title:
Correctly validating results from single molecule data: the case of
  stretched exponential decay in the catalytic activity of single lipase B
  molecules

abstract:
  The question of how to validate and interpret correctly the waiting time
probability density functions (WT-PDFs) from single molecule data is addressed.
It is shown by simulation that when a stretched exponential WT-PDF, with a
stretched exponent alfa and a time scale parameter tau, generates the off
periods of a two-state trajectory, a reliable recovery of the input WT-PDF from
the trajectory is obtained even when the bin size used to define the
trajectory, dt, is much larger than the parameter tau. This holds true as long
as the first moment of the WT-PDF is much larger than dt. Our results validate
the results in an earlier study of the activity of single Lipase B molecules
and disprove recent related critique.


title: microRNAs may sharpen spatial expression patterns

abstract:
  The precise layout of gene expression patterns is a crucial step in
development. Formation of a sharp boundary between high and low expression
domains requires a genetic mechanism which is both sensitive and robust to
fluctuations, a demand that may not be easily achieved by morphogens alone.
Recently it has been demonstrated that small RNAs (and, in particular,
microRNAs) play many roles in embryonic development. While some RNAs are
essential for embryogenesis, others are limited to fine-tuning a predetermined
gene expression pattern. Here we explore the possibility that small RNAs
participate in sharpening a gene expression profile that was crudely
established by a morphogen. To this end we study a model where small RNAs
interact with a target gene and diffusively move from cell to cell. Though
diffusion generally smears spatial expression patterns, we find that
intercellular mobility of small RNAs is actually critical in sharpening the
interface between target expression domains in a robust manner. We discuss the
applicability of our results, as examples, to the case of leaf polarity
establishment in maize and Hox patterning in the early {\it Drosophila} embryo.
Our findings point out the functional significance of some mechanistic
properties, such as mobility of small RNAs and the irreversibility of their
interactions. These properties are yet to be established directly for most
classes of small RNAs. An indirect yet simple experimental test of the proposed
mechanism is suggested in some detail.


title:
Multifractal analysis of normal RR heart-interbeat signals in power
  spectra ranges

abstract:
  Power spectral density is an accepted measure of heart rate variability. Two
estimators of multifractal properties: Wavelet Transform Modulus Maxima and
Multifractal Detrended Fluctuation Analysis are used to investigate
multifractal properties for the three strongly physiologically grounded
components of power spectra: low frequency (LF), very low frequency (VLF) and
ultra low frequency (ULV). Circadian rhythm changes are examined by
discrimination of daily activity from nocturnal rest. Investigations consider
normal sinus rhythms of healthy 39 subjects which are grouped in two sets:
5-hour wake series and 5-hour sleep series. Qualitative arguments are provided
to conjecture the presence of stochastic persistence in LF range, loss of heart
rate variability during night in VLF range and its increase in ULF.


title:
The Time Invariance Principle, Ecological (Non)Chaos, and A Fundamental
  Pitfall of Discrete Modeling

abstract:
  This paper is to show that most discrete models used for population dynamics
in ecology are inherently pathological that their predications cannot be
independently verified by experiments because they violate a fundamental
principle of physics. The result is used to tackle an on-going controversy
regarding ecological chaos. Another implication of the result is that all
continuous dynamical systems must be modeled by differential equations. As a
result it suggests that researches based on discrete modeling must be closely
scrutinized and the teaching of calculus and differential equations must be
emphasized for students of biology.


title:
The Cyclohedron Test for Finding Periodic Genes in Time Course
  Expression Studies

abstract:
  The problem of finding periodically expressed genes from time course
microarray experiments is at the center of numerous efforts to identify the
molecular components of biological clocks. We present a new approach to this
problem based on the cyclohedron test, which is a rank test inspired by recent
advances in algebraic combinatorics. The test has the advantage of being robust
to measurement errors, and can be used to ascertain the significance of
top-ranked genes. We apply the test to recently published measurements of gene
expression during mouse somitogenesis and find 32 genes that collectively are
significant. Among these are previously identified periodic genes involved in
the Notch/FGF and Wnt signaling pathways, as well as novel candidate genes that
may play a role in regulating the segmentation clock. These results confirm
that there are an abundance of exceptionally periodic genes expressed during
somitogenesis. The emphasis of this paper is on the statistics and
combinatorics that underlie the cyclohedron test and its implementation within
a multiple testing framework.


title:
Identifying evolutionary trees and substitution parameters for the
  general Markov model with invariable sites

abstract:
  The general Markov plus invariable sites (GM+I) model of biological sequence
evolution is a two-class model in which an unknown proportion of sites are not
allowed to change, while the remainder undergo substitutions according to a
Markov process on a tree. For statistical use it is important to know if the
model is identifiable; can both the tree topology and the numerical parameters
be determined from a joint distribution describing sequences only at the leaves
of the tree? We establish that for generic parameters both the tree and all
numerical parameter values can be recovered, up to clearly understood issues of
`label swapping.' The method of analysis is algebraic, using phylogenetic
invariants to study the variety defined by the model. Simple rational formulas,
expressed in terms of determinantal ratios, are found for recovering numerical
parameters describing the invariable sites.


title:
On the equilibria of the MAPK cascade: cooperativity, modularity and
  bistability

abstract:
  In this paper we present a discussion of a phenomenological model of the MAPK
cascade which was originally proposed by Angeli et al. (PNAS 101, 1822 (2004)).
The model and its solution are extended in several respects: a) an analytical
solution is given for the cascade equilibria, exploiting a parameter-based
symmetry of the rate equations; b) we discuss the cooperativity (Hill
coefficients) of the cascade and show that a feedforward loop within the
cascade increases its cooperativity. The relevance of this result for the
notion of modularity is discussed; c) the feedback model for cascade
bistability by Angeli et al. is reconsidered. We argue that care must be taken
in modeling the interactions and a biologically realistic phenomenological
model cannot be too reductionist. The inclusion of a time-dependent degradation
rate is needed to account for a switching of the cascade.


title: Topological coding in hippocampus

abstract:
  The proposed analysis of the currently available experimental results
concerning the neural cell activity in the brain area known as hippocampus
suggests a particular mechanism of spatial information and memory processing.
Below it is argued that the spatial information available through the analysis
of the hippocampal cell activity is predominantly of topological nature. It is
pointed out that a direct topological analysis can produce a topological
invariant based classification of the cell activity patterns and a complete
topological description of animal's current environment. It also provides a
full first order logical system for local topological reasoning about spatial
structure and animal's navigational strategies.


title:
Local Perturbations Do Not Affect Stability of Laboratory Fruitfly
  Metapopulations

abstract:
  A large number of theoretical studies predict that the dynamics of spatially
structured populations (metapopulations) can be altered by constant
perturbations to local population size. However, these studies presume large
metapopulations inhabiting noise-free, zero-extinction environments, and their
predictions have never been empirically verified.
  Here we report an empirical study on the effects of localized perturbations
on global dynamics and stability, using fruitfly metapopulations in the
laboratory. We find that constant addition of individuals to a particular
subpopulation in every generation stabilizes that subpopulation locally, but
does not have any detectable effect on the dynamics and stability of the
metapopulation. Simulations of our experimental system using a simple but
widely applicable model of population dynamics were able to recover the
empirical findings, indicating the generality of our results. We then simulated
the possible consequences of perturbing more subpopulations, increasing the
strength of perturbations, and varying the rate of migration, but found that
none of these conditions were expected to alter the outcomes of our
experiments. Finally, we show that our main results are robust to the presence
of local extinctions in the metapopulation.
  Our study shows that localized perturbations are unlikely to affect the
dynamics of real metapopulations, a finding that has cautionary implications
for ecologists and conservation biologists faced with the problem of
stabilizing unstable metapopulations in nature.


title: Kernel matrix regression

abstract:
  We address the problem of filling missing entries in a kernel Gram matrix,
given a related full Gram matrix. We attack this problem from the viewpoint of
regression, assuming that the two kernel matrices can be considered as
explanatory variables and response variables, respectively. We propose a
variant of the regression model based on the underlying features in the
reproducing kernel Hilbert space by modifying the idea of kernel canonical
correlation analysis, and we estimate the missing entries by fitting this model
to the existing samples. We obtain promising experimental results on gene
network inference and protein 3D structure prediction from genomic datasets. We
also discuss the relationship with the em-algorithm based on information
geometry.


title: Positive Feedback, Stochasticity and Genetic Competence

abstract:
  A single gene, regulating its own expression via a positive feedback loop,
constitutes a common motif in gene regulatory networks and signalling cascades.
Recent experiments on the development of competence in the bacterial population
\emph{B. subtilis} show that the autoregulatory genetic module by itself can
give rise to two types of cellular states. The states correspond to the low and
high expression states of the master regulator ComK. The high expression state
is attained when the ComK protein level exceeds a threshold value leading to a
full activation of the autostimulatory loop. Stochasticity in gene expression
drives the transitions between the two stable states. In this paper, we explain
the appearance of bimodal protein distributions in \emph{B. subtilis} cell
population in the framework of three possible scenarios. In two of the cases,
bistability provides the basis for binary gene expression. In the third case,
the system is monostable in a deterministic description and stochasticity in
gene expression is solely responsible for the appearance of the two expression
states.


title: The G-Ball, a New Icon for Codon Symmetry and the Genetic Code

abstract:
  A codon table is a useful tool for mapping codons to amino acids as they have
been assigned by nature. It has become a scientific icon because of the way it
embodies our understanding of this natural process and the way it immediately
communicates this understanding. However, advancements in molecular biology
over the past several decades must lead to a realization that our basic
understanding of genetic translation is fundamentally flawed and incomplete,
and, therefore, our icon is inadequate. A better understanding of symmetry and
an appreciation for the essential role it has played in codon formation will
improve our understanding of nature's coding processes. Incorporation of that
symmetry into our icon will facilitate that improvement.


