying the same amino acid sequence of
that of LES (p--LES). Aside from being specific and efficient, these inhibitors
are expected not to induce resistance: in fact, mutations which successfully
avoid their action imply the destabilization of one or more LES and thus should
lead to protein denaturation. Making use of Monte Carlo simulations within the
framework of a simple although not oversimplified model, which is able to
reproduce the main thermodynamic as well as dynamic properties of monoglobular
proteins, we first identify the LES of the HIV--1--PR and then show that the
corresponding p--LES peptides act as effective inhibitors of the folding of the
protease which do not create resistance.


title:
Mimivirus Gene Promoters Exhibit an Unprecedented Conservation among all
  Eukaryotes

abstract:
  The initial analysis of the recently sequenced genome of Acanthamoeba
polyphaga Mimivirus, the largest known double-stranded DNA virus, predicted a
proteome of size and complexity more akin to small parasitic bacteria than to
other nucleo-cytoplasmic large DNA viruses, and identified numerous functions
never before described in a virus. It has been proposed that the Mimivirus
lineage could have emerged before the individualization of cellular organisms
from the 3 domains of life. An exhaustive in silico analysis of the non-coding
moiety of all known viral genomes, now uncovers the unprecedented perfect
conservation of a AAAATTGA motif in close to 50% of the Mimivirus genes. This
motif preferentially occurs in genes transcribed from the predicted leading
strand and is associated with functions required early in the viral infectious
cycle, such as transcription and protein translation. A comparison with the
known promoter of unicellular eukaryotes, in particular amoebal protists,
strongly suggests that the AAAATTGA motif is the structural equivalent of the
TATA box core promoter element. This element is specific to the Mimivirus
lineage, and may correspond to an ancestral promoter structure predating the
radiation of the eukaryotic kingdoms. This unprecedented conservation of core
promoter regions is another exceptional features of Mimivirus, that again
raises the question of its evolutionary origin.


title: PCA and K-Means decipher genome

abstract:
  In this paper, we aim to give a tutorial for undergraduate students studying
statistical methods and/or bioinformatics. The students will learn how data
visualization can help in genomic sequence analysis. Students start with a
fragment of genetic text of a bacterial genome and analyze its structure. By
means of principal component analysis they ``discover'' that the information in
the genome is encoded by non-overlapping triplets. Next, they learn how to find
gene positions. This exercise on PCA and K-Means clustering enables active
study of the basic bioinformatics notions. Appendix 1 contains program listings
that go along with this exercise. Appendix 2 includes 2D PCA plots of triplet
usage in moving frame for a series of bacterial genomes from GC-poor to GC-rich
ones. Animated 3D PCA plots are attached as separate gif files. Topology
(cluster structure) and geometry (mutual positions of clusters) of these plots
depends clearly on GC-content.


title: Mimivirus Relatives in the Sargasso Sea

abstract:
  The discovery and genome analysis of Acanthamoeba polyphaga Mimivirus, the
largest known DNA virus, challenged much of the accepted dogma regarding
viruses. Its particle size (>400 nm), genome length (1.2 million bp) and huge
gene repertoire (911 protein coding genes) all contribute to blur the
established boundaries between viruses and the smallest parasitic cellular
organisms. Phylogenetic analyses also suggested that the Mimivirus lineage
could have emerged prior to the individualization of cellular organisms from
the three established domains, triggering a debate that can only be resolved by
generating and analyzing more data. The next step is then to seek some evidence
that Mimivirus is not the only representative of its kind and determine where
to look for new Mimiviridae. An exhaustive similarity search of all Mimivirus
predicted proteins against all publicly available sequences identified many of
their closest homologues among the Sargasso Sea environmental sequences.
Subsequent phylogenetic analyses suggested that unknown large viruses
evolutionarily closer to Mimivirus than to any presently characterized species
exist in abundance in the Sargasso Sea. Their isolation and genome sequencing
could prove invaluable in understanding the origin and diversity of large DNA
viruses, and shed some light on the role they eventually played in the
emergence of eukaryotes.


title:
Evidence of a universal power law characterizing the evolution of
  metabolic networks

abstract:
  Metabolic networks are known to be scale free but the evolutionary origin of
this structural property is not clearly understood. One way of studying the
dynamical process is to compare the metabolic networks of species that have
arisen at different points in evolution and hence are related to each other to
varying extents. We have compared the reaction sets of each metabolite across
and within 15 groups of species. For a given pair of species and a given
metabolite, the number $\Delta k$ of reactions of the metabolite that appear in
the metabolic network of only one species and not the other is a measure of the
distance between the two networks. While $\Delta k$ is small within groups of
related species and large across groups, we find its probability distribution
to be $\sim (\Delta k)^{-\gamma'}$ where $\gamma'$ is a universal exponent that
is the same within and across groups. This exponent equals, upto statistical
uncertainties, the exponent $\gamma$ in the scale free degree distribution
$\sim k^{-\gamma}$. We argue that this, as well as our finding that $\Delta k$
is approximately linearly correlated with the degree $k$ of the metabolite, is
evidence of a `proportionate change' process in evolution. We also discuss some
molecular mechanisms that might be responsible for such an evolutionary
process.


title:
On Recursive Production and Evolvabilty of Cells: Catalytic Reaction
  Network Approach

abstract:
  To unveil the logic of cell from a level of chemical reaction dynamics, we
need to clarify how ensemble of chemicals can autonomously produce the set of
chemical, without assuming a specific external control echanism. A cell
consists of a huge number of chemical species that catalyze each other. Often
the number of each molecule species is not so large, and accordingly the number
fluctuations in each molecule speciescan be large. In the amidst of such
diversity and large fluctuations, how can a cell make recursive production? On
the other hand, a cell can change its state to evolve to a different type over
a longer time span. How are reproduction and evolution compatible? We address
these questions, based on several model studies with catalytic reaction
network. In the present survey paper, we first formulate basic questions on the
recursiveness and evolvability of a cell, and then state the standpoint of our
research to answer the questions, that is termed as 'constructive biology'.
Based on this standpoint, we present general strategy of modeling a cell as a
chemical reaction network.

