title:
Bioinformatics analysis of experimentally determined protein complexes
  in the yeast, S. cerevisiae

abstract:
  Many important cellular functions are implemented by protein complexes that
act as sophisticated molecular machines of varying size and temporal stability.
Here we demonstrate quantitatively that protein complexes in the yeast,
Saccharomyces cerevisiae, are comprised of a core in which subunits are highly
coexpressed, display the same deletion phenotype (essential or non-essential)
and share identical functional classification and cellular localization. This
core is surrounded by a functionally mixed group of proteins, which likely
represent short-lived- or spurious attachments. The results allow us to define
the deletion phenotype and cellular task of most known complexes, and to
identify with high confidence the biochemical role of hundreds of proteins with
yet unassigned functionality.


title:
Hydration Water Dynamics and Instigation of Protein Structural
  Relaxation

abstract:
  The molecular mechanism of the solvent motion that is required to instigate
the protein structural relaxation above a critical hydration level or
transition temperature has yet to be determined. In this work we use
quasi-elastic neutron scattering (QENS) and molecular dynamics simulation to
investigate hydration water dynamics near a greatly simplified protein surface.
We consider the hydration water dynamics near the completely deuterated
N-acetyl-leucine-methylamide (NALMA) solute, a hydrophobic amino acid side
chain attached to a polar blocked polypeptide backbone, as a function of
concentration between 0.5M-2.0M, under ambient conditions. In this
Communication, we focus our results of hydration dynamics near a model protein
surface on the issue of how enzymatic activity is restored once a critical
hydration level is reached, and provide a hypothesis for the molecular
mechanism of the solvent motion that is required to trigger protein structural
relaxation when above the hydration transition.


title:
Auto-reverse nuclear migration in bipolar mammalian cells on
  micropatterned surfaces

abstract:
  A novel assay based on micropatterning and time-lapse microscopy has been
developed for the study of nuclear migration dynamics in cultured mammalian
cells. When cultured on 10-20 um wide adhesive stripes, the motility of C6
glioma and primary mouse fibroblast cells is diminished. Nevertheless, nuclei
perform an unexpected auto-reverse motion: when a migrating nucleus approaches
the leading edge, it decelerates, changes the direction of motion and
accelerates to move toward the other end of the elongated cell. During this
process cells show signs of polarization closely following the direction of
nuclear movement. The observed nuclear movement requires a functioning
microtubular system, as revealed by experiments disrupting the main
cytoskeletal components with specific drugs. On the basis of our results we
argue that auto-reverse nuclear migration is due to forces determined by the
interplay of microtubule dynamics and the changing position of the microtubule
organizing center as the nucleus reaches the leading edge. Our assay
recapitulates specific features of nuclear migration (cell polarization,
oscillatory nuclear movement), while allows the systematic study of a large
number of individual cells. In particular, our experiments yielded the first
direct evidence of reversive nuclear motion in mammalian cells, induced by
attachment constraints.


title:
How does connectivity between cortical areas depend on brain size?
  Implications for efficient computation

abstract:
  A formula for an average connectivity between cortical areas in mammals is
derived. Based on comparative neuroanatomical data, it is found, surprisingly,
that this connectivity is either only weakly dependent or independent of brain
size. It is discussed how this formula can be used to estimate the average
length of axons in white matter. Other allometric relations, such as cortical
patches and area sizes vs. brain size, are also provided. Finally, some
functional implications, with an emphasis on efficient cortical computation,
are discussed as well.


title:
Cytokinesis: the initial linear phase crosses over to a multiplicity of
  non-linear endings

abstract:
  We investigate the final stage of cytokinesis in two types of amoeba,
pointing out the existence of biphasic furrow contraction. The first phase is
characterized by a constant contraction rate, is better studied, and seems
universal to a large extent. The second phase is more diverse. In Dictyostelium
discoideum the transition involves a change in the rate of contraction, and
occurs when the width of the cleavage furrow is comparable to the height of the
cell. In Entamoeba invadens the contractile ring carries the cell through the
first phase, but cannot complete the second stage of cytokinesis. As a result,
a cooperative mechanism has evolved in that organism, where a neighboring
amoeba performs directed motion towards the dividing cell, and physically
causes separation by means of extending a pseudopod. We expand here on a
previous report of this novel chemotactic signaling mechanism.