title:
Detection of the dominant direction of information flow in densely
  interconnected regulatory networks

abstract:
  Finding the dominant direction of flow of information in densely
interconnected regulatory or signaling networks is required in many
applications in computational biology and neuroscience. This is achieved by
first identifying and removing links which close up feedback loops in the
original network and hierarchically arranging nodes in the remaining network.
In mathematical language this corresponds to a problem of making a graph
acyclic by removing as few links as possible and thus altering the original
graph in the least possible way. Practically in all applications the exact
solution of this problem requires an enumeration of all combinations of removed
links, which is computationally intractable. We introduce and compare two
algorithms: the deterministic, 'greedy' algorithm that preferentially cuts the
links that participate in the largest number of feedback cycles, and the
probabilistic one based on a simulated annealing of a hierarchical layout of
the network which minimizes the number of ``backward'' links going from lower
to higher hierarchical levels. We find that the annealing algorithm outperforms
the deterministic one in terms of speed, memory requirement, and the actual
number of removed links. Implications for system biology and directions for
further research are discussed.


title:
Symbolic Reachability Analysis of Genetic Regulatory Networks using
  Qualitative Abstractions

abstract:
  The switch-like character of gene regulation has motivated the use of hybrid,
discrete-continuous models of genetic regulatory networks. While powerful
techniques for the analysis, verification, and control of hybrid systems have
been developed, the specificities of the biological application domain pose a
number of challenges, notably the absence of quantitative information on
parameter values and the size and complexity of networks of biological
interest. We introduce a method for the analysis of reachability properties of
genetic regulatory networks that is based on a class of discontinuous
piecewise-affine (PA) differential equations well-adapted to the above
constraints. More specifically, we introduce a hyperrectangular partition of
the state space that forms the basis for a discrete abstraction preserving the
sign of the derivatives of the state variables. The resulting discrete
transition system provides a conservative approximation of the qualitative
dynamics of the network and can be efficiently computed in a symbolic manner
from inequality constraints on the parameters. The method has been implemented
in the computer tool Genetic Network Analyzer (GNA), which has been applied to
the analysis of a regulatory system whose functioning is not well-understood by
biologists, the nutritional stress response in the bacterium Escherichia coli.


title: Representing perturbed dynamics in biological network models

abstract:
  We study the dynamics of gene activities in relatively small size biological
networks (up to a few tens of nodes), e.g. the activities of cell-cycle
proteins during the mitotic cell-cycle progression. Using the framework of
deterministic discrete dynamical models, we characterize the dynamical
modifications in response to structural perturbations in the network
connectivities. In particular, we focus on how perturbations affect the set of
fixed points and sizes of the basins of attraction. Our approach uses two
analytical measures: the basin entropy $H$ and the perturbation size $\Delta$,
a quantity that reflects the distance between the set of fixed points of the
perturbed network to that of the unperturbed network. Applying our approach to
the yeast-cell cycle network introduced by Li \textit{et al.} provides a low
dimensional and informative fingerprint of network behavior under large classes
of perturbations. We identify interactions that are crucial for proper network
function, and also pinpoints functionally redundant network connections.
Selected perturbations exemplify the breadth of dynamical responses in this
cell-cycle model.


title: Toll Based Measures for Dynamical Graphs

abstract:
  Biological networks are one of the most studied object in computational
biology. Several methods have been developed for studying qualitative
properties of biological networks. Last decade had seen the improvement of
molecular techniques that make quantitative analyses reachable. One of the
major biological modelling goals is therefore to deal with the quantitative
aspect of biological graphs. We propose a probabilistic model that suits with
this quantitative aspects. Our model combines graph with several dynamical
sources. It emphazises various asymptotic statistical properties that might be
useful for giving biological insights


title: Continuum model of actin-mediated bacterial propulsion

abstract:
  The mechanism of propulsion of host bacteria under the action of actin gel
networks is examined by means of a continuum model of the dynamics of F-actin
concentration. The model includes the elasticity of the network, its attachment
to the host and the polymerization at the interface with it. A formula for the
cruise velocity is derived wherefrom the contributions of elasticity and
polymerization are made explicit.
  The velocity is proportional to the size of the active portion of the gel,
and in turn it elongates its shape. It is shown how a finite latency time is
needed for the onset of motion: the related threshold condition is explicitly
given. It is numerically found that at steady state the velocity has a
pulsating behavior, with sudden decelerations and subsequent recoveries: this
unveils the dominant role of the elastic forces in propulsion.


title: Dynamics of Microtubule Growth and Catastrophe

abstract:
  We investigate a simple model of microtubule dynamics in which a microtubule
evolves by: (i) attachment of guanosine triphosphate (GTP) to its end at rate
lambda, (ii) GTP converting irreversibly to guanosine diphosphate (GDP) at rate
1, and (iii) detachment of GDP from the end of a microtubule at rate mu. As a
function of these elemental rates, the microtubule can grow steadily or its
length can fluctuate wildly. A master equation approach is developed to
characterize these intriguing features. For mu=0, we find exact expressions for
tubule and GTP cap length distributions, as well as a power-law length
distributions of GTP and GDP islands. For mu=oo, we find the average time
between catastrophes, where the microtubule shrinks to zero length, and extend
this approach to also determine the size distribution of avalanches (sequence
of consecutive GDP detachment events). We obtain the phase diagram for general
rates and verify our predictions by numerical simulations.

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


title:
Autonomous Dynamics in Neural networks: The dHAN Concept and Associative
  Thought Processes

abstract:
  The neural activity of the human brain is dominated by self-sustained
activities. External sensory stimuli influence this autonomous activity but
they do not drive the brain directly. Most standard artificial neural network
models are however input driven and do not show spontaneous activities.
  It constitutes a challenge to develop organizational principles for
controlled, self-sustained activity in artificial neural networks. Here we
propose and examine the dHAN concept for autonomous associative thought
processes in dense and homogeneous associative networks. An associative
thought-process is characterized, within this approach, by a time-series of
transient attractors. Each transient state corresponds to a stored information,
a memory. The subsequent transient states are characterized by large
associative overlaps, which are identical to acquired patterns. Memory states,
the acquired patterns, have such a dual functionality.
  In this approach the self-sustained neural activity has a central functional
role. The network acquires a discrimination capability, as external stimuli
need to compete with the autonomous activity. Noise in the input is readily
filtered-out.
  Hebbian learning of external patterns occurs coinstantaneous with the ongoing
associative thought process. The autonomous dynamics needs a long-term
working-point optimization which acquires within the dHAN concept a dual
functionality: It stabilizes the time development of the associative thought
process and limits runaway synaptic growth, which generically occurs otherwise
in neural networks with self-induced activities and Hebbian-type learning
rules.


title:
Effect of Internal Viscosity on Brownian Dynamics of DNA Molecules in
  Shear Flow

abstract:
  The results of Brownian dynamics simulations of a single DNA molecule in
shear flow are presented taking into account the effect of internal viscosity.
The dissipative mechanism of internal viscosity is proved necessary in the
research of DNA dynamics. A stochastic model is derived on the basis of the
balance equation for forces acting on the chain. The Euler method is applied to
the solution of the model. The extensions of DNA molecules for different
Weissenberg numbers are analyzed. Comparison with the experimental results
available in the literature is carried out to estimate the contribution of the
effect of internal viscosity.


title: Excitable Scale Free Networks

abstract:
  When a simple excitable system is continuously stimulated by a Poissonian
external source, the response function (mean activity versus stimulus rate)
generally shows a linear saturating shape. This is experimentally verified in
some classes of sensory neurons, which accordingly present a small dynamic
range (defined as the interval of stimulus intensity which can be appropriately
coded by the mean activity of the excitable element), usually about one or two
decades only. The brain, on the other hand, can handle a significantly broader
range of stimulus intensity, and a collective phenomenon involving the
interaction among excitable neurons has been suggested to account for the
enhancement of the dynamic range. Since the role of the pattern of such
interactions is still unclear, here we investigate the performance of a
scale-free (SF) network topology in this dynamic range problem. Specifically,
we study the transfer function of disordered SF networks of excitable
Greenberg-Hastings cellular automata. We observe that the dynamic range is
maximum when the coupling among the elements is critical, corroborating a
general reasoning recently proposed. Although the maximum dynamic range yielded
by general SF networks is slightly worse than that of random networks, for
special SF networks which lack loops the enhancement of the dynamic range can
be dramatic, reaching nearly five decades. In order to understand the role of
loops on the transfer function we propose a simple model in which the density
of loops in the network can be gradually increased, and show that this is
accompanied by a gradual decrease of dynamic range.

