title: Physical origins of protein superfamilies

abstract:
  In this work, we discovered a fundamental connection between selection for
protein stability and emergence of preferred structures of proteins. Using
standard exact 3-dimensional lattice model we evolve sequences starting from
random ones and determining exact native structure after each mutation.
Acceptance of mutations is biased to select for stable proteins. We found that
certain structures, wonderfold, are independently discovered numerous times as
native states of stable proteins in many unrelated runs of selection. Diversity
of sequences that fold into wonderfold structures gives rise to superfamilies,
i.e. sets of dissimilar sequences that fold into the same or very similar
structures. Wonderfolds appear to be the most designable structures out of
complete set of compact lattice proteins. Furthermore, proteins having
wondefolds as their native structure tend to be most thermostable among all
evolved proteins. This effect is purely due to the favorable geometric
properties of wonderfolds and, thus, dominates any dependence on sequences. The
present work establishes a model of prebiotic structure selection, which
identifies dominant structural patterns emerging upon optimization of proteins
for survival in hot environment. Convergently discovered prebiotic initial
superfamilies with wonderfold structures could have served as a seed for
subsequent biological evolution involving gene duplications and divergence.


title:
Expanding the Temporal Analysis in Single-Molecule Switching Experiments
  Through the Auto-Correlation Function: Mathematical Framework

abstract:
  A method is presented that, when used in conjunction with single molecule
experimental techniques, allows for the extraction of rates and mechanical
properties of a biomolecule undergoing transitions between mechanically
distinct states. This analysis enables the exploration of systems where the
lifetimes of survival are of order of the intrinsic time constant of the
experimental apparatus; permitting the study of kinetic events whose transition
rates are an order of magnitude (or two) larger than those that can be studied
with traditional averaging methods. Using current experimental techniques, this
allows for the study of biomolecules whose lifetime of survival in a given
state are as low as milliseconds down to microseconds. The relevant observable
is the auto-correlation function of the experimental probe that is attached to
the biomolecule of interest. General solutions are expressed in terms of a
series. Closed form solutions are found for two physically opposing limits:
where transitions between the mechanically distinct states of the biomolecule
occur on either much faster or much slower time scales than those governing the
motion of the experimental probe. Motivated by the derivation of these opposing
bounds, two series solutions for the general case are then presented. We
present an error analysis for truncating each series at arbitrary order and
obtain a range of parameters for which this method could be applicable to the
study of the two state biomolecular problem. Finally, both series (up to third
order) are expressed for the two state problem when the system obeys Markov
statistics. These solutions should be amiable to the analysis of experimental
data, expanding temporal analysis of data from single molecule experiments.


title:
A Modified Iterative IOM Approach for Optimization of Biochemical
  Systems

abstract:
  The presented previously indirect optimization method (IOM) developed within
biochemical systems theory (BST) provides a versatile and mathematically
tractable optimization strategy for biochemical systems. However, due to the
local approximations nature of the BST formalism, the iterative version of this
technique possibly does not yield the true optimum solution. In this work, an
algorithm is proposed to obtain the correct and consistent optimum steady-state
operating point of biochemical systems. The existing linear optimization
problem of the direct IOM approach is modified by adding an equality constraint
of describing the consistency of solutions between the S-system and the
original model. Lagrangian analysis is employed to derive the first order
necessary optimality conditions for the above modified optimization problem.
This leads to a procedure that may be regarded as a modified iterative IOM
approach in which the optimization objective function includes an extra linear
term. The extra term contains a comparison of metabolite concentration
derivatives with respect to the enzyme activities between the S-system and the
original model and ensures that the new algorithm is still carried out within
linear programming techniques. The presented framework is applied to several
biochemical systems and shown to the tractability and effectiveness of the
method. The simulation is also studied to investigate the convergence
properties of the algorithm and to give a performance comparison of standard
and modified iterative IOM approach.


title:
Stimulus-invariant processing and spectrotemporal reverse correlation in
  primary auditory cortex

abstract:
  The spectrotemporal receptive field (STRF) provides a versatile and
integrated, spectral and temporal, functional characterization of single cells
in primary auditory cortex (AI). In this paper, we explore the origin of, and
relationship between, different ways of measuring and analyzing an STRF. We
demonstrate that STRFs measured using a spectrotemporally diverse array of
broadband stimuli -- such as dynamic ripples, spectrotemporally white noise,
and temporally orthogonal ripple combinations (TORCs) -- are very similar,
confirming earlier findings that the STRF is a robust linear descriptor of the
cell. We also present a new deterministic analysis framework that employs the
Fourier series to describe the spectrotemporal modulations contained in the
stimuli and responses. Additional insights into the STRF measurements,
including the nature and interpretation of measurement errors, is presented
using the Fourier transform, coupled to singular-value decomposition (SVD), and
variability analyses including bootstrap. The results promote the utility of
the STRF as a core functional descriptor of neurons in AI.


title:
Identifying Biomagnetic Sources in the Brain by the Maximum Entropy
  Approach

abstract:
  Magnetoencephalographic (MEG) measurements record magnetic fields generated
from neurons while information is being processed in the brain. The inverse
problem of identifying sources of biomagnetic fields and deducing their
intensities from MEG measurements is ill-posed when the number of field
detectors is far less than the number of sources. This problem is less severe
if there is already a reasonable prior knowledge in the form of a distribution
in the intensity of source activation. In this case the problem of identifying
and deducing source intensities may be transformed to one of using the MEG data
to update a prior distribution to a posterior distribution. Here we report on
some work done using the maximum entropy method (ME) as an updating tool.
Specifically, we propose an implementation of the ME method in cases when the
prior contain almost no knowledge of source activation. Two examples are
studied, in which part of motor cortex is activated with uniform and varying
intensities, respectively.


title:
How to formulate membrane potential in a spatially homogeneous myocyte
  model?

abstract:
  Membrane potential in a mathematical model of a cardiac myocyte can be
formulated in different ways. Assuming a spatially homogeneous myocyte that is
strictly charge-conservative and electroneutral as a whole, two methods will be
compared: (1) the differential formulation dV/dt=-I/C_m of membrane potential
used traditionally; and (2) the capacitor formulation, where membrane potential
is defined algebraically by the capacitor equation V=Q/C_m. We examine the
relationship between the formulations, assumptions under which each formulation
is consistent, and show that the capacitor formulation provides a transparent,
physically realistic formulation of membrane potential, whereas use of the
differential formulation may introduce unintended and undesirable behavior,
such as monotonic drift of concentrations. We prove that the drift of
concentrations in the differential formulation arises as a compensation for
failure to assign all currents in concentrations. As an example of these
considerations, we present an electroneutral, explicitly charge-conservative
formulation of Winslow et al. model (1999), and extend it to describe membrane
potentials between intracellular compartments.


title: The Topology of Pseudoknotted Homopolymers

abstract:
  We consider the folding of a self-avoiding homopolymer on a lattice, with
saturating hydrogen bond interactions. Our goal is to numerically evaluate the
statistical distribution of the topological genus of pseudoknotted
configurations. The genus has been recently proposed for classifying
pseudoknots (and their topological complexity) in the context of RNA folding.
We compare our results on the distribution of the genus of pseudoknots, with
the theoretical predictions of an existing combinatorial model for an
infinitely flexible and stretchable homopolymer. We thus obtain that steric and
geometric constraints considerably limit the topological complexity of
pseudoknotted configurations, as it occurs for instance in real RNA molecules.
We also analyze the scaling properties at large homopolymer length, and the
genus distributions above and below the critical temperature between the
swollen phase and the compact-globule phase, both in two and three dimensions.


title:
Fluctuations and Correlations in Lattice Models for Predator-Prey
  Interaction

abstract:
  Including spatial structure and stochastic noise invalidates the classical
Lotka-Volterra picture of stable regular population cycles emerging in models
for predator-prey interactions. Growth-limiting terms for the prey induce a
continuous extinction threshold for the predator population whose critical
properties are in the directed percolation universality class. Here, we discuss
the robustness of this scenario by considering an ecologically inspired
stochastic lattice predator-prey model variant where the predation process
includes next-nearest-neighbor interactions. We find that the corresponding
stochastic model reproduces the above scenario in dimensions 1< d \leq 4, in
contrast with mean-field theory which predicts a first-order phase transition.
However, the mean-field features are recovered upon allowing for
nearest-neighbor particle exchange processes, provided these are sufficiently
fast.

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


title: Should you believe that this coin is fair?

abstract:
  Faced with a sequence of N binary events, such as coin flips (or Ising
spins), it is natural to ask whether these events reflect some underlying
dynamic signals or are just random. Plausible models for the dynamics of hidden
biases lead to surprisingly high probabilities of misidentifying random
sequences as biased. In particular, this probability decays as N^(-1/4), so
that no reasonable amount of data would be sufficient to induce the concept of
a fair coin with high probability. I suggest that these theoretical results may
be relevant to understanding experiments on the apparent misperception of
random sequences by human observers.


title: Exact Solution of the Multi-Allelic Diffusion Model

abstract:
  We give an exact solution to the Kolmogorov equation describing genetic drift
for an arbitrary number of alleles at a given locus. This is achieved by
finding a change of variable which makes the equation separable, and therefore
reduces the problem with an arbitrary number of alleles to the solution of a
set of equations that are essentially no more complicated than that found in
the two-allele case. The same change of variable also renders the Kolmogorov
equation with the effect of mutations added separable, as long as the mutation
matrix has equal entries in each row. Thus this case can also be solved exactly
for an arbitrary number of alleles. The general solution, which is in the form
of a probability distribution, is in agreement with the previously known
results--which were for the cases of two and three alleles only. Results are
also given for a wide range of other quantities of interest, such as the
probabilities of extinction of various numbers of alleles, mean times to these
extinctions, and the means and variances of the allele frequencies. To aid
dissemination, these results are presented in two stages: first of all they are
given without derivations and too much mathematical detail, and then
subsequently derivations and a more technical discussion are provided.