title:
Phase transition and selection in a four-species cyclic Lotka-Volterra
  model

abstract:
  We study a four species ecological system with cyclic dominance whose
individuals are distributed on a square lattice. Randomly chosen individuals
migrate to one of the neighboring sites if it is empty or invade this site if
occupied by their prey. The cyclic dominance maintains the coexistence of all
the four species if the concentration of vacant sites is lower than a threshold
value. Above the treshold, a symmetry breaking ordering occurs via growing
domains containing only two neutral species inside. These two neutral species
can protect each other from the external invaders (predators) and extend their
common territory. According to our Monte Carlo simulations the observed phase
transition is equivalent to those found in spreading models with two equivalent
absorbing states although the present model has continuous sets of absorbing
states with different portions of the two neutral species. The selection
mechanism yielding symmetric phases is related to the domain growth process
whith wide boundaries where the four species coexist.


title: Fold-Hopf Bursting in a Model for Calcium Signal Transduction

abstract:
  We study a recent model for calcium signal transduction. This model displays
spiking, bursting and chaotic oscillations in accordance with experimental
results. We calculate bifurcation diagrams and study the bursting behaviour in
detail. This behaviour is classified according to the dynamics of separated
slow and fast subsystems. It is shown to be of the Fold-Hopf type, a type which
was previously only described in the context of neuronal systems, but not in
the context of signal transduction in the cell.


title: Complexity in the Immune System

abstract:
  The immune system is a real-time example of an evolving system that navigates
the essentially infinite complexity of protein sequence space. How this system
responds to disease and vaccination is discussed. Of particular focus is the
case when vaccination leads to increased susceptibility to disease, a
phenomenon termed original antigenic sin. A physical theory of protein
evolution to explain limitations in the immune system response to vaccination
and disease is discussed, and original antigenic sin is explained as stemming
from localization of the immune system response in antibody sequence space.
This localization is a result of the roughness in sequence space of the evolved
antibody affinity constant for antigen and is observed for diseases with high
year-to-year mutation rates, such as influenza.


title:
Thermal denaturation and folding rates of single domain proteins: size
  matters

abstract:
  We analyze the dependence of thermal denaturation transition and folding
rates of globular proteins on the number of amino acid residues, N. Using
lattice Go models we show that DeltaT/T_F ~ N^-1, where T_F is the folding
transition temperature and DeltaT is the folding transition width. This finding
is consistent with finite size effects expected for the systems undergoing a
phase transition from a disordered to an ordered phase. The dependence of the
folding rates k_F on N for lattice models and the dataset of 57 proteins and
peptides shows that k_F = k_F^0 exp(-CN^beta) provides a good fit, if 0 < beta
<= 2/3 and C is a constant. We find that k_F = k_F^0 exp(-1.1N^0.5) with k_F^0
=(0.4x10^-6 s)^-1 can estimate optimal protein folding rates to within an order
of magnitude in most cases. By using this fit for a set of proteins with
beta-sheet topology we find that k_F^0 is approximately equal to k_U^0, the
prefactor for unfolding rates. The maximum ratio of k_U^0/k_F^0 is 10 for this
class of proteins.


title:
Communication on the letter: "Evolutionary Conservation of Motif
  Constituents in the Yeast Protein Interaction Network."

abstract:
  Former work on an application of order-disorder theory is recalled as a
vehicle to add further development and significance to the recent paper on
motifs in protein interactions.


title: A covariance kernel for proteins

abstract:
  We propose a new kernel for biological sequences which borrows ideas and
techniques from information theory and data compression. This kernel can be
used in combination with any kernel method, in particular Support Vector
Machines for protein classification. By incorporating prior biological
assumptions on the properties of amino-acid sequences and using a Bayesian
averaging framework, we compute the value of this kernel in linear time and
space, benefiting from previous achievements proposed in the field of universal
coding. Encouraging classification results are reported on a standard protein
homology detection experiment.