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


title:
Evolution of Robustness to Noise and Mutation in Gene Expression
  Dynamics

abstract:
  Phenotype of biological systems needs to be robust against mutation in order
to sustain themselves between generations. On the other hand, phenotype of an
individual also needs to be robust against fluctuations of both internal and
external origins that are encountered during growth and development. Is there a
relationship between these two types of robustness, one during a single
generation and the other during evolution? Could stochasticity in gene
expression have any relevance to the evolution of these robustness? Robustness
can be defined by the sharpness of the distribution of phenotype; the variance
of phenotype distribution due to genetic variation gives a measure of `genetic
robustness' while that of isogenic individuals gives a measure of
`developmental robustness'. Through simulations of a simple stochastic gene
expression network that undergoes mutation and selection, we show that in order
for the network to acquire both types of robustness, the phenotypic variance
induced by mutations must be smaller than that observed in an isogenic
population. As the latter originates from noise in gene expression, this
signifies that the genetic robustness evolves only when the noise strength in
gene expression is larger than some threshold. In such a case, the two
variances decrease throughout the evolutionary time course, indicating increase
in robustness. The results reveal how noise that cells encounter during growth
and development shapes networks' robustness to stochasticity in gene
expression, which in turn shapes networks' robustness to mutation. The
condition for evolution of robustness as well as relationship between genetic
and developmental robustness is derived through the variance of phenotypic
fluctuations, which are measurable experimentally.


title:
Toward a better analysis of secreted proteins: the example of the
  myeloid cells secretome

abstract:
  The analysis of secreted proteins represents a challenge for current
proteomics techniques. Proteins are usually secreted at low concentrations in
the culture media, which makes their recovery difficult. In addition, culture
media are rich in salts and other compounds interfering with most proteomics
techniques, which makes selective precipitation of proteins almost mandatory
for a correct subsequent proteomics analysis. Last but not least, the
non-secreted proteins liberated in the culture medium upon lysis of a few dead
cells heavily contaminate the so-called secreted proteins preparations. Several
techniques have been used in the past for concentration of proteins secreted in
culture media. These techniques present several drawbacks, such as
coprecipitation of salts or poor yields at low protein concentrations. Improved
techniques based on carrier-assisted trichloroacetic acid precipitation are
described and discussed in this paper. These techniques have been used to
analyse the secretome of myeloid cells (macrophages, dendritic cells) and
enabled to analyze proteins secreted at concentrations close to 1 ng/ml,
thereby allowing to detect some of the cytokines (TNF, IL-12) secreted by the
myeloid cells upon activation by bacterial products.


title:
Simcluster: clustering enumeration gene expression data on the simplex
  space

abstract:
  Transcript enumeration methods such as SAGE, MPSS, and
sequencing-by-synthesis EST ``digital northern'', are important high-throughput
techniques for digital gene expression measurement. As other counting or voting
processes, these measurements constitute compositional data exhibiting
properties particular to the simplex space where the summation of the
components is constrained. These properties are not present on regular
Euclidean spaces, on which hybridization-based microarray data is often
modeled. Therefore, pattern recognition methods commonly used for microarray
data analysis may be non-informative for the data generated by transcript
enumeration techniques since they ignore certain fundamental properties of this
space. Here we present a software tool, Simcluster, designed to perform
clustering analysis for data on the simplex space. We present Simcluster as a
stand-alone command-line C package and as a user-friendly on-line tool. Both
versions are available at: http://xerad.systemsbiology.net/simcluster/ .
Simcluster is designed in accordance with a well-established mathematical
framework for compositional data analysis, which provides principled procedures
for dealing with the simplex space, and is thus applicable in a number of
contexts, including enumeration-based gene expression data.


title: The stochastic entry of enveloped viruses: Fusion vs. endocytosis

abstract:
  Viral infection requires the binding of receptors on the target cell membrane
to glycoproteins, or ``spikes,'' on the viral membrane. The initial entry is
usually classified as fusogenic or endocytotic. However, binding of viral
spikes to cell surface receptors not only initiates the viral adhesion and the
wrapping process necessary for internalization, but can simultaneously initiate
direct fusion with the cell membrane. Both fusion and internalization have been
observed to be viable pathways for many viruses. We develop a stochastic model
for viral entry that incorporates a competition between receptor mediated
fusion and endocytosis. The relative probabilities of fusion and endocytosis of
a virus particle initially nonspecifically adsorbed on the host cell membrane
are computed as functions of receptor concentration, binding strength, and
number of spikes. We find different parameter regimes where the entry pathway
probabilities can be analytically expressed. Experimental tests of our
mechanistic hypotheses are proposed and discussed.


title: An allosteric model of KaiC phosphorylation

abstract:
  In a recent series of ground-breaking experiments, Nakajima et al. [Science
308, 414-415 (2005)] showed that the three cyanobacterial clock proteins KaiA,
KaiB, and KaiC are sufficient in vitro to generate circadian phosphorylation of
KaiC. Here, we present a mathematical model of the Kai system. At its heart is
the assumption that KaiC can exist in two conformational states, one favoring
phosphorylation and the other dephosphorylation. Each individual KaiC hexamer
then has a propensity to be phosphorylated in a cyclic manner. To generate
macroscopic oscillations, however, the phosphorylation cycles of the different
hexamers must be synchronized. We propose a novel synchronisation mechanism
based on differential affinity: KaiA stimulates KaiC phosphorylation, but the
limited supply of KaiA dimers binds preferentially to those KaiC hexamers that
are falling behind in the oscillation. KaiB sequesters KaiA and stabilizes the
dephosphorylating KaiC state. We show that our model can reproduce a wide range
of published data, including the observed insensitivity of the oscillation
period to variations in temperature, and that it makes nontrivial predictions
about the effects of varying the concentrations of the Kai proteins.


title:
How to design multi-target drugs: Target search options in cellular
  networks

abstract:
  Despite improved rational drug design and a remarkable progress in genomic,
proteomic and high-throughput screening methods, the number of novel,
single-target drugs fell much behind expectations during the past decade.
Multi-target drugs multiply the number of pharmacologically relevant target
molecules by introducing a set of indirect, network-dependent effects. Parallel
with this the low-affinity binding of multi-target drugs eases the constraints
of druggability, and significantly increases the size of the druggable
proteome. These effects tremendously expand the number of potential drug
targets, and will introduce novel classes of multi-target drugs with smaller
side effects and toxicity. Here we review the recent progress in this field,
compare possible network attack strategies, and propose several methods to find
target-sets for multi-target drugs.


title: Genetic Code as a Harmonic System: three Supplements

abstract:
  The paper represents three supplements to the source paper, q-bio/0610044
[q-bio.OT], with three new series of harmonic structures of the genetic code,
determined by Gauss arithmetical algorithm; by Table of Minimal Adding, as in
(Rakocevic, 2011a: Table 4; 2011b: Table 4); all structures in relation to
Binary-code tree (Rakocevic, 1998). The determination itself is realized
through atom and nucleon number balancing and nuancing of molekular polarity.
In the first supplement the word is about some additional harmonic structures
in relation to a previous our paper (Rakocevic, 2004); in the second one about
the relation that structures with the polarity of protein amino acids. In the
third supplement we give new ideas about the genetic code by an inclusion of
the notions cipher of the genetic code and the key of that cipher.


title: A New Genetic Code Table

abstract:
  In this paper it is shown that within a Combined Genetic Code Table, realized
through a combination of Watson-Crick Table and Codon Path Cube it exists,
without an exception, a strict distinction between two classes of enzymes
aminoacyl-tRNA synthetases, corresponding two classes of amino acids and
belonging codons. By this, the distinction itself is followed by a strict
balance of atom number within two subclasses of class I as well as two
subclasses of class II of amino acids.


title: Utilizing the information content in two-state trajectories

abstract:
  The signal from many single molecule experiments monitoring molecular
processes, such as enzyme turnover via fluorescence and opening and closing of
ion channel via the flux of ions, consists of a time series of stochastic on
and off (or open and closed) periods, termed a two-state trajectory. This
signal reflects the dynamics in the underlying multi-substate on-off kinetic
scheme (KS) of the process. The determination of the underlying KS is difficult
and sometimes even impossible due to the loss of information in the mapping of
the mutli dimensional KS onto two dimensions. Here we introduce a new procedure
that efficiently and optimally relates the signal to all equivalent underlying
KSs. This procedure partitions the space of KSs into canonical (unique) forms
that can handle any KS, and obtains the topology and other details of the
canonical form from the data without the need for fitting. Also established are
relationships between the data and the topology of the canonical form to the
on-off connectivity of a KS. The suggested canonical forms constitute a
powerful tool in discriminating between KSs. Based on our approach, the upper
bound on the information content in two state trajectories is determined.


title: Coulomb Interaction as the Source of Muscle Force

abstract:
  Myosin motor is the machine, which performs mechanical work in the course of
adenosine triphosphate molecule hydrolysis and myosin head conformations
accompanying this process. For displacement of individual fragments of large
molecule relative to each other to arise and work to be performed, force must
be born inside protein. What kind of interaction generates this force?
  Models based on Huxley 1957 theory ascertain relations between chemical
reactions rate constants and energies of crossbridge conformations.
Nevertheless, understand in the framework of thermodynamics how myosin motor
works in principle is impossible: it is smoothly heated device cyclically
producing mechanical work (second law). Furthermore, in every working cycle
myosin head captures and splits a single molecule. Hence, ordinary dynamic laws
rather than stochastic laws govern this process.
  The simple mechanism of chemomechanical transduction is proposed. The two
products of adenosine triphosphate hydrolysis, adenosine diphosphate and
inorganic phosphate, have charges of the same sense and Coulomb interaction of
these charges produces the force pushing backdoor and rotating converter
domain. The velocity of filaments sliding becomes the principal parameter in
the model and new mechanism of indirect interaction between the cross-bridges
radically different from one suggested by Huxley and Simmons in 1971 appears.
The working stroke duration is inversely proportional to the velocity now.
Therefore Hill equation appears and the parameter values obtained are in
reasonable agreement with experiment.


title:
Analyzing the Dynamic Relationship between Tumor Growth and Angiogenesis
  in a Two Dimensional Finite Element Model

abstract:
  Employing a novel two-dimensional computational model we have simulated the
feedback between angiogenesis and tumor growth dynamics. Analyzing vessel
formation and elongation towards the concentration gradient of the
tumor-derived angiogenetic basic fibroblast growth factor, bFGF, we assumed
that prior to the blood vessels reaching the tumor surface, the resulting
pattern of tumor growth is symmetric, circular with a common center point.
However, after the vessels reach the tumor surface, we assumed that the growth
rate of that particular cancer region is accelerated compared to the tumor
surface section that lacks neo-vascularization. Therefore, the resulting
asymmetric tumor growth pattern is biased towards the site of the nourishing
vessels. The simulation results show over time an increase in vessel density, a
decrease in vessel branching length, and an increase in fracticality of the
vascular branching architecture. Interestingly, over time the fractal dimension
displayed a sigmoidal pattern with a reduced rate increase at earlier and later
tumor growth stages due to distinct characteristics in vessel length and
density. The finding that, at later stages, higher vascular fracticality
resulted in a marked increase of tumor slice volume provides further in silico
evidence for a functional impact of vascular patterns on cancer growth.