categories: q-bio.MN cond-mat.stat-mech nlin.AO physics.bio-ph q-bio.CB


title:
Min-oscillations in Escherichia coli induced by interactions of
  membrane-bound proteins

abstract:
  During division it is of primary importance for a cell to correctly determine
the site of cleavage. The bacterium Escherichia coli divides in the center,
producing two daughter cells of equal size. Selection of the center as the
correct division site is in part achieved by the Min-proteins. They oscillate
between the two cell poles and thereby prevent division at these locations.
Here, a phenomenological description for these oscillations is presented, where
lateral interactions between proteins on the cell membrane play a key role.
Solutions to the dynamic equations are compared to experimental findings. In
particular, the temporal period of the oscillations is measured as a function
of the cell length and found to be compatible with the theoretical prediction.


title: Neutral Theory and Relative Species Abundance in Ecology

abstract:
  The theory of island biogeography[1] asserts that an island or a local
community approaches an equilibrium species richness as a result of the
interplay between the immigration of species from the much larger metacommunity
source area and local extinction of species on the island (local community).
Hubbell[2] generalized this neutral theory to explore the expected steady-state
distribution of relative species abundance (RSA) in the local community under
restricted immigration. Here we present a theoretical framework for the unified
neutral theory of biodiversity[2] and an analytical solution for the
distribution of the RSA both in the metacommunity (Fisher's logseries) and in
the local community, where there are fewer rare species. Rare species are more
extinction-prone, and once they go locally extinct, they take longer to
re-immigrate than do common species. Contrary to recent assertions[3], we show
that the analytical solution provides a better fit, with fewer free parameters,
to the RSA distribution of tree species on Barro Colorado Island (BCI)[4] than
the lognormal distribution[5,6].


title: Scaling properties of the Penna model

abstract:
  We investigate the scaling properties of the Penna model, which has become a
popular tool for the study of population dynamics and evolutionary problems in
recent years. We find that the model generates a normalised age distribution
for which a simple scaling rule is proposed, that is able to reproduce
qualitative features for all genome sizes.


title:
Evolutionary ecology in-silico: Does mathematical modelling help in
  understanding the "generic" trends?

abstract:
  Motivated by the results of recent laboratory experiments (Yoshida et al.
Nature, 424, 303-306 (2003)) as well as many earlier field observations that
evolutionary changes can take place in ecosystems over relatively short
ecological time scales, several ``unified'' mathematical models of evolutionary
ecology have been developed over the last few years with the aim of describing
the statistical properties of data related to the evolution of ecosystems.
Moreover, because of the availability of sufficiently fast computers, it has
become possible to carry out detailed computer simulations of these models. For
the sake of completeness and to put these recent developments in the proper
perspective, we begin with a brief summary of some older models of ecological
phenomena and evolutionary processes. However, the main aim of this article is
to review critically these ``unified'' models, particularly those published in
the physics literature, in simple language that makes the new theories
accessible to wider audience.


title:
Sharp gene pool transition in a population affected by phenotype-based
  selective hunting

abstract:
  We use a microscopic model of population dynamics, a modified version of the
well known Penna model, to study some aspects of microevolution. This research
is motivated by recent reports on the effect of selective hunting on the gene
pool of bighorn sheep living in the Ram Mountain region, in Canada. Our model
finds a sharp transition in the structure of the gene pool as some threshold
for the number of animals hunted is reached.


title: Density-Dependence as a Size-Independent Regulatory Mechanism

abstract:
  The growth function of populations is central in biomathematics. The main
dogma is the existence of density dependence mechanisms, which can be modelled
with distinct functional forms that depend on the size of the population. One
important class of regulatory functions is the $\theta$-logistic, which
generalises the logistic equation. Using this model as a motivation, this paper
introduces a simple dynamical reformulation that generalises many growth
functions. The reformulation consists of two equations, one for population
size, and one for the growth rate. Furthermore, the model shows that although
population is density-dependent, the dynamics of the growth rate does not
depend either on population size, nor on the carrying capacity. Actually, the
growth equation is uncoupled from the population size equation, and the model
has only two parameters, a Malthusian parameter $\rho$ and a competition
coefficient $\theta$. Distinct sign combinations of these parameters reproduce
not only the family of $\theta$-logistics, but also the van Bertalanffy,
Gompertz and Potential Growth equations, among other possibilities. It is also
shown that, except for two critical points, there is a general size-scaling
relation that includes those appearing in the most important allometric
theories, including the recently proposed Metabolic Theory of Ecology. With
this model, several issues of general interest are discussed such as the growth
of animal population, extinctions, cell growth and allometry, and the effect of
environment over a population.


title: On Myosin II dynamics in the presence of external loads

abstract:
  We address the controversial hot question concerning the validity of the
loose coupling versus the lever-arm theories in the actomyosin dynamics by
re-interpreting and extending the phenomenological washboard potential model
proposed by some of us in a previous paper. In this new model a Brownian motion
harnessing thermal energy is assumed to co-exist with the deterministic swing
of the lever-arm, to yield an excellent fit of the set of data obtained by some
of us on the sliding of Myosin II heads on immobilized actin filaments under
various load conditions. Our theoretical arguments are complemented by accurate
numerical simulations, and the robustness of the model is tested via different
choices of parameters and potential profiles.