title: Asymmetry in the shapes of folded and denatured states of proteins

abstract:
  The asymmetry in the shapes of folded and unfolded states are probed using
two parameters, one being a measure of the sphericity and the other that
describes the shape. For the folded states, whose interiors are densely packed,
the radii of gyration (Rg) and these two parameters are calculated using the
coordinates of the experimentally determined structures. Although Rg scales as
expected for maximally compact structures, the distributions of the shape
parameters show that there is considerable asymmetry in the shapes of folded
structures. The degree of asymmetry is greater for proteins that form
oligomers. Analysis of the two- and three-body contacts in the native
structures shows that the presence of near equal number of contacts between
backbone and side-chains and between side-chains gives rise to dense packing.
We suggest that proteins with relatively large values of shape parameters can
tolerate volume mutations without greatly affecting the network of contacts or
their stability. To probe shape characteristics of denatured states we have
developed a model of a WW-like domain. The shape parameters, which are
calculated using Langevin simulations, change dramatically in the course of
coil to globule transition. Comparison of the values of shape parameters
between the globular state and the folded state of WW domain shows that both
energetic (especially dispersion in the hydrophobic interactions) and steric
effects are important in determining packing in proteins.


title:
Evolutionary conservation of motif constituents within the yeast protein
  interaction network

abstract:
  Understanding why some cellular components are conserved across species,
while others evolve rapidly is a key question of modern biology. Here we
demonstrate that in S. cerevisiae proteins organized in cohesive patterns of
interactions are conserved to a significantly higher degree than those that do
not participate in such motifs. We find that the conservation of proteins
within distinct topological motifs correlates with the motif's
inter-connectedness and function and also depends on the structure of the
overall interactome topology. These findings indicate that motifs may represent
evolutionary conserved topological units of cellular networks molded in
accordance with the specific biological function in which they participate.


title: Pattern Excitation-Based Processing: The Music of The Brain

abstract:
  An approach to information processing based on the excitation of patterns of
activity by non-linear active resonators in response to their input patterns is
proposed. Arguments are presented to show that any computation performed by a
conventional Turing machine-based computer, called T-machine in this paper,
could also be performed by the pattern excitation-based machine, which will be
called P-machine. A realization of this processing scheme by neural networks is
discussed. In this realization, the role of the resonators is played by neural
pattern excitation networks, which are the neural circuits capable of exciting
different spatio-temporal patterns of activity in response to different inputs.
Learning in the neural pattern excitation networks is also considered. It is
shown that there is a duality between pattern excitation and pattern
recognition neural networks, which allows to create new pattern excitation
modes corresponding to recognizable input patterns, based on Hebbian learning
rules. Hierarchically organized, such networks can produce complex behavior.
Animal behavior, human language and thought are treated as examples produced by
such networks.


title:
Protein secondary structure prediction by combining hidden Markov models
  and sliding window scores

abstract:
  Instead of conformation states of single residues, refined conformation
states of quintuplets are proposed to reflect conformation correlation. Simple
hidden Markov models combining with sliding window scores are used for
predicting secondary structure of a protein from its amino acid sequence. Since
the length of protein conformation segments varies in a narrow range, we ignore
the duration effect of the length distribution. The window scores for residues
are a window version of the Chou-Fasman propensities estimated under an
approximation of conditional independency. Different window widths are
examined, and the optimal width is found to be 17. A high accuracy about 70% is
achieved.


title: Random model for RNA interference yields scale free network

abstract:
  We introduce a random bit-string model of post-transcriptional genetic
regulation based on sequence matching. The model spontaneously yields a scale
free network with power law scaling with $ \gamma=-1$ and also exhibits
log-periodic behaviour. The in-degree distribution is much narrower, and
exhibits a pronounced peak followed by a Gaussian distribution. The network is
of the smallest world type, with the average minimum path length independent of
the size of the network, as long as the network consists of one giant cluster.
The percolation threshold depends on the system size.


title:
Upstream Plasticity and Downstream Robustness in Evolution of Molecular
  Networks

abstract:
  Evolving biomolecular networks have to combine the stability against
perturbations with flexibility allowing their constituents to assume new roles
in the cell. Gene duplication followed by functional divergence of associated
proteins is a major force shaping molecular networks in living organisms.
Recent availability of system-wide data for yeast S. Cerevisiae allow us to
access the effects of gene duplication on robustness and plasticity of
molecular networks. We demonstrate that the upstream transcriptional regulation
of duplicated genes diverges fast, losing on average 4% of their common
transcription factors for every 1% divergence of their amino acid sequences. In
contrast, the set of physical interaction partners of their protein products
changes much slower. The relative stability of downstream functions of
duplicated genes, is further corroborated by their ability to substitute for
each other in gene knockout experiments. We believe that the combination of the
upstream plasticity and the downstream robustness is a general feature
determining the evolvability of molecular networks.