title: A model for rolling swarms of locusts

abstract:
  We construct an individual-based kinematic model of rolling migratory locust
swarms. The model incorporates social interactions, gravity, wind, and the
effect of the impenetrable boundary formed by the ground. We study the model
using numerical simulations and tools from statistical mechanics, namely the
notion of H-stability. For a free-space swarm (no wind and gravity), as the
number of locusts increases, it approaches a crystalline lattice of fixed
density if it is H-stable, and in contrast becomes ever more dense if it is
catastrophic. Numerical simulations suggest that whether or not a swarm rolls
depends on the statistical mechanical properties of the corresponding
free-space swarm. For a swarm that is H-stable in free space, gravity causes
the group to land and form a crystalline lattice. Wind, in turn, smears the
swarm out along the ground until all individuals are stationary. In contrast,
for a swarm that is catastrophic in free space, gravity causes the group to
land and form a bubble-like shape. In the presence of wind, the swarm migrates
with a rolling motion similar to natural locust swarms. The rolling structure
is similar to that observed by biologists, and includes a takeoff zone, a
landing zone, and a stationary zone where grounded locusts can rest and feed.


title:
Thermal Impact on Spiking Properties in Hodgkin-Huxley Neuron with
  Synaptic Stimulus

abstract:
  The effect of environmental temperature on neuronal spiking behaviors is
investigated by numerically simulating the temperature dependence of spiking
threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find
that the spiking threshold exhibits a global minimum in a "comfortable
temperature" range where spike initiation needs weakest synaptic strength,
indicating the occurrence of optimal use of synaptic transmission in neural
system. We further explore the biophysical origin of this phenomenon in ion
channel gating kinetics and also discuss its possible biological relevance in
information processing in neural systems.


title: The functional structure of cortical neuronal networks grown in vitro

abstract:
  We apply an information theoretic treatment of action potential time series
measured with microelectrode arrays to estimate the connectivity of mammalian
neuronal cell assemblies grown {\it in vitro}. We infer connectivity between
two neurons via the measurement of the mutual information between their spike
trains. In addition we measure higher point multi-informations between any two
spike trains conditional on the activity of a third cell, as a means to
identify and distinguish classes of functional connectivity among three
neurons. The use of a conditional three-cell measure removes some
interpretational shortcomings of the pairwise mutual information and sheds
light into the functional connectivity arrangements of any three cells. We
analyze the resultant connectivity graphs in light of other complex networks
and demonstrate that, despite their {\it ex vivo} development, the connectivity
maps derived from cultured neural assemblies are similar to other biological
networks and display nontrivial structure in clustering coefficient, network
diameter and assortative mixing. Specifically we show that these networks are
weakly disassortative small world graphs, which differ significantly in their
structure from randomized graphs with the same degree. We expect our analysis
to be useful in identifying the computational motifs of a wide variety of
complex networks, derived from time series data.


title:
Robustness of Cooperation in the Evolutionary Prisoner's Dilemma on
  Complex Networks

abstract:
  Recent studies on the evolutionary dynamics of the Prisoner's Dilemma game in
scale-free networks have demonstrated that the heterogeneity of the network
interconnections enhances the evolutionary success of cooperation. In this
paper we address the issue of how the characterization of the asymptotic states
of the evolutionary dynamics depends on the initial concentration of
cooperators. We find that the measure and the connectedness properties of the
set of nodes where cooperation reaches fixation is largely independent of
initial conditions, in contrast with the behavior of both the set of nodes
where defection is fixed, and the fluctuating nodes. We also check for the
robustness of these results when varying the degree heterogeneity along a
one-parametric family of networks interpolating between the class of
Erdos-Renyi graphs and the Barabasi-Albert networks.


title: Chromosome Length Scaling in Haploid, Asexual Reproduction

abstract:
  We study the genetic behaviour of a population formed by haploid individuals
which reproduce asexually. The genetic information for each individual is
stored along a bit-string (or chromosome) with L bits, where 0-bits represent
the wild-type allele and 1-bits correspond to harmful mutations. Each newborn
inherits this chromosome from its parent with some few random mutations: on
average a fixed number m of bits are flipped. Selection is implemented
according to the number N of 1-bits counted along the individual's chromosome:
the smaller N the higher the probability an individual has to survive a new
time step. Such a population evolves, with births and deaths, and its genetic
distribution becomes stabilised after many enough generations have passed.
  The question we pose concerns the procedure of increasing L. The aim is to
get the same distribution of relative genetic loads N/L among the equilibrated
population, in spite of a larger L. Should we keep the same mutation rate m/L
for different values of L? The answer is yes, which intuitively seems to be
plausible. However, this conclusion is not trivial, according to our
simulational results: the question involves also the population size.


title:
The Origin of 2 Sexes Through Optimization of Recombination Entropy
  Against Time and Energy

abstract:
  Sexual reproduction in Nature requires two sexes, which raises the question
why the reproductive scheme did not evolve to have three or more sexes. Here we
construct a constrained optimization model based on the communication theory to
analyze trade-offs among reproductive schemes with arbitrary number of sexes.
More sexes on one hand lead to higher reproductive diversity, but on the other
hand incur greater cost in time and energy for reproductive success. Our model
shows that the two-sexes reproduction scheme maximizes the recombination
entropy-to-cost ratio, and hence is the optimal solution to the problem.


title:
Are Genetically Robust Regulatory Networks Dynamically Different from
  Random Ones?

abstract:
  We study a genetic regulatory network model developed to demonstrate that
genetic robustness can evolve through stabilizing selection for optimal
phenotypes. We report preliminary results on whether such selection could
result in a reorganization of the state space of the system. For the chosen
parameters, the evolution moves the system slightly toward the more ordered
part of the phase diagram. We also find that strong memory effects cause the
Derrida annealed approximation to give erroneous predictions about the model's
phase diagram.

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


title: Sensory Substitution : Perception Dedicated to Action

abstract:
  Paul Bach Y Rita [1] is the precursor of sensory substitutions. He started
thirty years ago using visuo-tactile prostheses with the intent of satisfying
blind people. These prostheses, called Tactile Vision Substitution Systems
(TVSS), transform a sensory input from a given modality (vision) into another
modality (touch). These new systems seemed to induce quasi-visual perceptions.
One of the author's interests dealt with the understanding of the coupling
between actions and sensations in perception mechanisms [4]. Throughout his
search, he noticed that the subjects had to move the camera themselves in order
to recognise a 3D target-object or a figure placed in front of them. Our work
consists in understanding how sensory information provided by a visuo-tactile
prosthesis can be used for motor behaviour. In this aim, we used the most
simple substitution device (one photoreceptor coupled with one tactile
stimulator) in order to control and enrich our knowledge of the ties between
perception and action.


title: Mixed-Cultures and Alcoholic Fermentations

abstract:
  The population dynamics of mixed-culture and sequential-cultures in
fruit-must fermentation is a very interesting problem from both the theoretical
and technological stand point. By mixed-culture we refer to those fermentations
in which more that one strain/species are present from the beginning of the
process; and by sequential to those in which different microorganisms are added
along the process. These kinds of fermentations play a key role in industry of
fermented beverages. The mathematical models of such processes should represent
the dynamics of multiple species growing in a mixture of substrates as the
fruit must composition includes an important proportion of hexoses and
pentoses. Since the flavor is a basic aspect of beverages, and in general of
all fermented foods, it is fundamental to study the population dynamics and its
impact in the organoleptic properties, through the influence in the volatile
compound profile. The goal of this paper is to present a panorama of the
investigations of these fermentative ecosystems from a biological,
mathematical, and technological stand point.


title: Network analysis of protein dynamics

abstract:
  The network paradigm is increasingly used to describe the topology and
dynamics of complex systems. Here we review the results of the topological
analysis of protein structures as molecular networks describing their
small-world character, and the role of hubs and central network elements in
governing enzyme activity, allosteric regulation, protein motor function,
signal transduction and protein stability. We summarize available data how
central network elements are enriched in active centers and ligand binding
sites directing the dynamics of the entire protein. We assess the feasibility
of conformational and energy networks to simplify the vast complexity of rugged
energy landscapes and to predict protein folding and dynamics. Finally, we
suggest that modular analysis, novel centrality measures, hierarchical
representation of networks and the analysis of network dynamics will soon lead
to an expansion of this field.


title: Role of boundary constraints in DNA cyclization

abstract:
  We modify the classical Shimada-Yamakawa theory of DNA looping by
generalizing the form of boundary constraints. This generalization is important
in the context of DNA cyclization experiments since it mimics the reduced local
rigidity of the "nicked" DNA loop. Our results indicate that the non-trivial
boundary constraints may be responsible for the existing dramatic discrepancy
between various DNA cyclization experiments. The developed effective
Hamiltonian method may be further extended to a broad class of DNA looping
problems.


title: Elasticity of strongly stretched ssDNA

abstract:
  We present a simple model which describes elastic response of single-stranded
DNA (ssDNA) to stretching, including the regime of very high force (up to 1000
pN). ssDNA is modelled as a discreet persistent chain, whose ground state is a
zigzag rather than a straight line configuration. This mimics the underlying
molecular architecture and helps to explain the experimentally observed
staturation of the stretching curve at very high force.