title:
A simple physical model for scaling in protein-protein interaction
  networks

abstract:
  It has recently been demonstrated that many biological networks exhibit a
scale-free topology where the probability of observing a node with a certain
number of edges (k) follows a power law: i.e. p(k) ~ k^-g. This observation has
been reproduced by evolutionary models. Here we consider the network of
protein-protein interactions and demonstrate that two published independent
measurements of these interactions produce graphs that are only weakly
correlated with one another despite their strikingly similar topology. We then
propose a physical model based on the fundamental principle that (de)solvation
is a major physical factor in protein-protein interactions. This model
reproduces not only the scale-free nature of such graphs but also a number of
higher-order correlations in these networks. A key support of the model is
provided by the discovery of a significant correlation between number of
interactions made by a protein and the fraction of hydrophobic residues on its
surface. The model presented in this paper represents the first physical model
for experimentally determined protein-protein interactions that comprehensively
reproduces the topological features of interaction networks. These results have
profound implications for understanding not only protein-protein interactions
but also other types of scale-free networks.


title: Quasispecies can exist under neutral drift at finite population sizes

abstract:
  We investigate the evolutionary dynamics of a finite population of RNA
sequences adapting to a neutral fitness landscape. Despite the lack of
differential fitness between viable sequences, we observe typical properties of
adaptive evolution, such as increase of mean fitness over time and punctuated
equilibrium transitions. We discuss the implications of these results for
understanding evolution at high mutation rates, and extend the relevance of the
quasispecies concept to finite populations and time scales. Our results imply
that the quasispecies concept and neutral drift are not complementary concepts,
and that the relative importance of each is determined by a combination of
population size and mutation rate.


title: Equation of state of looped DNA

abstract:
  We calculate the equation of state of DNA under tension for the case that the
DNA features loops. Such loops occur transiently during DNA condensation in the
presence of multivalent ions or sliding cationic protein linkers. The
force-extension relation of such looped DNA modelled as a wormlike chain is
calculated via path integration in the semiclassical limit. This allows us to
determine rigorously the high stretching asymptotics. Notably the functional
form of the force-extension curve resembles that of straight DNA, yet with a
strongly renormalized apparent persistence length. That means that the
experimentally extracted single molecule elasticity does not necessarily
reflect the bare DNA stiffness only, but can also contain additional
contributions that depend on the overall chain conformation and length.


title:
How Noise and Coupling Induce Bursting Action Potentials in Pancreatic
  beta-cells

abstract:
  Unlike isolated beta-cells, which usually produce continuous spikes or fast
and irregular bursts, electrically coupled beta-cells are apt to exhibit robust
bursting action potentials. We consider the noise induced by thermal
fluctuations as well as that by channel gating stochasticity and examine its
effects on the action potential behavior of the beta-cell model. It is observed
numerically that such noise in general helps single cells to produce a variety
of electrical activities. In addition, we also probe coupling via gap junctions
between neighboring cells,with heterogeneity induced by noise, to find that it
enhances regular bursts.


title: Networks of Mobile Elements for Biological Systems

abstract:
  In this paper we present a network model to study the impact of spatial
distribution of constituents, coupling between them and diffusive processes in
the context of biological situations. The model is in terms of network of
mobile elements whose internal dynamics is given by differential equations
exhibiting switching and/or oscillatory behaviour. To make the model more
consistent with the underlying biological phenomena we incorporate properties
like growth and decay into the network.
  We characterise this network by calculating the usual network measures like
network efficiency, entropy growth, vertex degree distribution, geodesic
lengths, centrality as well as fractal dimensions and generalised entropy. It
is seen that the model can demonstrate the features of both scale free networks
as well as small worlds network in different parameter domains. The formation
of spatio-temporal patterns is another feature of such networks which makes
them appealing for understanding broad qualitative aspects of problems like
cell differentiation and synchronization. The response of the network to
various attack strategies(isolated and multiple) is also studied.


title:
Modeling viral coevolution: HIV multi-clonal persistence and competition
  dynamics

abstract:
  The coexistence of different viral strains (quasispecies) within the same
host are nowadays observed for a growing number of viruses, most notably HIV,
Marburg and Ebola, but the conditions for the formation and survival of new
strains have not yet been understood. We present a model of HIV quasispecies
competition, that describes the conditions of viral quasispecies coexistence
under different immune system conditions. Our model incorporates both T and B
cells responses, and we show that the role of B cells is important and additive
to that of T cells. Simulations of coinfection (simultaneous infection) and
superinfection (delayed secondary infection) scenarios in the early stages
(days) and in the late stages of the infection (years) are in agreement with
emerging molecular biology findings. The immune response induces a competition
among similar phenotypes, leading to differentiation (quasi-speciation), escape
dynamics and complex oscillations of viral strain abundance. We found that the
quasispecies dynamics after superinfection or coinfection has time scales of
several months and becomes even slower when the immune system response is weak.
Our model represents a general framework to study the speed and distribution of
HIV quasispecies during disease progression, vaccination and therapy.


title: High resolution protein folding with a transferable potential

abstract:
  A generalized computational method for folding proteins with a fully
transferable potential and geometrically realistic all-atom model is presented
and tested on seven different helix bundle proteins. The protocol, which
includes graph-theoretical analysis of the ensemble of resulting folded
conformations, was systematically applied and consistently produced structure
predictions of approximately 3 Angstroms without any knowledge of the native
state. To measure and understand the significance of the results, extensive
control simulations were conducted. Graph theoretic analysis provides a means
for systematically identifying the native fold and provides physical insight,
conceptually linking the results to modern theoretical views of protein
folding. In addition to presenting a method for prediction of structure and
folding mechanism, our model suggests that a accurate all-atom amino acid
representation coupled with a physically reasonable atomic interaction
potential (that does not require optimization to the test set) and hydrogen
bonding are essential features for a realistic protein model.


title: Fixation of strategies for an evolutionary game in finite populations

abstract:
  A stochastic evolutionary dynamics of two strategies given by 2 x 2 matrix
games is studied in finite populations. We focus on stochastic properties of
fixation: how a strategy represented by a single individual wins over the
entire population. The process is discussed in the framework of a random walk
with arbitrary hopping rates. The time of fixation is found to be identical for
both strategies in any particular game. The asymptotic behavior of the fixation
time and fixation probabilities in the large population size limit is also
discussed. We show that fixation is fast when there is at least one pure
evolutionary stable strategy (ESS) in the infinite population size limit, while
fixation is slow when the ESS is the coexistence of the two strategies.


title:
Modeling the dynamics of inhomogeneous natural rotifer populations under
  toxicant exposure

abstract:
  Most population models assume that individuals within a given population are
identical, that is, the fundamental role of variation is ignored. Here we
develop a general approach to modeling heterogeneous populations with discrete
evolutionary time step. The theory is applied to population dynamics of natural
rotifer populations. We show that under particular conditions the behavior of
the inhomogeneous model possesses complex transition regimes, which depends
both on the mean and the variance of the initial parameter distribution and the
final state of the population depends on the least possible value from the
domain of the parameter. The question of persistence of the population is
discussed.


title: Mathematical modeling of evolution of horizontally transferred genes

abstract:
  We describe a stochastic birth-and-death model of evolution of horizontally
transferred genes in microbial populations. The model is a generalization of
the stochastic model described by Berg and Kurland and includes five
parameters: the rate of mutational inactivation, selection coefficient,
immigration rate (i.e., rate of arrival of a novel sequence from outside of the
recipient population), within-population horizontal transmission rate, and
population size. The model of Berg and Kurland included four parameters,
namely, mutational inactivation, selection coefficient, population size, and
transmission rate. However, the effect of transmission was disregarded in the
interpretation of the results, and the overall conclusion was that horizontally
acquired sequences can be fixed in a population only when they confer a
substantial selective advantage onto the recipient and therefore are subject to
strong positive selection. By contrast, analysis of the present model in
different domains of parameter values shows that, as long as the rate of
within-population horizontal transmission is comparable to the mutational
inactivation rate and there is even a low rate of immigration, horizontally
acquired sequences can be fixed in the population or at least persist for a
long time even when they are neutral or slightly deleterious. The available
biological data strongly suggest that intense within-population and even
between-populations gene flows are realistic for at least some prokaryotic
species and environments. Therefore our modeling results are compatible with
the notion of a pivotal role of horizontal gene transfer in the evolution of
prokaryotes.


title: Freely forming groups: Trying to be rare

abstract:
  A simple weakly frequency dependent model for the dynamics of a population
with a finite number of types is proposed, based upon an advantage of being
rare. In the infinite population limit, this model gives rise to a non-smooth
dynamical system that reaches its globally stable equilibrium in finite time.
This dynamical system is sufficiently simple to permit an explicit solution,
built piecewise from solutions of the logistic equation in continuous time. It
displays an interesting tree-like structure of coalescing components.


title:
Pure competition of multiple species during mixed-substrate microbial
  growth: Extending the resource-based theory

abstract:
  The simultaneous growth of multiple microbial species is a problem of
fundamental ecological interest. In media containing more than one
growth-limiting substrate, multiple species can coexist. The question then
arises: Can single-species data predict the existence and stability of
mixed-culture steady states in mixed-substrate environments? This question has
been extensively studied with the help of resource-based models. These studies
have shown that the single-species data required to predict mixed-culture
behavior consists of the growth isoclines and consumption vectors, which in
turn are determined from single-substrate data by making specific assumptions
about the kinetics of mixed-substrate growth. Here, we show that these
assumptions are not valid for microbial growth on mixtures of substitutable
substrates. However, the theory can be developed by determining the growth
isoclines and consumption vectors directly from the mixed-substrate data, thus
obviating the need for specific assumptions about the kinetics of
mixed-substrate growth. We show furthermore that in addition to the growth
isoclines and consumption vectors, the single-species, mixed-substrate data
yields a new family of curves, which we call the consumption curves.
Consideration of the growth isoclines and the consumption curves yields deeper
insights into the behavior of the mixed cultures. It yields a priori bounds on
the substrate concentrations achieved during coexistence, permits the extension
of the theory to systems in which the growth isoclines are non-monotonic, and
clarifies earlier results obtained by considering only the growth isoclines.