title:
Statistical analysis of the spatial distribution of operons in the
  transcriptional regulation network of Escherichia coli

abstract:
  We have performed a statistical analysis of the spatial distribution of
operons in the transcriptional regulation network of Escherichia coli. The
analysis reveals that operons that regulate each other and operons that are
coregulated tend to lie next to each other on the genome. Moreover, these pairs
of operons tend to be transcribed in diverging directions. This spatial
arrangement of operons allows the upstream regulatory regions to interfere with
each other. This affords additional regulatory control, as illustrated by a
mean-field analysis of a feed-forward loop. Our results suggest that regulatory
control can provide a selection pressure that drives operons together in the
course of evolution.


title: A graph model for the evolution of specificity in humoral immunity

abstract:
  The immune system protects the body against health-threatening entities,
known as antigens, through very complex interactions involving the antigens and
the system's own entities. One remarkable feature resulting from such
interactions is the immune system's ability to improve its capability to fight
antigens commonly found in the individual's environment. This adaptation
process is called the evolution of specificity. In this paper, we introduce a
new mathematical model for the evolution of specificity in humoral immunity,
based on Jerne's functional, or idiotypic, network. The evolution of
specificity is modeled as the dynamic updating of connection weights in a graph
whose nodes are related to the network's idiotypes. At the core of this
weight-updating mechanism are the increase in specificity caused by clonal
selection and the decrease in specificity due to the insertion of uncorrelated
idiotypes by the bone marrow. As we demonstrate through numerous computer
experiments, for appropriate choices of parameters the new model correctly
reproduces, in qualitative terms, several immune functions.


title: The Evolution of tRNA-Leu Genes in Animal Mitochondrial Genomes

abstract:
  Animal mitochondrial genomes usually have two transfer RNAs for Leucine: one,
with anticodon UAG, translates the four-codon family CUN, whilst the other,
with anticodon UAA, translates the two-codon family UUR. These two genes must
differ at the third anticodon position, but in some species the genes differ at
many additional sites, indicating that these genes have been independent for a
long time. Duplication and deletion of genes in mitochondrial genomes occurs
frequently during the evolution of the Metazoa. If a tRNA-Leu gene were
duplicated and a substitution occurred in the anticodon, this would effectively
turn one type of tRNA into the other. The original copy of the second tRNA type
might then be lost by a deletion elsewhere in the genome. There are several
groups of species in which the two tRNA-Leu genes occur next to one another (or
very close) on the genome, which suggests that tandem duplication has occurred.
Here we use RNA-specific phylogenetic methods to determine evolutionary trees
for both genes. We present evidence that the process of duplication, anticodon
mutation and deletion of tRNA-Leu genes has occurred at least five times during
the evolution of the Metazoa - once in the common ancestor of all Protostomes,
once in the common ancestor of Echinoderms and Hemichordates, once in the
hermit crab, and twice independently in Molluscs.


title:
Localization and extinction of bacterial populations under inhomogeneous
  growth conditions

abstract:
  The transition from localized to systemic spreading of bacteria, viruses and
other agents is a fundamental problem that spans medicine, ecology, biology and
agriculture science. We have conducted experiments and simulations in a simple
one-dimensional system to determine the spreading of bacterial populations that
occurs for an inhomogeneous environment under the influence of external
convection. Our system consists of a long channel with growth inhibited by
uniform UV illumination except in a small ``oasis'', which is shielded from the
UV light. To mimic blood flow or other flow past a localized infection, the
oasis is moved with a constant velocity through the UV-illuminated ``desert''.
The experiments are modeled with a convective reaction-diffusion equation. In
both the experiment and model, localized or extinct populations are found to
develop, depending on conditions, from an initially localized population. The
model also yields states where the population grows everywhere. Further, the
model reveals that the transitions between localized, extended, and extinct
states are continuous and non-hysteretic. However, it does not capture the
oscillations of the localized population that are observed in the experiment.