title: Dynamics of RNA Translocation through a Nanopore

abstract:
  We present a simplified model of the dynamics of translocation of RNA through
a nanopore which only allows the passage of unbound nucleotides. In particular,
we consider the disorder averaged translocation dynamics of random,
two-component, single-stranded nucleotides, by reducing the dynamics to the
motion of a random walker on a one-dimensional free energy landscape of
translocation. These translocation landscapes are calculated from the folds of
the RNA sequences and the voltage bias applied across the nanopore. We compute
these landscapes for 1500 randomly drawn two-letter sequences of length 4000.
Simulations of the dynamics on these landscapes display anomalous
characteristics, similar to random forcing energy landscapes, where the
translocation process proceeds slower than linearly in time for sufficiently
small voltage biases across the nanopore, but moves linearly in time at large
voltage biases. We argue that our simplified model provides an upper bound to
the more realistic translocation dynamics, and thus we expect that all RNA
translocation models will exhibit anomalous regimes.


title: Hydrodynamic and rheology of active polar filaments

abstract:
  The cytoskeleton provides eukaryotic cells with mechanical support and helps
them perform their biological functions. It is a network of semiflexible polar
protein filaments and many accessory proteins that bind to these filaments,
regulate their assembly, link them to organelles and continuously remodel the
network. Here we review recent theoretical work that aims to describe the
cytoskeleton as a polar continuum driven out of equilibrium by internal
chemical reactions. This work uses methods from soft condensed matter physics
and has led to the formulation of a general framework for the description of
the structure and rheology of active suspension of polar filaments and
molecular motors.


title: Deterministic and Stochastic Simulations of Simple Genetic Circuits

abstract:
  We analyze three simple genetic circuits which involve transcriptional
regulation and feedback: the autorepressor, the switch and the repressilator,
that consist of one, two and three genes, respectively. Such systems are
commonly simulated using rate equations, that account for the concentrations of
the mRNAs and proteins produced by these genes. Rate equations are suitable
when the concentrations of the relevant molecules in a cell are large and
fluctuations are negligible. However, when some of the proteins in the circuit
appear in low copy numbers, fluctuations become important and the rate
equations fail. In this case stochastic methods, such as direct numerical
integration of the master equation or Monte Carlo simulations are required.
Here we present deterministic and stochastic simulations of the autorepressor,
the switch and the repressilator. We show that fluctuations give rise to
quantitative and qualitative changes in the dynamics of these systems. In
particular, we demonstrate a fluctuations-induced bistability in a variant of
the genetic switch and and noisy oscillations obtained in the repressilator
circuit.


title: Monte Carlo Simulation of Medical Resource Allocation

abstract:
  Computer simulations prove that we should spend more money on red wine than
on medication. We optimise the problem of how to distribute a fixed amount of
money between medication and food spendings, using the Penna ageing model.


title: Dynamics of Microtubule Instabilities

abstract:
  We investigate the dynamics of an idealized model of microtubule growth that
evolves by: (i) attachment of guanosine triphosphate (GTP) at rate lambda, (ii)
conversion of GTP to guanosine diphosphate (GDP) at rate 1, and (iii)
detachment of GDP at rate mu. As a function of these rates, a microtubule can
grow steadily or its length can fluctuate wildly. For mu=0, we find the exact
tubule and GTP cap length distributions, and power-law length distributions of
GTP and GDP islands. For mu=infinity, we argue that the time between
catastrophes, where the microtubule shrinks to zero length, scales as
exp(lambda). We also find the phase boundary between a growing and shrinking
microtubule.


title:
Complex population dynamics as a competition between multiple time-scale
  phenomena

abstract:
  The role of the selection pressure and mutation amplitude on the behavior of
a single-species population evolving on a two-dimensional lattice, in a
periodically changing environment, is studied both analytically and
numerically. The mean-field level of description allows to highlight the
delicate interplay between the different time-scale processes in the resulting
complex dynamics of the system. We clarify the influence of the amplitude and
period of the environmental changes on the critical value of the selection
pressure corresponding to a phase-transition "extinct-alive" of the population.
However, the intrinsic stochasticity and the dynamically-built in correlations
among the individuals, as well as the role of the mutation-induced variety in
population's evolution are not appropriately accounted for. A more refined
level of description, which is an individual-based one, has to be considered.
The inherent fluctuations do not destroy the phase transition "extinct-alive",
and the mutation amplitude is strongly influencing the value of the critical
selection pressure. The phase diagram in the plane of the population's
parameters -- selection and mutation is discussed as a function of the
environmental variation characteristics. The differences between a smooth
variation of the environment and an abrupt, catastrophic change are also
addressesd.

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


title: Metric learning for phylogenetic invariants

abstract:
  We introduce new methods for phylogenetic tree quartet construction by using
machine learning to optimize the power of phylogenetic invariants. Phylogenetic
invariants are polynomials in the joint probabilities which vanish under a
model of evolution on a phylogenetic tree. We give algorithms for selecting a
good set of invariants and for learning a metric on this set of invariants
which optimally distinguishes the different models. Our learning algorithms
involve linear and semidefinite programming on data simulated over a wide range
of parameters. We provide extensive tests of the learned metrics on simulated
data from phylogenetic trees with four leaves under the Jukes-Cantor and Kimura
3-parameter models of DNA evolution. Our method greatly improves on other uses
of invariants and is competitive with or better than neighbor-joining. In
particular, we obtain metrics trained on trees with short internal branches
which perform much better than neighbor joining on this region of parameter
space.


title:
Innate immunity, assessed by plasma NO measurements, is not suppressed
  during the incubation fast in eiders

abstract:
  Immunity is hypothesized to share limited resources with other physiological
functions and may mediate life history trade-offs, for example between
reproduction and survival. However, vertebrate immune defense is a complex
system that consists of three components. To date, no study has assessed all of
these components for the same animal model and within a given situation.
Previous studies have determined that the acquired immunity of common eiders
(Somateria mollissima) is suppressed during incubation. The present paper aims
to assess the innate immune response in fasting eiders in relation to their
initial body condition. Innate immunity was assessed by measuring plasma nitric
oxide (NO) levels, prior to and after injection of lipopolysaccharides (LPS), a
method which is easily applicable to many wild animals. Body condition index
and corticosterone levels were subsequently determined as indicators of body
condition and stress level prior to LPS injection. The innate immune response
in eiders did not vary significantly throughout the incubation period. The
innate immune response of eiders did not vary significantly in relation to
their initial body condition but decreased significantly when corticosterone
levels increased. However, NO levels after LPS injection were significantly and
positively related to initial body condition, while there was a significant
negative relationship with plasma corticosterone levels. Our study suggests
that female eiders preserve an effective innate immune response during
incubation and this response might be partially determined by the initial body
condition.


title:
Morphological relationship between axon and dendritic arborizations as
  revealed by Minkowski functionals

abstract:
  The spatial structure of the axonal and dendritic arborizations is closely
related to the functionality of specific neurons or neuronal subsystems. The
present work describes how multiscale Minkowski functionals can be used in
order to characterize and compare the spatial organization of these two types
of arborizations. The discrimination potential of the method is illustrated
with respect to three classes of cortical neurons.


title:
Universal properties of correlation transfer in integrate-and-fire
  neurons

abstract:
  One of the fundamental characteristics of a nonlinear system is how it
transfers correlations in its inputs to correlations in its outputs. This is
particularly important in the nervous system, where correlations between
spiking neurons are prominent. Using linear response and asymptotic methods for
pairs of unconnected integrate-and-fire (IF) neurons receiving white noise
inputs, we show that this correlation transfer depends on the output spike
firing rate in a strong, stereotyped manner, and is, surprisingly, almost
independent of the interspike variance. For cells receiving heterogeneous
inputs, we further show that correlation increases with the geometric mean
spiking rate in the same stereotyped manner, greatly extending the generality
of this relationship. We present an immediate consequence of this relationship
for population coding via tuning curves.


title:
A Pattern Discovery-Based Method for Detecting Multi-Locus Genetic
  Association

abstract:
  Methods to effectively detect multi-locus genetic association are becoming
increasingly relevant in the genetic dissection of complex trait in humans.
Current approaches typically consider a limited number of hypotheses, most of
which are related to the effect of a single locus or of a relatively small
number of neighboring loci on a chromosomal region. We have developed a novel
method that is specifically designed to detect genetic association involving
multiple disease-susceptibility loci, possibly on different chromosomes. Our
approach relies on the efficient discovery of patterns comprising spatially
unrestricted polymorphic markers and on the use of appropriate test statistics
to evaluate pattern-trait association. Power calculations using multi-locus
disease models demonstrate significant gain of power by using this method in
detecting multi-locus genetic association when compared to a standard single
marker analysis method. When analyzing a Schizophrenia dataset, we confirmed a
previously identified gene-gene interaction. In addition, a less conspicuous
association involving different markers on the same two genes was also
identified, implicating genetic heterogeneity.


title: Bounding biomass in the Fisher equation

abstract:
  The FKPP equation with a variable growth rate and advection by an
incompressible velocity field is considered as a model for plankton dispersed
by ocean currents. If the average growth rate is negative then the model has a
survival-extinction transition; the location of this transition in the
parameter space is constrained using variational arguments and delimited by
simulations. The statistical steady state reached when the system is in the
survival region of parameter space is characterized by integral constraints and
upper and lower bounds on the biomass and productivity that follow from
variational arguments and direct inequalities. In the limit of
zero-decorrelation time the velocity field is shown to act as Fickian diffusion
with an eddy diffusivity much larger than the molecular diffusivity and this
allows a one-dimensional model to predict the biomass, productivity and
extinction transitions. All results are illustrated with a simple growth and
stirring model.