title:
Identification of the growth-limiting step in continuous cultures from
  initial rates measured in response to substrate-excess conditions

abstract:
  When steady state chemostat cultures are abruptly exposed to substrate-excess
conditions, they exhibit long lags before adjusting to the new environment. The
identity of the rate-limiting step for this slow response can be inferred from
the initial yields and specific growth rates measured by exposing steady state
cultures at various dilution rates to substrate-excess conditions. We measured
these parameters for glucose-limited cultures of E. coli ML308 growing at
various dilution rates between 0.03 and 0.6 1/hr. In all the cases, the initial
yields were 20-30% less than the steady state yields. The decline of the yield
implies that overflow metabolism is triggered in response to excess glucose. It
is therefore unlikely that the initial response of the cells is limited by
substrate uptake. The initial specific growth rates of cultures growing at low
dilution rates (D = 0.03, 0.05, 0.075, 0.1, 0.3 1/hr) were significantly higher
than the steady state specific growth rates. However, the increment in the
specific growth rate decreased with the dilution rate, and at D=0.6 1/hr, there
was no improvement in the specific growth rate. The initial specific growth
rates varied hyperbolically with the dilution, decreasing sharply at dilution
rates below 0.1 1/hr and saturating at D=0.6 1/hr. This is consistent with a
picture in which the initial response is limited by the activity of glutamate
dehydrogenase.


title:
Fermentation kinetics including product and substrate inhibitions plus
  biomass death: a mathematical analysis

abstract:
  Fermentation is generally modelled by kinetic equations giving the time
evolutions for biomass, substrate, and product concentrations. Although these
equations can be solved analytically in simple cases if substrate/product
inhibition and biomass death are included, they are typically solved
numerically. We propose an analytical treatment of the kinetic equations
--including cell death and an arbitrary number of inhibitions-- in which
constant yield needs not be assumed. Equations are solved in phase space, i.e.
the biomass concentration is written explicitly as a function of the substrate
concentration.


title: An intermediate phase in DNA melting

abstract:
  We predict a novel temperature-driven phase transition of DNA below the
melting transition. The additional, intermediate phase exists for repetitive
sequences, when the two strands have different lengths. In this phase, the
excess bases of the longer strand are completely absorbed as bulge loops inside
the helical region. When the temperature is lowered, the excess bases desorb
into overhanging ends, resulting in a contour length change. This continuous
transition is in many aspects analogous to Bose Einstein condensation. Weak
sequence disorder renders the transition discontinuous.


title: Signal processing in the TGF-beta superfamily ligand-receptor network

abstract:
  The TGF-beta pathway plays a central role in tissue homeostasis and
morphogenesis. It transduces a variety of extracellular signals into
intracellular transcriptional responses that control a plethora of cellular
processes, including cell growth, apoptosis, and differentiation. We use
computational modeling to show that coupling of signaling with receptor
trafficking results in a highly versatile signal-processing unit, able to sense
by itself absolute levels of ligand, temporal changes in ligand concentration,
and ratios of multiple ligands. This coupling controls whether the response of
the receptor module is transient or permanent and whether or not different
signaling channels behave independently of each other. Our computational
approach unifies seemingly disparate experimental observations and suggests
specific changes in receptor trafficking patterns that can lead to phenotypes
that favor tumor progression.

categories: q-bio.MN nlin.AO physics.bio-ph q-bio.SC


title: Spiky oscillations in NF-kB signalling

abstract:
  The NF-kB signalling system is involved in a variety of cellular processes
including immune response, inflammation, and apoptosis. Recent experiments have
found oscillations in the nuclear-cytoplasmic translocation of the NF-kB
transcription factor. How the cell uses the oscillations to differentiate input
conditions and send specific signals to downstream genes is an open problem. We
shed light on this issue by examining the small core network driving the
oscillations, which, we show, is designed to produce periodic spikes in nuclear
NF-kB concentration. The oscillations can be used to regulate downstream genes
in a variety of ways. In particular, we show that genes to whose operator sites
NF-kB binds and dissociates fast can respond very sensitively to changes in the
input signal, with effective Hill coefficients in excess of 20.


title:
A Hydrophobic Gate in an Ion Channel: The Closed State of the Nicotinic
  Acetylcholine Receptor

abstract:
  The nicotinic acetylcholine receptor (nAChR) is the prototypic member of the
`Cys-loop' superfamily of ligand-gated ion channels which mediate synaptic
neurotransmission, and whose other members include receptors for glycine,
gamma-aminobutyric acid, and serotonin. Cryo-electron microscopy has yielded a
three dimensional structure of the nAChR in its closed state. However, the
exact nature and location of the channel gate remains uncertain. Although the
transmembrane pore is constricted close to its center, it is not completely
occluded. Rather, the pore has a central hydrophobic zone of radius about 3 A.
Model calculations suggest that such a constriction may form a hydrophobic
gate, preventing movement of ions through a channel. We present a detailed and
quantitative simulation study of the hydrophobic gating model of the nicotinic
receptor, in order to fully evaluate this hypothesis. We demonstrate that the
hydrophobic constriction of the nAChR pore indeed forms a closed gate.
Potential of mean force (PMF) calculations reveal that the constriction
presents a barrier of height ca. 10 kT to the permeation of sodium ions,
placing an upper bound on the closed channel conductance of 0.3 pS. Thus, a 3 A
radius hydrophobic pore can form a functional barrier to the permeation of a 1
A radius Na+ ion. Using a united atom force field for the protein instead of an
all atom one retains the qualitative features but results in differing
conductances, showing that the PMF is sensitive to the detailed molecular
interactions.


title: A folding inhibitor of the HIV-1 Protease

abstract:
  Being the HIV-1 Protease (HIV-1-PR) an essential enzyme in the viral life
cycle, its inhibition can control AIDS. The folding of single domain proteins,
like each of the monomers forming the HIV-1-PR homodimer, is controlled by
local elementary structures (LES, folding units stabilized by strongly
interacting, highly conserved, as a rule hydrophobic, amino acids). These LES
have evolved over myriad of generations to recognize and strongly attract each
other, so as to make the protein fold fast and be stable in its native
conformation. Consequently, peptides displaying a sequence identical to those
segments of the monomers associated with LES are expected to act as competitive
inhibitors and thus destabilize the native structure of the enzyme. These
inhibitors are unlikely to lead to escape mutants as they bind to the protease
monomers through highly conserved amino acids which play an essential role in
the folding process. The properties of one of the most promising inhibitors of
the folding of the HIV-1-PR monomers found among these peptides is demonstrated
with the help of spectrophotometric assays and CD spectroscopy.


title: Functional modes of proteins are among the most robust ones

abstract:
  It is shown that a small subset of modes which are likely to be involved in
protein functional motions of large amplitude can be determined by retaining
the most robust normal modes obtained using different protein models. This
result should prove helpful in the context of several applications proposed
recently, like for solving difficult molecular replacement problems or for
fitting atomic structures into low-resolution electron density maps. Moreover,
it may also pave the way for the development of methods allowing to predict
such motions accurately.


title:
A Cognitive Model of an Epistemic Community: Mapping the Dynamics of
  Shallow Lake Ecosystems

abstract:
  We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake
ecosystem model by augmenting the individual cognitive maps drawn by 8
scientists working in the area of shallow lake ecology. We calculated graph
theoretical indices of the individual cognitive maps and the collective
cognitive map produced by augmentation. The graph theoretical indices revealed
internal cycles showing non-linear dynamics in the shallow lake ecosystem. The
ecological processes were organized democratically without a top-down
hierarchical structure. The steady state condition of the generic model was a
characteristic turbid shallow lake ecosystem since there were no dynamic
environmental changes that could cause shifts between a turbid and a clearwater
state, and the generic model indicated that only a dynamic disturbance regime
could maintain the clearwater state. The model developed herein captured the
empirical behavior of shallow lakes, and contained the basic model of the
Alternative Stable States Theory. In addition, our model expanded the basic
model by quantifying the relative effects of connections and by extending it.
In our expanded model we ran 4 simulations: harvesting submerged plants,
nutrient reduction, fish removal without nutrient reduction, and
biomanipulation. Only biomanipulation, which included fish removal and nutrient
reduction, had the potential to shift the turbid state into clearwater state.
The structure and relationships in the generic model as well as the outcomes of
the management simulations were supported by actual field studies in shallow
lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to
understand the complex structure of shallow lake ecosystems as a whole and
obtain a valid generic model based on tacit knowledge of experts in the field.


title:
Cyclic Fluctuations, Climatic Changes and Role of Noise in Planktonic
  Foraminifera in the Mediterranean Sea

abstract:
  The study of Planktonic Foraminifera abundances permits to obtain climatic
curves on the basis of percentage ratio between tropical and temperate/polar
forms. Climatic changes were controlled by several phenomena as: (i)
Milankovitch's cycles, produced by variations of astronomical parameters such
as precession, obliquity and eccentricity; (ii) continental geodynamic
evolution and orogenic belt; (iii) variations of atmospheric and oceanic
currents; (iv) volcanic eruptions; (v) meteor impacts. But while astronomical
parameters have a quasi-regular periodicity, the other phenomena can be
considered as "noise signal" in natural systems. The interplay between cyclical
astronomical variations, the "noise signal" and the intrinsic nonlinearity of
the ecologic system produces strong glacial or interglacial period according to
the stochastic resonance phenomenon.