title: Pattern overlapping decomposition by Cumulative Local Cross-Correlation

abstract:
  Background
  Nucleotide sequences contain multiple codes responsible for organism's
functioning and structure. They can be investigated by various signal
processing methods. These techniques are well suited for indication of
frequently encountered sequence motifs (i.e., repeats). However, if there are
two or more codes containing the same motif, the local nucleotide distribution
(i.e., profile), resulting from sequence alignment by the motif position, will
represent overlapping of the code patterns.
  Results
  The novel algorithm for decomposition of pattern overlapping is proposed. It
is capable to work with dispersed repeats as well. The algorithm is based on
cross-correlation procedure applied locally in a cumulative fashion. Its
sensitivity was tested on human genomic sequences.
  Conclusions
  Cumulative Local Cross-Correlation was successfully used to decompose
overlapping of nucleotide patterns in human genomic sequences. Being very
general technique (as general as cross-correlation), it can be easily adopted
in other signal processing applications and naturally extended for
multidimensional cases.
  Software implementation of the algorithm is available on request from the
authors.


title: Protein secondary structure: Entropy, correlations and prediction

abstract:
  Is protein secondary structure primarily determined by local interactions
between residues closely spaced along the amino acid backbone, or by non-local
tertiary interactions? To answer this question we have measured the entropy
densities of primary structure and secondary structure sequences, and the local
inter-sequence mutual information density. We find that the important
inter-sequence interactions are short ranged, that correlations between
neighboring amino acids are essentially uninformative, and that only 1/4 of the
total information needed to determine the secondary structure is available from
local inter-sequence correlations. Since the remaining information must come
from non-local interactions, this observation supports the view that the
majority of most proteins fold via a cooperative process where secondary and
tertiary structure form concurrently. To provide a more direct comparison to
existing secondary structure prediction methods, we construct a simple hidden
Markov model (HMM) of the sequences. This HMM achieves a prediction accuracy
comparable to other single sequence secondary structure prediction algorithms,
and can extract almost all of the inter-sequence mutual information. This
suggests that these algorithms are almost optimal, and that we should not
expect a dramatic improvement in prediction accuracy. However, local
correlations between secondary and primary structure are probably of
under-appreciated importance in many tertiary structure prediction methods,
such as threading.


title: Why humans die -- an unsolved biological problem

abstract:
  Mortality is an instrument of natural selection. Evolutionary motivated
theories imply its irreversibility and life history dependence. This is
inconsistent with mortality data for protected populations. Accurate analysis
yields mortality law, which is specific for their evolutionary unprecedented
conditions, yet universal for species as evolutionary remote as humans and
flies. The law is exact, instantaneous, reversible, stepwise, and allows for a
rapid (within less than two years for humans) and significant mortality
decrease at any (but very old) age.

categories: q-bio.OT physics.bio-ph q-bio.PE q-bio.QM


title: "Junk" DNA as a genetic decoy

abstract:
  We propose that the evolutionary purpose of junk DNA is to protect the gene.
Mutation agents, such as retro-viruses, hit ``decoy'' DNA most of the time.
Although the argument is far from general, we propose that the percentage of
junk DNA should correlate with the number of retroviruses attacking a given
species. It should also anti-correlate with the ideal mutation rates (higher in
insects than in mammals).


title:
U(1)xU(1)xU(1) symmetry of the Kimura 3ST model and phylogenetic
  branching processes

abstract:
  An analysis of the Kimura 3ST model of DNA sequence evolution is given on the
basis of its continuous Lie symmetries. The rate matrix commutes with a
U(1)xU(1)xU(1) phase subgroup of the group GL(4) of 4x4x4 invertible complex
matrices acting on a linear space spanned by the 4 nucleic acid base letters.
The diagonal `branching operator' representing speciation is defined, and shown
to intertwine the U(1)xU(1)xU(1) action. Using the intertwining property, a
general formula for the probability density on the leaves of a binary tree
under the Kimura model is derived, which is shown to be equivalent to
established phylogenetic spectral transform methods.


title:
Plant defense multigene families: II Evolution of coding sequence and
  differential expression of PR10 genes in Pisum