title: Gene surfing

abstract:
  Spatially resolved genetic data is increasingly used to reconstruct the
migrational history of species. To assist such inference, we study, by means of
simulations and analytical methods, the dynamics of neutral gene frequencies in
a population undergoing a continual range expansion in one dimension. During
such a colonization period, lineages can fix at the wave front by means of a
``surfing'' mechanism [Edmonds C.A., Lillie A.S. & Cavalli-Sforza L.L. (2004)
Proc Natl Acad Sci USA 101: 975-979]. We quantify this phenomenon in terms of
(i) the spatial distribution of lineages that reach fixation and, closely
related, (ii) the continual loss of genetic diversity (heterozygosity) at the
wave front, characterizing the approach to fixation. Our simulations show that
an effective population size can be assigned to the wave that controls the
(observable) gradient in heterozygosity left behind the colonization process.
This effective population size is markedly higher in pushed waves than in
pulled waves, and increases only sub-linearly with deme size. To explain these
and other findings, we develop a versatile analytical approach, based on the
physics of reaction-diffusion systems, that yields simple predictions for any
deterministic population dynamics.


title: Community-driven dispersal in an individual-based predator-prey model

abstract:
  We present a spatial, individual-based predator-prey model in which dispersal
is dependent on the local community. We determine species suitability to the
biotic conditions of their local environment through a time and space varying
fitness measure. Dispersal of individuals to nearby communities occurs whenever
their fitness falls below a predefined tolerance threshold. The spatiotemporal
dynamics of the model is described in terms of this threshold. We compare this
dynamics with the one obtained through density-independent dispersal and find
marked differences. In the community-driven scenario, the spatial correlations
in the population density do not vary in a linear fashion as we increase the
tolerance threshold. Instead we find the system to cross different dynamical
regimes as the threshold is raised. Spatial patterns evolve from disordered, to
scale-free complex patterns, to finally becoming well-organized domains. This
model therefore predicts that natural populations, the dispersal strategies of
which are likely to be influenced by their local environment, might be subject
to complex spatiotemporal dynamics.


title:
An allosteric model for circadian KaiC phosphorylation - Supporting
  Information

abstract:
  In this Supporting Information, we provide background information on our
model of the in vitro Kai system and the calculations that we have performed.
We will closely follow the outline of the main text.


title:
Effects of Langmuir Kinetics of Two-Lane Totally Asymmetric Exclusion
  Processes in Protein Traffic

abstract:
  In this paper, we study a two-lane totally asymmetric simple exclusion
process (TASEP) coupled with random attachment and detachment of particles
(Langmuir kinetics) in both lanes under open boundary conditions. Our model can
describe the directed motion of molecular motors, attachment and detachment of
motors, and free inter-lane transition of motors between filaments. In this
paper, we focus on some finite-size effects of the system because normally the
sizes of most real systems are finite and small (e.g., size $\leq 10,000$). A
special finite-size effect of the two-lane system has been observed, which is
that the density wall moves left first and then move towards the right with the
increase of the lane-changing rate. We called it the jumping effect. We find
that increasing attachment and detachment rates will weaken the jumping effect.
We also confirmed that when the size of the two-lane system is large enough,
the jumping effect disappears, and the two-lane system has a similar density
profile to a single-lane TASEP coupled with Langmuir kinetics. Increasing
lane-changing rates has little effect on density and current after the density
reaches maximum. Also, lane-changing rate has no effect on density profiles of
a two-lane TASEP coupled with Langmuir kinetics at a large
attachment/detachment rate and/or a large system size. Mean-field approximation
is presented and it agrees with our Monte Carlo simulations.


title:
On the existence of potential landscape in the evolution of complex
  systems

abstract:
  A recently developed treatment of stochastic processes leads to the
construction of a potential landscape for the dynamical evolution of complex
systems. Since the existence of a potential function in generic settings has
been frequently questioned in literature,herewe study several related
theoretical issues that lie at core of the construction. We showthat the novel
treatment,via a transformation,is closely related to the symplectic structure
that is central in many branches of theoretical physics. Using this insight, we
demonstrate an invariant under the transformation. We further explicitly
demonstrate, in one-dimensional case, the contradistinction among the new
treatment to those of Ito and Stratonovich, as well as others.Our results
strongly suggest that the method from statistical physics can be useful in
studying stochastic, complex systems in general.

categories: q-bio.QM cond-mat.stat-mech cs.IT math.DS math.IT nlin.AO q-bio.MN


title: Monte Carlo Simulation of Age-Dependent Host-Parasite Relations

abstract:
  The death of a biological population is an extreme event which we investigate
here for a host-parasitoid system. Our simulations using the Penna ageing model
show how biological evolution can ``teach'' the parasitoids to avoid extinction
by waiting for the right age of the host. We also show the dependence of
extinction time on the population size.


title: Neural Decision Boundaries for Maximal Information Transmission

abstract:
  We consider here how to separate multidimensional signals into two
categories, such that the binary decision transmits the maximum possible
information transmitted about those signals. Our motivation comes from the
nervous system, where neurons process multidimensional signals into a binary
sequence of responses (spikes). In a small noise limit, we derive a general
equation for the decision boundary that locally relates its curvature to the
probability distribution of inputs. We show that for Gaussian inputs the
optimal boundaries are planar, but for non-Gaussian inputs the curvature is
nonzero. As an example, we consider exponentially distributed inputs, which are
known to approximate a variety of signals from natural environment.


title: Oscillations and temporal signalling in cells

abstract:
  The development of new techniques to quantitatively measure gene expression
in cells has shed light on a number of systems that display oscillations in
protein concentration. Here we review the different mechanisms which can
produce oscillations in gene expression or protein concentration, using a
framework of simple mathematical models. We focus on three eukaryotic genetic
regulatory networks which show "ultradian" oscillations, with time period of
the order of hours, and involve, respectively, proteins important for
development (Hes1), apoptosis (p53) and immune response (NFkB). We argue that
underlying all three is a common design consisting of a negative feedback loop
with time delay which is responsible for the oscillatory behaviour.


title:
An "All Possible Steps" Approach to the Accelerated Use of Gillespie's
  Algorithm

abstract:
  Many physical and biological processes are stochastic in nature.
Computational models and simulations of such processes are a mathematical and
computational challenge. The basic stochastic simulation algorithm was
published by D. Gillespie about three decades ago [D.T. Gillespie, J. Phys.
Chem. {\bf 81}, 2340, (1977)]. Since then, intensive work has been done to make
the algorithm more efficient in terms of running time. All accelerated versions
of the algorithm are aimed at minimizing the running time required to produce a
stochastic trajectory in state space. In these simulations, a necessary
condition for reliable statistics is averaging over a large number of
simulations. In this study I present a new accelerating approach which does not
alter the stochastic algorithm, but reduces the number of required runs. By
analysis of collected data I demonstrate high precision levels with fewer
simulations. Moreover, the suggested approach provides a good estimation of
statistical error, which may serve as a tool for determining the number of
required runs.


title: Shapes of Semiflexible Polymer Rings

abstract:
  The shape of semiflexible polymer rings is studied over their whole range of
flexibility. Investigating the joint distribution of asphericity and nature of
asphericity as well as their respective averages we find two distinct shape
regimes depending on the flexibility of the polymer. For small perimeter to
persistence length the fluctuating rings exhibit only planar, elliptical
configurations. At higher flexibilities three dimensional, crumpled structures
arise. Analytic calculations for tight polymer rings confirm an elliptical
shape in the stiff regime.


title:
From a quantum mechanical description of the assembly processes in
  microtubules to their semiclassical nonlinear dynamics

abstract:
  In this paper a quantum mechanical description of the assembly/disassembly
process for microtubules is proposed. We introduce creation and annihilation
operators that raise or lower the microtubule length by a tubulin layer.
Following that, the Hamiltonian and corresponding equations of motion are
derived that describe the dynamics of microtubules. These Heisenberg-type
equations are then transformed to semi-classical equations using the method of
coherent structures. The latter equations are very similar to the
phenomenological equations that describe dynamic instability of microtubules in
a tubulin solution.


title:
Is Adaptive Landscape in Biology a Metaphor or a Quantitative Concept?
  or Both?

abstract:
  Some biologists accept Wright's adaptive landscape idea, believing it is one
of most profound concepts in evolutionary dynamics. Some wouldn't, believing
that "the idea that there is such a quantity remains one of the most widely
held popular misconceptions about evolution." The two groups usually have very
limited communication with each other. Sometimes such isolation can be good,
because it protects budding ideas in a harsh environment. Thanks to the
theoretical and experimental progress during past few years, time may have
arrived to consider both sides seriously. Present letter is a small attempt to
bridge this gap.


title:
Int\'er\^ets et limites de l'approche mol\'eculaire pour aborder la
  biog\'eographie et la sp\'eciation : l'exemple de quelques Mammif\`eres
  d'Afrique tropicale

abstract:
  We attempted to test biogeographic hypotheses proposed for the evolution of
tropical faunas using mitochondrial DNA sequences of selected African mammalian
taxa (Insectivora, Rodentia and Primates). 1/ we constructed a molecular
phylogeny of taxa in order to ascertain their monophyly and calibrate a
molecular clock; 2/ we analysed and compared the phylogeographic patterns of
five forest-dwelling taxa; 3/ we evaluated the evolutionary processes
potentially involved in the speciation of cercopithecine Primates. Phylogenetic
results confirm that gene history is not necessarily the same as organism
history. Phylogeographic analyses reveal distinct patterns for each model
species, suggesting differences in initial distributions or different responses
to the same events. They indicate a role of Plio-Pleistocene vicariance events
in the intra-specific diversification of small mammals. Thus, genetic
divergence would be much older than the last glacial cycles. In cercopithecine
Primates, speciation would have been predominantly allopatric and driven by
Miocene and Pliocene vicariance events. Altogether, results give support to the
refuge hypothesis, without excluding the riverine barrier nor the
paleogrographic ones. They emphasize the role of paleo-ecological changes in
generating diversity and of the main riverine barriers in shaping the present
distribution of that diversity.