title: In silicio stretching of chromatin

abstract:
  We present Monte-Carlo (MC) simulations of the stretching of a single 30 nm
chromatin fiber. The model approximates the DNA by a flexible polymer chain
with Debye-H\"uckel electrostatics and uses a two-angle zig-zag model for the
geometry of the linker DNA connecting the nucleosomes. The latter are
represented by flat disks interacting via an attractive Gay-Berne potential.
Our results show that the stiffness of the chromatin fiber strongly depends on
the linker DNA length. Furthermore, changing the twisting angle between
nucleosomes from 90 deg to 130 deg increases the stiffness significantly. An
increase in the opening angle from 22 deg to 34 deg leads to softer fibers for
small linker lengths. We observe that fibers containing a linker histone at
each nucleosome are stiffer compared to those without the linker histone. The
simulated persistence lengths and elastic moduli agree with experimental data.
Finally, we show that the chromatin fiber does not behave as an isotropic
elastic rod, but its rigidity depends on the direction of deformation:
chromatin is much more resistant to stretching than to bending.


title: Weighted and unweighted network of amino acids within protein

abstract:
  The information regarding the structure of a single protein is encoded in the
network of interacting amino acids. Considering each protein as a weighted and
unweighted network of amino acids we have analyzed a total of forty nine
protein structures that covers the three branches of life on earth. Our results
show that the probability degree distribution of network connectivity follows
Poisson's distribution; whereas the probability strength distribution does not
follow any known distribution. However, the average strength of amino acid node
depends on its degree (k). For some of the proteins, the strength of a node
increases linearly with k. On the other hand, for a set of other proteins,
although the strength increases linaerly with k for smaller values of k, we
have not obtained any clear functional relationship of strength with degree at
higher values of k. The results also show that the weight of the amino acid
nodes belonging to the highly connected nodes tend to have a higher value. The
result that the average clustering coefficient of weighted network is less than
that of unweighted network implies that the topological clustering is generated
by edges with low weights. The ratio of average clustering coefficients of
protein network to that of the corresponding classical random network varies
linearly with the number (N) of amino acids of a protein; whereas the ratio of
characteristic path lengths varies logarithmically with N. The power law
behaviour of clustering coefficients of weighted and unweighted network as a
function of degree k indicates that the network has a signature of hierarchical
network. It has also been observed that the network is of assortative type.


title: Embedded transfer RNA Genes

abstract:
  In euryarchaeal methanogen M.kandleri and in Nanoarchaea N. equitans some of
the missing tRNA genes are embedded in others. We argue from bioinformatic
evidence that position specific intron splicing is the key behind co-location
of these tRNA genes.


title:
Universality of Long-Range Correlations in Expansion-Randomization
  Systems

abstract:
  We study the stochastic dynamics of sequences evolving by single site
mutations, segmental duplications, deletions, and random insertions. These
processes are relevant for the evolution of genomic DNA. They define a
universality class of non-equilibrium 1D expansion-randomization systems with
generic stationary long-range correlations in a regime of growing sequence
length. We obtain explicitly the two-point correlation function of the sequence
composition and the distribution function of the composition bias in sequences
of finite length. The characteristic exponent $\chi$ of these quantities is
determined by the ratio of two effective rates, which are explicitly calculated
for several specific sequence evolution dynamics of the universality class.
Depending on the value of $\chi$, we find two different scaling regimes, which
are distinguished by the detectability of the initial composition bias. All
analytic results are accurately verified by numerical simulations. We also
discuss the non-stationary build-up and decay of correlations, as well as more
complex evolutionary scenarios, where the rates of the processes vary in time.
Our findings provide a possible example for the emergence of universality in
molecular biology.


title:
Stimulus - response curves of a neuronal model for noisy subthreshold
  oscillations and related spike generation

abstract:
  We investigate the stimulus-dependent tuning properties of a noisy ionic
conductance model for intrinsic subthreshold oscillations in membrane potential
and associated spike generation. On depolarization by an applied current, the
model exhibits subthreshold oscillatory activity with occasional spike
generation when oscillations reach the spike threshold. We consider how the
amount of applied current, the noise intensity, variation of maximum
conductance values and scaling to different temperature ranges alter the
responses of the model with respect to voltage traces, interspike intervals and
their statistics and the mean spike frequency curves. We demonstrate that
subthreshold oscillatory neurons in the presence of noise can sensitively and
also selectively be tuned by stimulus-dependent variation of model parameters.


title: Glucose metabolism and oscillatory behavior of pancreatic islets

abstract:
  A variety of oscillations are observed in pancreatic islets.We establish a
model, incorporating two oscillatory systems of different time scales: One is
the well-known bursting model in pancreatic beta-cells and the other is the
glucose-insulin feedback model which considers direct and indirect feedback of
secreted insulin. These two are coupled to interact with each other in the
combined model, and two basic assumptions are made on the basis of biological
observations: The conductance g_{K(ATP)} for the ATP-dependent potassium
current is a decreasing function of the glucose concentration whereas the
insulin secretion rate is given by a function of the intracellular calcium
concentration. Obtained via extensive numerical simulations are complex
oscillations including clusters of bursts, slow and fast calcium oscillations,
and so on. We also consider how the intracellular glucose concentration depends
upon the extracellular glucose concentration, and examine the inhibitory
effects of insulin.


title:
Domesticated P elements in the Drosophila montium species subgroup have
  a new function related to a DNA binding property

abstract:
  Molecular domestication of a transposable element is defined as its
functional recruitment by the host genome. To date, two independent events of
molecular domestication of the P transposable element have been described: in
the Drosophila obscura species group and in the Drosophila montium species
subgroup. These P neogenes consist to stationary, non repeated sequences,
potentially encoding 66 kDa repressor-like proteins (RLs). Here we investigate
the function of the montium P neogenes. We provide evidence for the presence of
RLs proteins in two montium species (D. tsacasi and D. bocqueti) specifically
expressed in adult and larval brain and gonads. We tested the hypothesis that
the montium P neogenes function is related to the repression of the
transposition of distant related mobile P elements which coexist in the genome.
Our results strongly suggest that the montium P neogenes are not recruited to
down regulate the P element transposition. Given that all the proteins encoded
by mobile or stationary P homologous sequences show a strong conservation of
the DNA Binding Domain, we tested the capacity of the RLs proteins to bind DNA
in vivo. Immunstaining of polytene chromosomes in D. melanogaster transgenic
lines strongly suggest that montium P neogenes encode proteins that bind DNA in
vivo. RLs proteins show multiple binding to the chromosomes. We suggest that
the property recruited in the case of the montium P neoproteins is their DNA
binding property. The possible functions of these neogenes are discussed.


title: Population genetics of translational robustness

abstract:
  Recent work has shown that expression level is the main predictor of a
gene’s evolutionary rate, and that more highly expressed genes evolve
slower. A possible explanation for this observation is selection for proteins
which fold properly despite mistranslation, in short selection for
translational robustness. Translational robustness leads to the somewhat
paradoxical prediction that highly expressed genes are extremely tolerant to
missense substitutions but nevertheless evolve very slowly. Here, we study a
simple theoretical model of translational robustness that allows us to gain
analytic insight into how this paradoxical behavior arises.


title:
Speciational view of macroevolution: are micro and macroevolution
  decoupled?

abstract:
  We introduce a simple computational model that, with a microscopic dynamics
driven by natural selection and mutation alone, allows the description of true
speciation events. A statistical analysis of the so generated evolutionary tree
captures realistic features showing power laws for frequency distributions in
time and size. Albeit these successful predictions, the difficulty in obtaining
punctuated dynamics with mass extinctions suggests the necessity of decoupling
micro and macro-evolutionary mechanisms in agreement with some ideas of Gould's
and Eldredge's theory of punctuated equilibrium.


title: The genetic signature of (astronomically induced) life extinctions

abstract:
  The current understanding of supernova and gamma-ray burst events suggests
important effects on the biosphere if one of more of them happened to strike
the earth in the past. In this paper we evaluate the possibility that life
extinctions which probably occurred due to excess of radiation occurring in the
geologic past might have left a genetic signature on surviving species. We
emphasize the signatures of these extinctions, proposing a quantitative model
to evaluate the surviving probability of the species, based on kinetic aspects
of the frequency of mutations and the DNA repair rate.


title:
Age-Associated Disorders As A Proxy Measure Of Biological Age: Findings
  From the NLTCS Data

abstract:
  Background: The relative contribution of different aging-associated processes
to the age phenotype may differ among individuals, creating variability in
aging manifestations among age-peers. Capturing this variability can
significantly advance understanding the aging and mortality. An index of
age-associated health disorders (deficits), called a "frailty index" (FI),
appears to be a promising characteristic of such processes. In this study we
address the connections of the FI with age focusing on disabled individuals who
might be at excessive risk of frailty. Methods: The National Long Term Care
Survey (NLTCS) assessed health and functioning of the U.S. elderly in 1982,
1984, 1989, 1994, and 1999. Detailed information for our sample was assessed
from about 26,700 interviews. The individual FI is defined as a proportion of
deficits for a given person. We perform cross-sectional empirical analysis of
the FI age-patterns. Results: FI in the NLTCS exhibits accelerated (quadratic)
increase with age. Deficits might accumulate faster among the elderly who, at
younger ages, had a low mean FI ("healthy" group) than a high FI ("disabled"
group). Age-patterns for "healthy" and "disabled" groups converge at advanced
ages. The rate of deficit accumulation is sex-sensitive. Convergence of the
(sex-specific) FI for "healthy" and "disabled" groups in later ages determines
biological age limits, associated with given levels of health-maintenance in
the society, which correspond to 109.4 years for females and 92.5 years for
males. Conclusions: The FI can be employed as a measure of biological age and
population heterogeneity for modeling aging processes and mortality in elderly
individuals.


title: Analytic approach to the evolutionary effects of genetic exchange

abstract:
  We present an approximate analytic study of our previously introduced model
of evolution including the effects of genetic exchange. This model is motivated
by the process of bacterial transformation. We solve for the velocity, the rate
of increase of fitness, as a function of the fixed population size, $N$. We
find the velocity increases with $\ln N$, eventually saturated at an $N$ which
depends on the strength of the recombination process. The analytical treatment
is seen to agree well with direct numerical simulations of our model equations.