abstract:
  While it is not possible to directly the observe evolution of multigene
families, the best alternative is to compare orthologous family members among
several closely-related species with varying degrees of reproductive isolation.
Using RT-PCR we show that in pea (Pisum sativum) each member of the
pathogenesis-related PR10 family has a distinct pattern of expression in
response to the fungus Fusarium solani, and in treatment with salicylic acid,
chitosan and abcisic acid. Sequencing reveals that PR10.1, PR10.2 and PR10.3
exist in P. humile, P. elatius and P. fulvum, except that no PR10.2 orthologue
was identified in P. elatius. PR10.1, PR10.2 and PR10.3 appear to have diverged
from a single gene in the common Pisum ancestor. For the recently diverged
PR10.1 and PR10.2, the timing of fungal-induced expression differs greatly
among species. For example, PR10.1 was strongly induced in P. sativum by F.
solani within 8 hours postinoculation (h.p.i.), whereas little PR10.1
expression was seen in pea's closest relative, P. humile, and in the more
distantly-related P. elatius. In P. fulvum, expression did not peak until 48
h.p.i. Expression of the more ancient PR10.4 and PR10.5 genes is more tightly
conserved among Pisum species. These data indicate that expression, as well as
sequence, can evolve rapidly. We hypothesize that changes in differential
expression of multigene family members could provide a source of phenotypic
diversity in populations, which may be of particular importance to
plant/pathogen coevolution.


title:
Different ocular dominance map formation by influence of orientation
  columns in visual cortices

abstract:
  In animal experiments, the observed orientation preference (OP) and ocular
dominance (OD) columns in the visual cortex of the brain show various pattern
types. Here, we show that the different visual map formations in various
species are due to the crossover behavior in anisotropic systems composed of
orientational and scalar components such as easy-plane Heisenberg models. We
predict the transition boundary between different pattern types with the
anisotropy as a main bifurcation parameter, which is consistent with
experimental observations.


title:
Computational identification of transcription factor binding sites by
  functional analysis of sets of genes sharing overrepresented upstream motifs

abstract:
  BACKGROUND: Transcriptional regulation is a key mechanism in the functioning
of the cell, and is mostly effected through transcription factors binding to
specific recognition motifs located upstream of the coding region of the
regulated gene. The computational identification of such motifs is made easier
by the fact that they often appear several times in the upstream region of the
regulated genes, so that the number of occurrences of relevant motifs is often
significantly larger than expected by pure chance. RESULTS: To exploit this
fact, we construct sets of genes characterized by the statistical
overrepresentation of a certain motif in their upstream regions. Then we study
the functional characterization of these sets by analyzing their annotation to
Gene Ontology terms. For the sets showing a statistically significant specific
functional characterization, we conjecture that the upstream motif
characterizing the set is a binding site for a transcription factor involved in
the regulation of the genes in the set. CONCLUSIONS: The method we propose is
able to identify many known binding sites in S. cerevisiae and new candidate
targets of regulation by known transcription factors. Its application to less
well studied organisms is likely to be valuable in the exploration of their
regulatory interaction network.


title:
Enhancement of the stability of genetic switches by overlapping upstream
  regulatory domains

abstract:
  We study genetic switches formed from pairs of mutually repressing operons.
The switch stability is characterised by a well defined lifetime which grows
sub-exponentially with the number of copies of the most-expressed transcription
factor, in the regime accessible by our numerical simulations. The stability
can be markedly enhanced by a suitable choice of overlap between the upstream
regulatory domains. Our results suggest that robustness against biochemical
noise can provide a selection pressure that drives operons, that regulate each
other, together in the course of evolution.


title: Mathematical models of haploinsufficiency

abstract:
  We study simple mathematical models of gene expression to explore the
possible origins of haploinsufficiency (HI). In a diploid organism, each gene
exists in two copies and when one of these is mutated, the amount of proteins
synthesized is reduced and may fall below a threshold level for the onset of
some desired activity. This can give rise to HI, a manifestation of which is in
the form of a disease. We consider both deterministic and stochastic models of
gene expression and suggest possible scenarios for the occurrence of HI in the
two cases. In the stochastic case, random fluctuations around the mean protein
level give rise to a finite probability that the protein level falls below a
threshold. Increased gene copy number and faster gene expression kinetics
reduce the variance around the mean protein level. The difference between slow
and fast gene expression kinetics, as regards response to a signaling gradient,
is further pointed out. The majority of results reported in the paper are
derived analytically.


title:
Computer simulations of history of life: speciation, emergence of
  complex species from simpler organisms, and extinctions

abstract:
  We propose a generic model of eco-systems, with a {\it hierarchical} food web
structure. In our computer simulations we let the eco-system evolve
continuously for so long that that we can monitor extinctions as well as
speciations over geological time scales. {\it Speciation} leads not only to
horizontal diversification of species at any given trophic level but also to
vertical bio-diversity that accounts for the emergence of complex species from
simpler forms of life. We find that five or six trophic levels appear as the
eco-system evolves for sufficiently long time, starting initially from just one
single level. Moreover, the time intervals between the successive collections
of ecological data is so short that we could also study ``micro''-evolution of
the eco-system, i.e., the birth, ageing and death of individual organisms.