title: Global statistical analysis of the protein homology network

abstract:
  The similarity between protein sequences is a directly and easly computed
quantity from which to deduce information about their evolutionary distance and
to detect homologous proteins. The SIMAP database -- Similarity Matrix of
Proteins -- provides a pre-computed similarity matrix covering the similarity
space formed by about all publicly available amino acid sequences from public
databases and completely sequenced genomes. From SIMAP we construct the protein
homology network, where the proteins are the nodes and the links represent
homology relationships. With more than 5 million nodes and about 70 10^9 edges
it is the greatest protein homology network ever been builded. We describe the
basic features and we perform a global statistical analysis of the network.
Starting from the Smith-Waterman similarity score, we define for each edge a
weight w to measure the similarity distance between two nodes. Keeping only
edges with a weigth greater than a minimal w_min, and by varying w_min we build
a family of networks with different degree of similarity. We investigate the
distribution of connected components (clusters) of the networks at different
w_min and in particular we find a behaviour similar to a phase transition
guided by the formation of a giant component. Moreover we study selected
sequence features and protein domains of protein pairs that connect different
clusters in the networks at different level of similarity. We observed
specific, non-random distributions of the protein features and domains for
proteins connecting clusters at certain weight intervals.


title: A simple stochastic model for the evolution of protein lengths

abstract:
  We analyse a simple discrete-time stochastic process for the theoretical
modeling of the evolution of protein lengths. At every step of the process a
new protein is produced as a modification of one of the proteins already
existing and its length is assumed to be random variable which depends only on
the length of the originating protein. Thus a Random Recursive Trees (RRT) is
produced over the natural integers. If (quasi) scale invariance is assumed, the
length distribution in a single history tends to a lognormal form with a
specific signature of the deviations from exact gaussianity. Comparison with
the very large SIMAP protein database shows good agreement.


title: The microtubule transistor

abstract:
  I point out the similarity between the microtubule experiment reported by
Priel et al [Biophys. J. 90, 4639 (2006)] and the ZnO nanowire experiment of
Wang et al [Nanolett. 6, 2768 (2006)]. It is quite possible that MTs are
similar to a piezoelectric field effect transistor for which the role of the
control gate electrode is played by the piezo-induced electric field across the
width of the MT walls and their elastic bending features


title:
Quantitative Characterization of Combinatorial Transcriptional Control
  of the Lactose Operon of E. coli

abstract:
  It is the goal of systems biology to understand the behavior of the whole in
terms of the knowledge of the parts. This is hard to achieve in many cases due
to the difficulty of characterizing the many constituents and their complex web
of interactions involved in a biological system. The lac promoter of E. coli
offers a possibility of confronting system-leve properties of transcriptional
regulation with the known biochemistry of the molecular constituents and their
mutual interactions. Such confrontations can reveal previously unknown
constituents and interactions, as well as offering new insight into how the
components work together as a whole. Here we study the combinatorial control of
the lac promoter by the regulators LacR and CRP. A previous in vivo study
[Setty et al., PNAS 100: 7702-7 (2003)] found gross disagreement between the
observed promoter activites and the expected behavior based on the known
molecular mechanisms. We repeated the study by identifying and removing several
extraneous factors which significantly modulated the expression of the lac
promoter. Through quantitative, systematic characterization of promoter
activity for a number of key mutants and guided by the thermodynamic model of
transcriptional gene regulation, we are able to account for the combinatorial
control of the lac promoter quantitatively, in terms of a cooperative
interaction between CRP and LacR-mediated DNA looping. Specifically, our
analysis indicates that the sensitivity of the inducer response results from
LacR-mediated DNA looping, which is significantly enhanced by CRP.


title: Population dynamics with a stable efficient equilibrium

abstract:
  We propose a game-theoretic dynamics of a population of replicating
individuals. It consists of two parts: the standard replicator one and a
migration between two different habitats. We consider symmetric two-player
games with two evolutionarily stable strategies: the efficient one in which the
population is in a state with a maximal payoff and the risk-dominant one where
players are averse to risk. We show that for a large range of parameters of our
dynamics, even if the initial conditions in both habitats are in the basin of
attraction of the risk-dominant equilibrium (with respect to the standard
replication dynamics without migration), in the long run most individuals play
the efficient strategy.


title: A mathematical model for the therapy of the HIV infection

abstract:
  In this paper we consider the evolution of the HIV infection under a highly
effective treatment based on a combination of RTI and/or PI drugs. This is
usually modelled with a set of ODEs where the drug efficacy is a constant. In
this paper we consider the treatment efficacy as a dynamic variable which
evolves during the treatment. To model the dynamics of the drug efficacy we use
an evolutive type assumption. The resulting set of ODEs are able to reproduce
the typical pattern of the illness evolution under treatment: a period of
remission, which can last several years, followed by a progressive
recrudescence and a viral rebound.


title:
The regulatory network of E. coli metabolism as a boolean dynamical
  system exhibits both homeostasis and flexibility of response

abstract:
  Elucidating the architecture and dynamics of large scale genetic regulatory
networks of cells is an important goal in systems biology. We study the system
level dynamical properties of the genetic network of Escherichia coli that
regulates its metabolism, and show how its design leads to biologically useful
cellular properties. Our study uses the database (Covert et al., Nature 2004)
containing 583 genes and 96 external metabolites which describes not only the
network connections but also the boolean rule at each gene node that controls
the switching on or off of the gene as a function of its inputs. We have
studied how the attractors of the boolean dynamical system constructed from
this database depend on the initial condition of the genes and on various
environmental conditions corresponding to buffered minimal media. We find that
the system exhibits homeostasis in that its attractors, that turn out to be
fixed points or low period cycles, are highly insensitive to initial conditions
or perturbations of gene configurations for any given fixed environment. At the
same time the attractors show a wide variation when external media are varied
implying that the system mounts a highly flexible response to changed
environmental conditions. The regulatory dynamics acts to enhance the cellular
growth rate under changed media. Our study shows that the reconstructed genetic
network regulating metabolism in {\it E. coli} is hierarchical, modular, and
largely acyclic, with environmental variables controlling the root of the
hierarchy. This architecture makes the cell highly robust to perturbations of
gene configurations as well as highly responsive to environmental changes. The
twin properties of homeostasis and response flexibility are achieved by this
dynamical system even though it is not close to the edge of chaos.


title: Robust protein-protein interactions in crowded cellular environments

abstract:
  The capacity of proteins to interact specifically with one another underlies
our conceptual understanding of how living systems function. Systems-level
study of specificity in protein-protein interactions is complicated by the fact
that the cellular environment is crowded and heterogeneous; interaction pairs
may exist at low relative concentrations and thus be presented with many more
opportunities for promiscuous interactions compared to specific interaction
possibilities. Here we address these questions using a simple computational
model that includes specifically designed interacting model proteins immersed
in a mixture containing hundreds of different unrelated ones; all of them
undergo simulated diffusion and interaction. We find that specific complexes
are quite robust to interference from promiscuous interaction partners, only in
the range of temperatures Tdesign>T>Trand. At T>Tdesign specific complexes
become unstable, while at T<Trand formation of specific complexes is suppressed
by promiscuous interactions. Specific interactions can form only if
Tdesign>Trand. This condition requires an energy gap between binding energy in
a specific complex and set of binding energies between randomly associating
proteins, providing a general physical constraint on evolutionary selection or
design of specific interacting protein interfaces. This work has implications
for our understanding of how the protein repertoire functions and evolves
within the context of cellular systems.


title: Statistical mechanics unifies different ecological patterns

abstract:
  Recently there has been growing interest in the use of Maximum Relative
Entropy (MaxREnt) as a tool for statistical inference in ecology. In contrast,
here we propose MaxREnt as a tool for applying statistical mechanics to
ecology. We use MaxREnt to explain and predict species abundance patterns in
ecological communities in terms of the most probable behaviour under given
environmental constraints, in the same way that statistical mechanics explains
and predicts the behaviour of thermodynamic systems. We show that MaxREnt
unifies a number of different ecological patterns: (i) at relatively local
scales a unimodal biodiversity-productivity relationship is predicted in good
agreement with published data on grassland communities, (ii) the predicted
relative frequency of rare vs. abundant species is very similar to the
empirical lognormal distribution, (iii) both neutral and non-neutral species
abundance patterns are explained, (iv) on larger scales a monotonic
biodiversity-productivity relationship is predicted in agreement with the
species-energy law, (v) energetic equivalence and power-law self-thinning
behaviour are predicted in resource-rich communities. We identify mathematical
similarities between these ecological patterns and the behaviour of
thermodynamic systems, and conclude that the explanation of ecological patterns
is not unique to ecology but rather reflects the generic statistical behaviour
of complex systems with many degrees of freedom under very general types of
environmental constraints.


title: Evolutionary game theory and population dynamics

abstract:
  Many socio-economic and biological processes can be modeled as systems of
interacting individuals. The behaviour of such systems can be often described
within game-theoretic models. In these lecture notes, we introduce fundamental
concepts of evolutionary game theory and review basic properties of
deterministic replicator dynamics and stochastic dynamics of finite
populations. We discuss stability of equilibria in deterministic dynamics with
migration, time-delay, and in stochastic dynamics of well-mixed populations and
spatial games with local interactions. We analyze the dependence of the
long-run behaviour of a population on various parameters such as the time
delay, the noise level, and the size of the population.