title:
Collective synchronization in populations of globally coupled phase
  oscillators with drifting frequencies

abstract:
  We generalize the Kuramoto model for coupled phase oscillators by allowing
the frequencies to drift in time according to Ornstein-Uhlenbeck dynamics. Such
drifting frequencies were recently measured in cellular populations of
circadian oscillator and inspired our work. Linear stability analysis of the
Fokker-Planck equation for an infinite population is amenable to exact solution
and we show that the incoherent state is unstable passed a critical coupling
strength $K_c(\ga, \sigf)$, where $\ga$ is the inverse characteristic drifting
time and $\sigf$ the asymptotic frequency dispersion. Expectedly $K_c$ agrees
with the noisy Kuramoto model in the large $\ga$ (Schmolukowski) limit but
increases slower as $\ga$ decreases. Asymptotic expansion of the solution for
$\ga\to 0$ shows that the noiseless Kuramoto model with Gaussian frequency
distribution is recovered in that limit. Thus varying a single parameter allows
to interpolate smoothly between two regimes: one dominated by the frequency
dispersion and the other by phase diffusion.


title:
A probabilistic model for gene content evolution with duplication, loss,
  and horizontal transfer

abstract:
  We introduce a Markov model for the evolution of a gene family along a
phylogeny. The model includes parameters for the rates of horizontal gene
transfer, gene duplication, and gene loss, in addition to branch lengths in the
phylogeny. The likelihood for the changes in the size of a gene family across
different organisms can be calculated in O(N+hM^2) time and O(N+M^2) space,
where N is the number of organisms, $h$ is the height of the phylogeny, and M
is the sum of family sizes. We apply the model to the evolution of gene content
in Preoteobacteria using the gene families in the COG (Clusters of Orthologous
Groups) database.


title:
Frailty Index as a Major Indicator of Aging Processes and Mortality in
  Elderly: Results From Analyses of the National Long Term Care Survey Data

abstract:
  To better understand mortality change with age capturing the variability in
individuals' rates of aging, we performed comprehensive analysis of statistical
properties of a cumulative index of age-associated disorders (deficits), called
a "frailty index" (FI). This index is calculated as the proportion of the
health deficits in an individual. It is found, first, that frequency,
time-to-death, mortality-rate, and relative-risk-of-death exhibit remarkably
similar FI- and age- patterns. Second, the FI, on the one hand, and mortality
rate and relative risk, on the other hand, also exhibit similar age patterns
with accelerated increase up to oldest-old ages and with subsequent
deceleration and even decline. Third, distribution of the FI with time-to-death
is sharper than that of age with time-to-death. These and related findings
support the conclusion that the FI can describe aging processes and population
heterogeneity. We also discuss the ability of the FI to capture physiological
processes underlying aging both on individual and population levels.


title:
The response of amino acid frequencies to directional mutation pressure
  in mitochondrial genome sequences is related to the physical properties of
  the amino acids and to the structure of the genetic code

abstract:
  The frequencies of A, C, G and T in mitochondrial DNA vary among species due
to unequal rates of mutation between the bases. The frequencies of bases at
four-fold degenerate sites respond directly to mutation pressure. At 1st and
2nd positions, selection reduces the degree of frequency variation. Using a
simple evolutionary model, we show that 1st position sites are less constrained
by selection than 2nd position sites, and therefore that the frequencies of
bases at 1st position are more responsive to mutation pressure than those at
2nd position. We define a similarity measure between amino acids that is a
function of 8 measured physical properties. We define a proximity measure for
each amino acid, which is the average similarity between an amino acid and all
others that are accessible via single point mutations in the genetic code. We
also define a responsiveness for each amino acid, which measures how rapidly an
amino acid frequency changes as a result of mutation pressure acting on the
base frequencies. There is a strong correlation between responsiveness and
proximity, and both these quantities are also correlated with the mutability of
amino acids estimated from the mtREV substitution rate matrix. We also consider
the variation of base frequencies between strands and between genes on a
strand. These trends are consistent with the patterns expected from analysis of
the variation among genomes


title:
Algorithmic and Complexity Results for Decompositions of Biological
  Networks into Monotone Subsystems

abstract:
  A useful approach to the mathematical analysis of large-scale biological
networks is based upon their decompositions into monotone dynamical systems.
This paper deals with two computational problems associated to finding
decompositions which are optimal in an appropriate sense. In graph-theoretic
language, the problems can be recast in terms of maximal sign-consistent
subgraphs. The theoretical results include polynomial-time approximation
algorithms as well as constant-ratio inapproximability results. One of the
algorithms, which has a worst-case guarantee of 87.9 percent from optimality,
is based on the semidefinite programming relaxation approach of
Goemans-Williamson. The algorithm was implemented and tested on a Drosophila
segmentation network and an Epidermal Growth Factor Receptor pathway model, and
it was found to perform close to optimally.


title: Sexual replication in the quasispecies model

abstract:
  This paper develops a simplified model for sexual replication within the
quasispecies formalism. We assume that the genomes of the replicating organisms
are two-chromosomed and diploid, and that the fitness is determined by the
number of chromosomes that are identical to a given master sequence. We also
assume that there is a cost to sexual replication, given by a characteristic
time $ \tau_{seek} $ during which haploid cells seek out a mate with which to
recombine. If the mating strategy is such that only viable haploids can mate,
then when $ \tau_{seek} = 0 $, it is possible to show that sexual replication
will always outcompete asexual replication. However, as $ \tau_{seek} $
increases, sexual replication only becomes advantageous at progressively higher
mutation rates. Once the time cost for sex reaches a critical threshold, the
selective advantage for sexual replication disappears entirely. The results of
this paper suggest that sexual replication is not advantageous in small
populations per se, but rather in populations with low replication rates. In
this regime, the cost for sex is sufficiently low that the selective advantage
obtained through recombination leads to the dominance of the strategy. In fact,
at a given replication rate and for a fixed environment volume, sexual
replication is selected for in high populations because of the reduced time
spent finding a reproductive partner.


title: Comparative analysis of some models of mixed-substrate microbial growth

abstract:
  Mixed-substrate microbial growth is among the most intensely studied systems
in molecular microbiology. Several mathematical models have been developed to
account for the genetic regulation of such systems, especially those resulting
in diauxic growth. In this work, we compare the dynamics of three such models
(Narang, Biotech. Bioeng., 59, 116, 1998; Thattai & Shraiman, Biophys. J, 85,
744, 2003; Brandt et al, Water Research, 38, 1004, 2004). We show that these
models are dynamically similar - the initial motion of the inducible enzymes in
all the models is described by Lotka-Volterra equations for competing species.
The dynamic similarity occurs because in all the models, the inducible enzymes
possess properties characteristic of competing species: Their synthesis is
autocatalytic, and they inhibit each other. Despite this dynamic similarity,
the models vary with respect to the range of dynamics captured. The Brandt et
al model captures only the diauxic growth pattern, whereas the remaining two
models capture both diauxic and non-diauxic growth patterns. The models also
differ with respect to the mechanisms that generate the mutual inhibition
between the enzymes. In the Narang model, the mutual inhibition occurs because
the enzymes for each substrate enhance the dilution of the enzymes for the
other substrate. In the Thattai & Shraiman model, the mutual inhibition is
entirely due to competition for the phosphoryl groups.


title:
Statistical Indicators of Collective Behavior and Functional Clusters in
  Gene Networks of Yeast

abstract:
  We analyze gene expression time-series data of yeast S. cerevisiae measured
along two full cell-cycles. We quantify these data by using q-exponentials,
gene expression ranking and a temporal mean-variance analysis. We construct
gene interaction networks based on correlation coefficients and study the
formation of the corresponding giant components and minimum spanning trees. By
coloring genes according to their cell function we find functional clusters in
the correlation networks and functional branches in the associated trees. Our
results suggest that a percolation point of functional clusters can be
identified on these gene expression correlation networks.


title: Epidemics in small world networks

abstract:
  For many infectious diseases, a small-world network on an underlying regular
lattice is a suitable simplified model for the contact structure of the host
population. It is well known that the contact network, described in this
setting by a single parameter, the small-world parameter $p$, plays an
important role both in the short term and in the long term dynamics of epidemic
spread. We have studied the effect of the network structure on models of immune
for life diseases and found that in addition to the reduction of the effective
transmission rate, through the screening of infectives, spatial correlations
may strongly enhance the stochastic fluctuations. As a consequence, time series
of unforced Susceptible-Exposed-Infected-Recovered (SEIR) models provide
patterns of recurrent epidemics with realistic amplitudes, suggesting that
these models together with complex networks of contacts are the key ingredients
to describe the prevaccination dynamical patterns of diseases such as measles
and pertussis. We have also studied the role of the host contact strucuture in
pathogen antigenic variation, through its effect on the final outcome of an
invasion by a viral strain of a population where a very similar virus is
endemic. Similar viral strains are modelled by the same infection and
reinfection parameters, and by a given degree of cross immunity that represents
the antigenic distance between the competing strains. We have found, somewhat
surprisingly, that clustering on the network decreases the potential to sustain
pathogen diversity.


title: Implications of Aging in Bacteria

abstract:
  Motivated by recent research of aging in E. coli, we explore the effects of
aging on bacterial fitness. The disposable soma theory of aging was developed
to explain how differences in lifespans and aging rates could be linked to life
history trade-offs. Although generally applied for multicellular organisms, it
is also useful for exploring life history strategies of single celled organisms
such as bacteria. Starting from the Euler-Lotka equation, we propose a
mathematical model to explore how a finite lifespan effects fitness of
bacteria. We find that that there is surprisingly little loss of fitness when
the bacterium has limited opportunities to reproduce. Instead, the fitness
gained each time the bacteria reproduces decreases rapidly, and investing
resources to survive to reproduce the first few times is likely more
advantageous than investing additional resources to try to maintain cell
integrity longer.