title:
Relaxation of DNA curvature by single stranded breaks: Simulations and
  experiments

abstract:
  The recently proposed compressed backbone theory suggested that the intrinsic
curvature in DNA can result from a geometric mismatch between the specific
backbone length and optimal base stacking orientations. It predicted that the
curvature in A-tract repeats can be relaxed by introducing single stranded
breaks (nicks). This effect has not been tested earlier and it would not be
accounted for by alternative models of DNA bending. Here the curvature in a
specifically designed series of nicked DNA fragments is tested experimentally
by gel mobility assays and, simultaneously, by free molecular dynamics
simulations. Single stranded breaks produce virtually no effect upon the gel
mobility of the random sequence DNA. In contrast, nicked A-tract fragments
reveal a regular modulation of curvature depending upon the position of the
strand break with respect to the overall bend. Maximal relaxation is observed
when nicks occur inside A-tracts. The results are partially reproduced in
simulations. Analysis of computed curved DNA conformations reveals a group of
sugar atoms that exhibit reduced backbone length within A-tracts, which can
correspond to the compression hypothesis.


title: Cooperativity in two-state protein folding kinetics

abstract:
  We present a solvable model that predicts the folding kinetics of two-state
proteins from their native structures. The model is based on conditional chain
entropies. It assumes that folding processes are dominated by small-loop
closure events that can be inferred from native structures. For CI2, the src
SH3 domain, TNfn3, and protein L, the model reproduces two-state kinetics, and
it predicts well the average Phi-values for secondary structures. The barrier
to folding is the formation of predominantly local structures such as helices
and hairpins, which are needed to bring nonlocal pairs of amino acids into
contact.


title:
Do reductionist cures select for holistic diseases? Adaptive chronic
  infection, structured stress, and medical magic bullets

abstract:
  With a generalized language-of-thought argument for immune cognition, we
model how population-directed structured psychosocial stress can impose an
image of itself on the coevolutionary conflict between a highly adaptive
chronic infection and the immune system. We raise the possibility that, for
successful 'evolution machines' like HIV and malaria, simplistic
individual-oriented magic bullet drug treatments, vaccines, behavior
modification, or other interventions that do not address the fundamental living
and working conditions underlying disease ecology will fail to control current
epidemics and may select for holistic pathogenic life histories which increase
disease virulence.


title: What do neural nets and quantum theory tell us about mind and reality?

abstract:
  This paper proposes an approach to framing and answering fundamental
questions about consciousness. It argues that many of the more theoretical
debates about consciousness, such as debates about "when does it begin?", are
misplaced and meaningless, in part because "consciousness" as a word has many
valid and interesting definitions, and in part because consciousness qua mind
or intelligence (the main focus here)is a matter of degree or level, not a
binary variable. It proposes that new mathematical work related to functional
neural network designs -- designs so functional that they can be used in
engineering -- is essential to a functional understanding of intelligence as
such, and outlines some key mathematics as of 1999, citing earlier work for
more details. Quantum theory is relevant, but not in the simple ways proposed
in more popular philosophies.


title:
From the Termite Mound to the Stars: Meditations on Discussions With
  Ilya Prigogine

abstract:
  This paper summarizes and re-evaluates Prigogine's evolution of thought, from
a more classical view of thermodynamics with negative implications for the
evolution and persistence of life, through to a far more general and open
formulation of thermodynamics, which does not require assumption of a Big Bang.
The paper also proposes an encoding scheme for the statistics of Lorentzian
systems into mixed Fermi-Bose density matrices, to complete the program given
in quant-ph/0309087, which forcibly points towards symmetry in time at the
microscopic level. The paper suggests future directions to reconcile
microscopic time symmetry and macroscopic asymmetry and evolution, and
concludes that the space-time continuum may be larger and more interesting than
we are able yet to pin down.