title:
Noise-filtering features of transcription regulation in the yeast S.
  cerevisiae

abstract:
  Transcription regulation is largely governed by the profile and the dynamics
of transcription factors' binding to DNA. Stochastic effects are intrinsic to
this dynamics and the binding to functional sites must be controled with a
certain specificity for living organisms to be able to elicit specific cellular
responses. Specificity stems here from the interplay between binding affinity
and cellular abundancy of transcription factor proteins and the binding of such
proteins to DNA is thus controlled by their chemical potential.
  We combine large-scale protein abundance data in the budding yeast with
binding affinities for all transcription factors with known DNA binding site
sequences to assess the behavior of their chemical potentials. A sizable
fraction of transcription factors is apparently bound non-specifically to DNA
and the observed abundances are marginally sufficient to ensure high
occupations of the functional sites. We argue that a biological cause of this
feature is related to its noise-filtering consequences: abundances below
physiological levels do not yield significant binding of functional targets and
mis-expressions of regulated genes are thus tamed.


title:
Triiodothyronine suppresses humoral immunity but not T-cell-mediated
  immune response in incubating female eiders (Somateria mollissima)

abstract:
  Immunity is believed to share limited resources with other physiological
functions and this may partly account for the fitness costs of reproduction.
Previous studies have shown that the acquired immunity of female common eiders
(Somateria mollissima) is suppressed during the incubation fast. To save
energy, triiodothyronine (T3) is adaptively decreased during fasting in most
bird species, despite T3 levels are maintained throughout incubation in female
eiders. However, the relationship between thyroid hormones and the immune
system is not fully understood. The current study aimed to determine the
endocrine mechanisms that underlie immunosuppression in incubating female
eiders. ...


title:
A network model to investigate structural and electrical properties of
  proteins

abstract:
  One of the main trend in to date research and development is the
miniaturization of electronic devices. In this perspective, integrated
nanodevices based on proteins or biomolecules are attracting a major interest.
In fact, it has been shown that proteins like bacteriorhodopsin and azurin,
manifest electrical properties which are promising for the development of
active components in the field of molecular electronics. Here we focus on two
relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein,
and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most
qualified treatments of Alzheimer disease. Both these proteins exert their
functioning starting with a conformational change of their native structure.
Our guess is that such a change should be accompanied with a detectable
variation of their electrical properties. To investigate this conjecture, we
present an impedance network model of proteins, able to estimate the different
electrical response associated with the different configurations. The model
resolution of the electrical response is found able to monitor the structure
and the conformational change of the given protein. In this respect, rhodopsin
exhibits a better differential response than AChE. This result gives room to
different interpretations of the degree of conformational change and in
particular supports a recent hypothesis on the existence of a mixed state
already in the native configuration of the protein.


title: The Mechanisms of Codon Reassignments in Mitochondrial Genetic Codes

abstract:
  Many cases of non-standard genetic codes are known in mitochondrial genomes.
We carry out analysis of phylogeny and codon usage of organisms for which the
complete mitochondrial genome is available, and we determine the most likely
mechanism for codon reassignment in each case. Reassignment events can be
classified according to the gain-loss framework. The gain represents the
appearance of a new tRNA for the reassigned codon or the change of an existing
tRNA such that it gains the ability to pair with the codon. The loss represents
the deletion of a tRNA or the change in a tRNA so that it no longer translates
the codon. One possible mechanism is Codon Disappearance, where the codon
disappears from the genome prior to the gain and loss events. In the
alternative mechanisms the codon does not disappear. In the Unassigned Codon
mechanism, the loss occurs first, whereas in the Ambiguous Intermediate
mechanism, the gain occurs first. Codon usage analysis gives clear evidence of
cases where the codon disappeared at the point of the reassignment and also
cases where it did not disappear. Codon disappearance is the probable
explanation for stop to sense reassignments and a small number of reassignments
of sense codons. However, the majority of sense to sense reassignments cannot
be explained by codon disappearance. In the latter cases, by analysis of the
presence or absence of tRNAs in the genome and of the changes in tRNA
sequences, it is sometimes possible to distinguish between the Unassigned Codon
and Ambiguous Intermediate mechanisms. We emphasize that not all reassignments
follow the same scenario and that it is necessary to consider the details of
each case carefully.


title: Evolutionary and Ecological Trees and Networks

abstract:
  Evolutionary relationships between species are usually represented in
phylogenies, i.e. evolutionary trees, which are a type of networks. The
terminal nodes of these trees represent species, which are made of individuals
and populations among which gene flow occurs. This flow can also be represented
as a network. In this paper we briefly show some properties of these complex
networks of evolutionary and ecological relationships. First, we characterize
large scale evolutionary relationships in the Tree of Life by a degree
distribution. Second, we represent genetic relationships between individuals of
a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum
Spanning Tree. Finally, relationships among plant shoots inside populations are
represented as networks of genetic similarity.


title: A four-party unlockable bound-entangled state

abstract:
  I present a four-party unlockable bound-entangled state, that is, a
four-party quantum state which cannot be written in a separable form and from
which no pure entanglement can be distilled by local quantum operations and
classical communication among the parties, and yet when any two of the parties
come together in the same laboratory they can perform a measurement which
enables the other two parties to create a pure maximally entangled state
between them without coming together. This unlocking ability can be viewed in
two ways, as either a determination of which Bell state is shared in the
mixture, or as a kind of quantum teleportation with cancellation of Pauli
operators.


title:
Coherent states, displaced number states and Laguerre polynomial states
  for su(1,1) Lie algebra

abstract:
  The ladder operator formalism of a general quantum state for su(1,1) Lie
algebra is obtained. The state bears the generally deformed oscillator
algebraic structure. It is found that the Perelomov's coherent state is a
su(1,1) nonlinear coherent state. The expansion and the exponential form of the
nonlinear coherent state are given. We obtain the matrix elements of the
su(1,1) displacement operator in terms of the hypergeometric functions and the
expansions of the displaced number states and Laguerre polynomial states are
followed. Finally some interesting su(1,1) optical systems are discussed.


title: Photon-added one-photon and two-photon nonlinear coherent states

abstract:
  From the photon-added one-photon nonlinear coherent states $a^{\dagger
m}|\alpha,f>$, we introduce a new type of nonlinear coherent states with
negative values of $m.$ The nonlinear coherent states corresponding to the
positive and negative values of $m$ are shown to be the result of nonunitarily
deforming the number states $|m>$ and $|0>$, respectively. As an example, we
study the sub-Poissonian statistics and squeezing effects of the photon-added
geometric states with negative values of $m$ in detail. Finally we investigate
the photon-added two-photon nonlinear coherent states and find that they are
still the two-photon nonlinear coherent states with certain nonlinear
functions.


title: The Role of the Environment in Molecular Systems

abstract:
  The work is devoted to the investigation of the influence of a heat bath on
the physical processes in a quantum system. We use the density matrix theory as
one of the most powerfool tool for investigation of quantum relaxation. In the
beginning of the work (chapter 2) we mention and recall the most important
steps of derivation of the equation of motion for the reduced density matrix
(master equation) for an arbitrary quantum system in diabatic representation
interacting with the environment modeled by a set of independent harmonic
oscillators. Chapter 3 deals with the question of the border between classical
and quantum effects and reports on a study of the environmental influence on
the time evolution of a coherent state or the superposition of two coherent
states of a harmonic oscillator as a simple system displaying the peculiarities
of the transition from quantum to classical regime. Chapters 4 and 5 concern
the electron transfer (ET) problem, namely the mathematical description of the
ET in molecular zinc-porphyrin-quinone complexes modeling artificial
photosynthesis (chapter 4) and photoinduced processes in the porphyrin triad
(chapter 5). Each chapter starts with an introduction and ends with a brief
summary. The main achievements of the present work are summarized in the
Conclusions.


title:
The class of languages recognizable by 1-way quantum finite automata is
  not closed under union

abstract:
  In this paper we develop little further the theory of quantum finite automata
(QFA). There are already few properties of QFA known, that deterministic and
probabilistic finite automata do not have e.g. they cannot recognize all
regular languages. In this paper we show, that class of languages recognizable
by QFA is not closed under union, even not under any Boolean operation, where
both arguments are significant.


title:
Comment on "Quantum Phase Shift Caused by Spatial Confinement", by B.E.
  Allman et al

abstract:
  The analysis of phase shifts in executed and proposed interferometry
experiments on photons and neutrons neglected forces exerted at the boundaries
of spatial constrictions. When those forces are included it is seen that the
observed phenomena are not in fact geometric in nature. A new proposal to be
published by Allman et al. avoids that pitfall.


title:
Universal quantum limits on single channel information, entropy and heat
  flow

abstract:
  We show that the recently discovered universal upper bound on the thermal
conductance of a single channel comprising particles obeying arbitrary
fractional statistics is in fact a consequence of a more general universal
upper bound, involving the averaged entropy and energy currents of a single
channel connecting heat reservoirs with arbitrary temperatures and chemical
potentials. The latter upper bound in turn leads, via Holevo's theorem, to a
universal (i.e., statistics independent) upper bound on the optimum capacity
for classical information transmission down a single, wideband quantum channel.


title: Optical Realization of Quantum Gambling Machine

abstract:
  Quantum gambling --- a secure remote two-party protocol which has no
classical counterpart --- is demonstrated through optical approach. A photon is
prepared by Alice in a superposition state of two potential paths. Then one
path leads to Bob and is split into two parts. The security is confirmed by
quantum interference between Alice's path and one part of Bob's path. It is
shown that a practical quantum gambling machine can be feasible by this way.


title: New strategy for suppressing decoherence in quantum computation

abstract:
  Controlable strong interaction of the qubit's bath with an external system
(i.e. with the bath's environment) allows for choosing the conditions under
which the decoherence of the qubit's states can be substantially decreased (in
a certain limit: completely avoided). By "substantially decreased" we mean that
the correlations which involve the bath's states prove negligible, while the
correlations between the qubit's and the environment's states can be made
ineffective during a comparatively long time interval. So, effectively, one may
choose the conditions under which, for sufficiently long time interval, the
initial state of "qubit + bath" remains unchanged, thus removing any kind of
the errors. The method has been successfully employed in the (simplified) model
of the solid-state-nuclear quantum computer (proposed by Kane).