title: A p53 Oscillator Model of DNA Break Repair Control

abstract:
  The transcription factor p53 is an important regulator of cell fate.
Mutations in p53 gene are associated with many cancers. In response to signals
such as DNA damage, p53 controls the transcription of a series of genes that
cause cell cycle arrest during which DNA damage is repaired, or triggers
programmed cell death that eliminates possibly cancerous cells wherein DNA
damage might have remained unrepaired. Previous experiments showed oscillations
in p53 level in response to DNA damage, but the mechanism of oscillation
remained unclear. Here we examine a model where the concentrations of p53
isoforms are regulated by Mdm22, Arf, Siah, and beta-catenin. The extent of DNA
damage is signalled through the switch-like activity of a DNA damage sensor,
the DNA-dependent protein kinase Atm. This switch is responsible for initiating
and terminating oscillations in p53 concentration. The strength of the DNA
damage signal modulates the number of oscillatory waves of p53 and Mdm22 but
not the frequency or amplitude of oscillations{a result that recapitulates
experimental findings. A critical fnding was that the phosphorylated form of
Nbs11, a member of the DNA break repair complex Mre11-Rad50-Nbs11 (MRN), must
augment the activity of Atm kinase. While there is in vitro support for this
assumption, this activity appears essential for p53 dynamics. The model
provides several predictions concerning, among others, degradation of the
phosphorylated form of p53, the rate of DNA repair as a function of DNA damage,
the sensitivity of p53 oscillation to transcription rates of SIAH, beta-CATENIN
and ARF, and the hysteretic behavior of active Atm kinase levels with respect
to the DNA damage signal


title: Control of neural chaos by synaptic noise

abstract:
  We studied neural automata -or neurobiologically inspired cellular automata-
which exhibits chaotic itinerancy among the different stored patterns or
memories. This is a consequence of activity-dependent synaptic fluctuations,
which continuously destabilize the attractor and induce irregular hopping to
other possible attractors. The nature of the resulting irregularity depends on
the dynamic details, namely, on the intensity of the synaptic noise and on the
number of sites of the network that are synchronously updated at each time
step. Varying these details, different regimes occur from regular to chaotic.
In the absence of external agents, the chaotic behavior may turn regular after
tuning the noise intensity. It is argued that a similar mechanism might be at
the origin of the self-control of chaos in natural systems.


title:
The simplest model of spatially distributed population with reasonable
  migration of organisms

abstract:
  The simplest model of a smart spatial redistribution of individuals is
proposed. A single-species population is considered, to be composed of two
discrete subpopulations inhabiting two stations; migration is a transfer
between them. The migration is not random and yields the maximization of net
reproduction, with respect to the transaction costs. The organisms are supposed
to be globally informed. Discrete time model is studied, since it shows all the
features of a smart migrations, while the continuous time case brings no new
knowledge but the technical problems. Some properties of the model are studied
and discussed.


title: Pair Approximation Models for Disease Spread

abstract:
  We consider a Susceptible-Infective-Recovered (SIR) model, where the
mechanism for the renewal of susceptibles is demographic, on a ring with next
nearest neighbour interactions, and a family of correlated pair approximations
(CPA), parametrized by a measure of the relative contributions of loops and
open triplets of the sites involved in the infection process. We have found
that the phase diagram of the CPA, at fixed coordination number, changes
qualitatively as the relative weight of the loops increases, from the phase
diagram of the uncorrelated pair approximation to phase diagrams typical of
one-dimensional systems. In addition, we have performed computer simulations of
the same model and shown that while the CPA with a constant correlation
parameter cannot describe the global behaviour of the model, a reasonable
description of the endemic equilibria as well as of the phase diagram may be
obtained by allowing the parameter to depend on the demographic rate.


title: Protein crystallization in vivo

abstract:
  Protein crystallization in vivo provides some fascinating examples of
biological self-assembly. Here, we provide a selective survey to show the
diversity of functions for which protein crystals are used, and the physical
properties of the crystals thatare exploited. Where known, we emphasize how the
nature of the protein-protein interactions leads to control of the
crystallization behaviour.


title: The fitness value of information

abstract:
  Biologists measure information in different ways. Neurobiologists and
researchers in bioinformatics often measure information using
information-theoretic measures such as Shannon's entropy or mutual information.
Behavioral biologists and evolutionary ecologists more commonly use
decision-theoretic measures, such the value of information, which assess the
worth of information to a decision maker. Here we show that these two kinds of
measures are intimately related in the context of biological evolution. We
present a simple model of evolution in an uncertain environment, and calculate
the increase in Darwinian fitness that is made possible by information about
the environmental state. This fitness increase -- the fitness value of
information -- is a composite of both Shannon's mutual information and the
decision-theoretic value of information. Furthermore, we show that in certain
cases the fitness value of responding to a cue is exactly equal to the mutual
information between the cue and the environment. In general the Shannon entropy
of the environment, which seemingly fails to take anything about organismal
fitness into account, nonetheless imposes an upper bound on the fitness value
of information.


title:
The Tangled nature model with inheritance and constraint: Evolutionary
  ecology restricted by a conserved resource

abstract:
  We study a version of the Tangled Nature model of evolutionary ecology
redefined in a phenotype space where mutants have properties correlated to
their parents. The model has individual-based dynamics whilst incorporating
species scale competitive constraints and a system scale resource constraint.
Multiple species arise that coexist in a species interaction network with
evolving global properties. Both the mean interaction strength and the network
connectance increase relative to the null system as mutualism becomes more
extensive. From a study of the dependence of average degree on the resource
level we extract the diversity-connectance relationship which conforms to the
hyperbolic form seen in field data. This is adjudged to arise as a consequence
of the evolutionary pressure to achieve positive interactions. The network
degree distributions conform more strongly to exponential than to the null
binomial distributions in all cases. This effect is believed to be caused by
correlations in the reproductive process. We also study how resource
availability influences the phenotypical lifetime distribution which is
approximately of power law form. We observe that the mean lifetime is inversely
related to the resource level.


title: Network growth models and genetic regulatory networks

abstract:
  We study a class of growth algorithms for directed graphs that are candidate
models for the evolution of genetic regulatory networks. The algorithms involve
partial duplication of nodes and their links, together with innovation of new
links, allowing for the possibility that input and output links from a newly
created node may have different probabilities of survival. We find some
counterintuitive trends as parameters are varied, including the broadening of
indegree distribution when the probability for retaining input links is
decreased. We also find that both the scaling of transcription factors with
genome size and the measured degree distributions for genes in yeast can be
reproduced by the growth algorithm if and only if a special seed is used to
initiate the process.


title: Role of transport performance on neuron cell morphology

abstract:
  The compartmental model is a basic tool for studying signal propagation in
neurons, and, if the model parameters are adequately defined, it can also be of
help in the study of electrical or fluid transport. Here we show that the input
resistance, in different networks which simulate the passive properties of
neurons, is the result of an interplay between the relevant conductances,
morphology and size. These results suggest that neurons must grow in such a way
that facilitates the current flow. We propose that power consumption is an
important factor by which neurons attain their final morphological appearance.


abstract:
  A new formalism for calculation of the partition function of single stranded
nucleic acids is presented. Secondary structures and the topology of structure
elements are the level of resolution that is used. The folding model deals with
matches, mismatches, symmetric and asymmetric interior loops, stacked pairs in
loop and dangling end regions, multi-branched loops, bulges and single base
stacking that might exist at duplex ends or at the ends of helices.
Calculations on short and long sequences show, that for short oligonucleotides,
a duplex formation often displays a two-state transition. However, for longer
oligonucleotides, the thermodynamic properties of the single self-folding
transition affects the transition nature of the duplex formation, resulting in
a population of intermediate hairpin species in the solution. The role of
intermediate hairpin species is analyzed in the case when a short
oligonucleotides (molecular beacons) have to reliably identify and hybridize to
accessible nucleotides within their targeted mRNA sequences. It is shown that
the enhanced specificity of the molecular beacons is a result of their
constrained conformational flexibility and the all-or-none mechanism of their
hybridization to the target sequence.


title: Gene Copy Number and Cell Cycle Arrest

abstract:
  The cell cycle is an orderly sequence of events which ultimately lead to the
division of a single cell into two daughter cells. In the case of DNA damage by
radiation or chemicals, the damage checkpoints in the $G_{1}$ and $G_{2}$
phases of the cell cycle are activated. This results in an arrest of the cell
cycle so that the DNA damage can be repaired. Once this is done, the cell
continues with its usual cycle of activity. We study a mathematical model of
the DNA damage checkpoint in the $G_{2}$ phase which arrests the transition
from the $G_{2}$ to the $M$ (mitotic) phase of the cell cycle. The tumor
suppressor protein p53 plays a key role in activating the pathways leading to
cell cycle arrest in mammalian systems. If the DNA damage is severe, the p53
proteins activate other pathways which bring about apoptosis, i.e., programmed
cell death. Loss of the p53 gene results in the proliferation of cells
containing damaged DNA, i.e., in the growth of tumors which may ultimately
become cancerous. There is some recent experimental evidence which suggests
that the mutation of a single copy of the p53 gene (in the normal cell each
gene has two identical copies) is sufficient to trigger the formation of
tumors. We study the effect of reducing the gene copy number of the p53 and two
other genes on cell cycle arrest and obtain results consistent with
experimental observations.


title: The protein map of Synechococcus sp. PCC 7942 - the first overlook

abstract:
  The unicellular cyanobacterium Synechococcus PCC 7942 has been used as a
model organism for studies of prokaryotic circadian rhythms,
carbon-concentrating mechanisms, response to a variety of nutrient and
environmental stresses, and cell division. This paper presents the results of
the first proteomic exploratory study of Synechococcus PCC 7942. The proteome
was analyzed using two-dimensional gel electrophoresis followed by MALDI-TOF
mass spectroscopy, and database searching. Of 140 analyzed protein spots, 110
were successfully identified as 62 different proteins, many of which occurred
as multiple spots on the gel. The identified proteins were organized into 18
different functional categories reflecting the major metabolic and cellular
processes occurring in the cyanobacterial cells in the exponential growth
phase. Among the identified proteins, 14 previously unknown or considered to be
hypothetical are here shown to be true gene products in Synechococcus sp. PCC
7942, and may be helpful for annotation of the newly sequenced genome.


title: Predictive Models for Characterization of Ecological Data

abstract:
  Although ARTMAP and ART-based models were introduced in early 70's they were
not used in characterizing and classifying ecological observations. ART-based
models have been extensively used for classification models based on satellite
imagery. This report, to our knowledge, is the first application of ART-based
methods and specifically ARTMAP for predicting habitat selection and spatial
distribution of species. We compare the performance of ARTMAP to assess the
breeding success of three bird species (Lanius senator, Hippolais pallida, and
Calandrella brachydactyla) based on multi-spectral satellite imagery and
environmental variables. ARTMAP is superior both in terms of performance
(percent correctly classified - pcc = 1.00) and generalizability (pcc >0.96) to
those of feedforward multilayer backpropogation (>0.87, >0.65), linear and
quadratic discriminant analysis (>0.48, >0.46) and k-nearest neighbor (>0.82,
>0.66) methods. Compared to other methods, ARTMAP is able to incorporate new
observations with far less computational effort and can easily add data to
already trained models.


title:
Participatory Ecosystem Management Planning at Tuzla Lake (Turkey) Using
  Fuzzy Cognitive Mapping

abstract:
  A participatory environmental management plan was prepared for Tuzla Lake,
Turkey. Fuzzy cognitive mapping approach was used to obtain stakeholder views
and desires. Cognitive maps were prepared with 44 stakeholders (villagers,
local decisionmakers, government and non-government organization (NGO)
officials). Graph theory indices, statistical methods and "What-if" simulations
were used in the analysis. The most mentioned variables were livelihood,
agriculture and animal husbandry. The most central variable was agriculture for
local people (villagers and local decisionmakers) and education for NGO &
Government officials. All the stakeholders agreed that livelihood was increased
by agriculture and animal husbandry while hunting decreased birds and wildlife.
Although local people focused on their livelihoods, NGO & Government officials
focused on conservation of Tuzla Lake and education of local people.
Stakeholders indicated that the conservation status of Tuzla Lake should be
strengthened to conserve the ecosystem and biodiversity, which may be
negatively impacted by agriculture and irrigation. Stakeholders mentioned salt
extraction, ecotourism, and carpet weaving as alternative economic activities.
Cognitive mapping provided an effective tool for the inclusion of the
stakeholders' views and ensured initial participation in environmental planning
and policy making.


title:
Generalizability of Artificial Neural Network Models in Ecological
  Applications: Predicting Nest Occurrence and Breeding Success of the
  Red-winged Blackbird Agelaius phoeniceus

abstract:
  Separate artificial neural network (ANN) models were developed from data in
two geographical regions and years apart for a marsh-nesting bird, the
red-winged blackbird Agelaius phoeniceus. Each model was independently tested
on the spatially and temporally distinct data from the other region to
determine how generalizable it was. The first model was developed to predict
occurrence of nests in two wetlands on Lake Erie, Ohio in 1995 and 1996. The
second model was developed to predict breeding success in two marshes in
Connecticut, USA in 1969 and 1970. Independent variables were vegetation
durability, stem density, stem/nest height, distance to open water, distance to
edge, and water depth. With input variable relevances, sensitivity analyses and
neural interpretation diagrams we were able to understand how the different
models predicted nest occurrence and breeding success and compare their
differences and similarities. Both models also predicted increasing nest
occurrence/breeding success with increasing water depth under the nest and
increasing distance to edge. However, relationships for prediction differed in
the models. Generalizability of the models was poor except when the marshes had
similar values of important variables in the model. ANN models performed better
than generalized linear models (GLM) on marshes with similar structures.
Generalizability of the models did not differ in nest occurrence and breeding
success data. Extensive testing also showed that the GLMs were not necessarily
more generalizable than ANNs, suggesting that ANN models make good definitions
of a study system but are too specific to generalize well to other ecologically
complex systems unless input variable distributions are very similar.


title:
Methodological Issues in Building, Training, and Testing Artificial
  Neural Networks

abstract:
  We review the use of artificial neural networks, particularly the feedforward
multilayer perceptron with back-propagation for training (MLP), in ecological
modelling. Overtraining on data or giving vague references to how it was
avoided is the major problem. Various methods can be used to determine when to
stop training in artificial neural networks: 1) early stopping based on
cross-validation, 2) stopping after a analyst defined error is reached or after
the error levels off, 3) use of a test data set. We do not recommend the third
method as the test data set is then not independent of model development. Many
studies used the testing data to optimize the model and training. Although this
method may give the best model for that set of data it does not give
generalizability or improve understanding of the study system. The importance
of an independent data set cannot be overemphasized as we found dramatic
differences in model accuracy assessed with prediction accuracy on the training
data set, as estimated with bootstrapping, and from use of an independent data
set. The comparison of the artificial neural network with a general linear
model (GLM) as a standard procedure is recommended because a GLM may perform as
well or better than the MLP. MLP models should not be treated as black box
models but instead techniques such as sensitivity analyses, input variable
relevances, neural interpretation diagrams, randomization tests, and partial
derivatives should be used to make the model more transparent, and further our
ecological understanding which is an important goal of the modelling process.
Based on our experience we discuss how to build a MLP model and how to optimize
the parameters and architecture.


title: A Model Analyzing Life Cycle of Periodical Cicadas

abstract:
  This paper focuses on a mathematical model interpreting the prime number life
cycle of periodical cicadas.Changed the viewpoint to predators rather than the
prey,this model fits reality very well by utilizing some principles and
assumption.With the definition of the predator income,natural selection from
predators seems to be the main reason for such a long life cycle.Consequent
solution of this model is exactly the fact of real nature.


title: Species Numbers versus Area in Chowdhury Ecosystems

abstract:
  For a fixed number of food levels on a lattice, the Chowdhury model for
ecosystem is simulated and found to give a number of different species which
approaches exponentially a plateau if the considered area is increased.


title: $C_{E}PT$ Symmetry of the Simple Ecological Dynamical Equations

abstract:
  It is shown that all simple ecological, i.e. population dynamical equations
(unlimited exponential population growth (or decrease) dynamics, logistic or
Verhulst equation, usual and generalized Lotka-Volterra equations) hold a
symmetry, called $C_{E}PT$ symmetry. Namely, all simple ecological dynamical
equations are invariant (symmetric) in respect to successive application of the
time reversal transformation - $T$, space coordinates reversal or parity
transformation - $P$, and predator-prey reversal transformation - $C_{E}$ that
changes preys in the predators or pure (healthy) in the impure (fatal)
environment, and vice versa. It is deeply conceptually analogous to remarkable
$CPT$ symmetry of the fundamental physical dynamical equations. Further, it is
shown that by more accurate, "microscopic" analysis, given $C_{E}PT$ symmetry
becomes explicitly broken.


title:
Non-extensive Trends in the Size Distribution of Coding and Non-coding
  DNA Sequences in the Human Genome

abstract:
  We study the primary DNA structure of four of the most completely sequenced
human chromosomes (including chromosome 19 which is the most dense in coding),
using Non-extensive Statistics. We show that the exponents governing the decay
of the coding size distributions vary between $5.2 \le r \le 5.7$ for the short
scales and $1.45 \le q \le 1.50$ for the large scales. On the contrary, the
exponents governing the decay of the non-coding size distributions in these
four chromosomes, take the values $2.4 \le r \le 3.2$ for the short scales and
$1.50 \le q \le 1.72$ for the large scales. This quantitative difference, in
particular in the tail exponent $q$, indicates that the non-coding (coding)
size distributions have long (short) range correlations. This non-trivial
difference in the DNA statistics is attributed to the non-conservative
(conservative) evolution dynamics acting on the non-coding (coding) DNA
sequences.


title: Content based network model with duplication and divergence

abstract:
  We construct a minimal content-based realization of the duplication and
divergence model of genomic networks introduced by Wagner [A. Wagner, Proc.
Natl. Acad. Sci. {\bf 91}, 4387 (1994)] and investigate the scaling properties
of the directed degree distribution and clustering coefficient. We find that
the content based network exhibits crossover between two scaling regimes, with
log-periodic oscillations for large degrees. These features are not present in
the original gene duplication model, but inherent in the content based model of
Balcan and Erzan. The scaling exponents $\gamma_1$ and $\gamma_2=\gamma_1-1/2$
of the Balcan-Erzan model turn out to be robust under duplication and point
mutations, but get modified in the presence of splitting and merging of
strings. The clustering coefficient as a function of the degree, $C(d)$, is
found, for the Balcan-Erzan model, to behave in a way qualitatively similar to
the out-degree distribution, however with a very small exponent $\alpha_1=
1-\gamma_1$ and an envelope for the oscillatory part, which is essentially
flat, thus $\alpha_2= 0$. Under duplication and mutations including splitting
and merging of strings, $C(d)$ is found to decay exponentially.


title: The equilibrium theory of life evolution

abstract:
  Apparent biodiversity on earth exists only if we compare different species
separated from their environments. Meanwhile coexisting species have to be
identical in terms of energetic interactions. Consider the biosphere as a
network of chemical reactions. This leads to the conclusion that forces which
drive life evolution may be found inside the process of the transformations of
molecules. From the thermodynamic point of view the system of reacting
particles reaches a steady state when the chemical potentials of reagents
become equal. Interactions between chemical compounds taking part in concurrent
reactions and the equilibration of their chemical potentials is the essence of
biological evolution and its only driving force.


title:
Effect of pooling samples on the efficiency of comparative studies using
  microarrays

abstract:
  Many biomedical experiments are carried out by pooling individual biological
samples. However, pooling samples can potentially hide biological variance and
give false confidence concerning the data significance. In the context of
microarray experiments for detecting differentially expressed genes, recent
publications have addressed the problem of the efficiency of sample-pooling,
and some approximate formulas were provided for the power and sample size
calculations. It is desirable to have exact formulas for these calculations and
have the approximate results checked against the exact ones. We show that the
difference between the approximate and exact results can be large. In this
study, we have characterized quantitatively the effect of pooling samples on
the efficiency of microarray experiments for the detection of differential gene
expression between two classes. We present exact formulas for calculating the
power of microarray experimental designs involving sample pooling and technical
replications. The formulas can be used to determine the total numbers of arrays
and biological subjects required in an experiment to achieve the desired power
at a given significance level. The conditions under which pooled design becomes
preferable to non-pooled design can then be derived given the unit cost
associated with a microarray and that with a biological subject. This paper
thus serves to provide guidance on sample pooling and cost effectiveness. The
formulation in this paper is outlined in the context of performing microarray
comparative studies, but its applicability is not limited to microarray
experiments. It is also applicable to a wide range of biomedical comparative
studies where sample pooling may be involved.


title: NF-kappa B oscillations and cell-to-cell variability

abstract:
  Oscillations of the transcription factor NF-kappa B have been observed
experimentally both for cell populations by Hoffmann et al. (2002) and for
single cells by Nelson et al. (2004). The latter experiments show significant
cell-to-cell variability. We use the (stochastic) Gillespie algorithm to study
the set of reactions proposed by Hoffmann et al. and variants thereof. The
amounts of cellular NF-kappa B and activated kinase IKK are treated as external
parameters. We show that intrinsic fluctuations are small in a model with
strong transcription, while they are large for weak transcription. Extrinsic
noise can be significant: fluctuations in NF-kappa B affect mainly the
amplitude of oscillations, whereas fluctuations in activated IKK affect both
their amplitude and period. The latter results are in qualitative agreement
with the observations of Nelson et al.


title: Some Theoretical Investigations in EEG Studies

abstract:
  It is well known that Electroencephalography(EEG) and the respective evoked
potentials have deep implications corresponding to specific cognitive tasks and
in the diagnosis of several diseases such as epilepsy and schizophrenia. Some
recent experimental results have already shown some evidence of chaotic
activity in the brain. The Hodgekin-Huxley(HH) models, may yield geometrical
solutions in terms of limit cycles and basins of attractors, but its
implementation requires a priori knowledge of the kinetics of the innumerable
conductances acting in a given set of cells. We are of the opinion that the EEG
data should reflect the neuronal dynamics, and there should be some mechanism
at the neuronal level which generates stochasticity compatible with the
recorded data. In this paper we develop a theoretical framework to show that
EEG dynamics may be governed by a suitably biased Vander-Pol oscillator which
is closely related with the modified version of the FitzHugh-Nagumo(FN) model
making extension of the ideas of dynamic causal modelling (DCM). Eventually we
also give a prescription to compute the correlation matrices which may be
tested empirically, for some small values of the parameters.


title: Mathematical approaches to differentiation and gene regulation

abstract:
  We consider some mathematical issues raised by the modelling of gene
networks. The expression of genes is governed by a complex set of regulations,
which is often described symbolically by interaction graphs. Once such a graph
has been established, there remains the difficult task to decide which
dynamical properties of the gene network can be inferred from it, in the
absence of precise quantitative data about their regulation. In this paper we
discuss a rule proposed by R.Thomas according to which the possibility for the
network to have several stationary states implies the existence of a positive
circuit in the corresponding interaction graph. We prove that, when properly
formulated in rigorous terms, this rule becomes a theorem valid for several
different types of formal models of gene networks. This result is already known
for models of differential or boolean type. We show here that a stronger
version of it holds in the differential setup when the decay of protein
concentrations is taken into account. This allows us to verify also the
validity of Thomas' rule in the context of piecewise-linear models and the
corresponding discrete models. We discuss open problems as well.


title:
Classification of capped tubular viral particles in the family of
  Papovaviridae

abstract:
  A vital constituent of a virus is its protein shell, called the viral capsid,
that encapsulates and hence provides protection for the viral genome. Viral
capsids are usually spherical, and for a significant number of viruses exhibit
overall icosahedral symmetry. The corresponding surface lattices, that encode
the locations of the capsid proteins and intersubunit bonds, can be modelled by
Viral Tiling Theory.
  It has been shown in vitro that under a variation of the experimental
boundary conditions, such as the pH value and salt concentration, tubular
particles may appear instead of, or in addition to, spherical ones. In order to
develop models that describe the simultaneous assembly of both spherical and
tubular variants, and hence study the possibility of triggering tubular
malformations as a means of interference with the replication mechanism, Viral
Tiling Theory has to be extended to include tubular lattices with end caps.
This is done here for the case of Papovaviridae, which play a distinguished
role from the viral structural point of view as they correspond to all pentamer
lattices, i.e. lattices formed from clusters of five protein subunits
throughout. These results pave the way for a generalisation of recently
developed assembly models.


title: Vector space of DNA genomic sequences on a Genetic Code Galois Field

abstract:
  A new N-dimensional vector space of DNA sequences over the Galois field of
the 64 codons (GF(64)) was recently presented. Now, in order to include
deletions and insertions (indel mutations), we have defined a new Galois field
over the set of elements X1X2X3 (C125), where Xi belong to {O, A, C, G, C}. We
have called this set, the extended triplet set and the elements X1X2X3, the
extended triplets. The order of the bases is derived from the Z64-algebra of
the genetic code -recently published-. Starting from the natural bijection phi:
GF(5^3)-> C125 between the polynomial representation of elements from GF(5^3)
and the elements X1X2X3, a novel Galois field over the set of elements X1X2X3
is defined. Taking the polynomial coefficients a0, a1, a2 belong to GF(5) and
the bijective function f: GF(5) ->{O, A, C, G, C}, where f(0) = O, f(1) = A,
f(2) = C, f(3) = G, f(4) = U, bijection phi is induced such that phi(a0 + a1x +
a2x^2) = (f(a1), f(a2), f(a0)) = (X1X2X3). Next, by means of the bijection phi
we define sum "+" and product "*" operations in the set of codons C125, in such
a way that the resultant field (C125, +, *) turns isomorphic to the Galois
Field GF(5^3). This field allows the definition of a novel N-dimensional vector
space (S) over the field GF (5^3) on the set of all 125^N sequences of extended
triplets in which all possible DNA sequence alignments of length N are
included. Here the "classical gap" produced by alignment algorithms corresponds
to the neutral element "O". It is verified that the homologous (generalized)
recombination between two homologous DNA duplexes involving a reciprocal
exchange of DNA sequences -e.g. between two chromosomes that carry the same
genetic loci- algebraically corresponds to the action of two automorphism pairs
(or two translation pairs) over two paired DNA duplexes.


title:
Genome-wide discovery of modulators of transcriptional interactions in
  human B lymphocytes

abstract:
  Transcriptional interactions in a cell are modulated by a variety of
mechanisms that prevent their representation as pure pairwise interactions
between a transcription factor and its target(s). These include, among others,
transcription factor activation by phosphorylation and acetylation, formation
of active complexes with one or more co-factors, and mRNA/protein degradation
and stabilization processes.
  This paper presents a first step towards the systematic, genome-wide
computational inference of genes that modulate the interactions of specific
transcription factors at the post-transcriptional level. The method uses a
statistical test based on changes in the mutual information between a
transcription factor and each of its candidate targets, conditional on the
expression of a third gene. The approach was first validated on a synthetic
network model, and then tested in the context of a mammalian cellular system.
By analyzing 254 microarray expression profiles of normal and tumor related
human B lymphocytes, we investigated the post transcriptional modulators of the
MYC proto-oncogene, an important transcription factor involved in
tumorigenesis. Our method discovered a set of 100 putative modulator genes,
responsible for modulating 205 regulatory relationships between MYC and its
targets. The set is significantly enriched in molecules with function
consistent with their activities as modulators of cellular interactions,
recapitulates established MYC regulation pathways, and provides a notable
repertoire of novel regulators of MYC function. The approach has broad
applicability and can be used to discover modulators of any other transcription
factor, provided that adequate expression profile data are available.


title:
Statistical Predictive Models in Ecology: Comparison of Performances and
  Assessment of Applicability

abstract:
  Ecological systems are governed by complex interactions which are mainly
nonlinear. In order to capture this complexity and nonlinearity, statistical
models recently gained popularity. However, although these models are commonly
applied in ecology, there are no studies to date aiming to assess the
applicability and performance. We provide an overview for nature of the wide
range of the data sets and predictive variables, from both aquatic and
terrestrial ecosystems with different scales of time-dependent dynamics, and
the applicability and robustness of predictive modeling methods on such data
sets by comparing different statistical modeling approaches. The methods
considered k-NN, LDA, QDA, generalized linear models (GLM) feedforward
multilayer backpropagation networks and pseudo-supervised network ARTMAP. For
ecosystems involving time-dependent dynamics and periodicities whose frequency
are possibly less than the time scale of the data considered, GLM and
connectionist neural network models appear to be most suitable and robust,
provided that a predictive variable reflecting these time-dependent dynamics
included in the model either implicitly or explicitly. For spatial data, which
does not include any time-dependence comparable to the time scale covered by
the data, on the other hand, neighborhood based methods such as k-NN and ARTMAP
proved to be more robust than other methods considered in this study. In
addition, for predictive modeling purposes, first a suitable, computationally
inexpensive method should be applied to the problem at hand a good predictive
performance of which would render the computational cost and efforts associated
with complex variants unnecessary.