title: Complex folding pathways in a simple beta-hairpin

abstract:
  The determination of the folding mechanisms of proteins is critical to
understand the topological change that can propagate Alzheimer and
Creutzfeld-Jakobs diseases, among others. The computational community has paid
considerable attention to this problem; however, the associated time scale,
typically on the order of milliseconds or more, represents a formidable
challenge. Ab initio protein folding from long molecular dynamics (MD)
simulations or ensemble dynamics is not feasible with ordinary computing
facilities and new techniques must be introduced. Here we present a detailed
study of the folding of a 16-residue beta-hairpin, described by a generic
energy model and using the activation-relaxation technique. From a total of 90
trajectories at 300 K, three folding pathways emerge. All involve a
simultaneous optimization of the complete hydrophobic and hydrogen bonding
interactions. The first two follow closely those observed by previous
theoretical studies. The third pathway, never observed by previous all-atom
folding, unfolding and equilibrium simulations, can be described as a reptation
move of one strand of the beta-sheet with respect to the other. This reptation
move indicates that non-native interactions can play a dominant role in the
folding of secondary structures. These results point to a more complex folding
picture than expected for a simple beta-hairpin.


title: Tropical Geometry of Statistical Models

abstract:
  This paper presents a unified mathematical framework for inference in
graphical models, building on the observation that graphical models are
algebraic varieties.
  From this geometric viewpoint, observations generated from a model are
coordinates of a point in the variety, and the sum-product algorithm is an
efficient tool for evaluating specific coordinates. The question addressed here
is how the solutions to various inference problems depend on the model
parameters. The proposed answer is expressed in terms of tropical algebraic
geometry. A key role is played by the Newton polytope of a statistical model.
Our results are applied to the hidden Markov model and to the general Markov
model on a binary tree.


title:
Analytic models for mechanotransduction: gating a mechanosensitive
  channel

abstract:
  Analytic estimates for the forces and free energy generated by bilayer
deformation reveal a compelling and intuitive model for MscL channel gating
analogous to the nucleation of a second phase. We argue that the competition
between hydrophobic mismatch and tension results in a surprisingly rich story
which can provide both a quantitative comparison to measurements of opening
tension for MscL when reconstituted in bilayers of different thickness and
qualitative insights into the function of the MscL channel and other
transmembrane proteins.


title: Are residues in a protein folding nucleus evolutionarily conserved?

abstract:
  It is important to understand how protein folding and evolution influences
each other. Several studies based on entropy calculation correlating
experimental measurement of residue participation in folding nucleus and
sequence conservation have reached different conclusions. Here we report
analysis of conservation of folding nucleus using an evolutionary model
alternative to entropy based approaches. We employ a continuous time Markov
model of codon substitution to distinguish mutation fixed by evolution and
mutation fixed by chance. This model takes into account bias in codon
frequency, bias favoring transition over transversion, as well as explicit
phylogenetic information. We measure selection pressure using the ratio
$\omega$ of synonymous vs. non-synonymous substitution at individual residue
site. The $\omega$-values are estimated using the {\sc Paml} method, a
maximum-likelihood estimator. Our results show that there is little correlation
between the extent of kinetic participation in protein folding nucleus as
measured by experimental $\phi$-value and selection pressure as measured by
$\omega$-value. In addition, two randomization tests failed to show that
folding nucleus residues are significantly more conserved than the whole
protein. These results suggest that at the level of codon substitution, there
is no indication that folding nucleus residues are significantly more conserved
than other residues. We further reconstruct candidate ancestral residues of the
folding nucleus and suggest possible test tube mutation studies of ancient
folding nucleus.


title: The Role of Computation in Complex Regulatory Networks

abstract:
  Biological phenomena differ significantly from physical phenomena. At the
heart of this distinction is the fact that biological entities have
computational abilities and thus they are inherently difficult to predict. This
is the reason why simplified models that provide the minimal requirements for
computation turn out to be very useful to study networks of many components. In
this chapter, we briefly review the dynamical aspects of models of regulatory
networks, discussing their most salient features, and we also show how these
models can give clues about the way in which networks may organize their
capacity to evolve, by providing simple examples of the implementation of
robustness and modularity.


title:
Adaptive walks in a gene network model of morphogenesis: insights into
  the Cambrian explosion

abstract:
  The emergence of complex patterns of organization close to the Cambrian
boundary is known to have happened over a (geologically) short period of time.
It involved the rapid diversification of body plans and stands as one of the
major transitions in evolution. How it took place is a controversial issue.
Here we explore this problem by considering a simple model of pattern formation
in multicellular organisms. By modeling gene network-based morphogenesis and
its evolution through adaptive walks, we explore the question of how
combinatorial explosions might have been actually involved in the Cambrian
event. Here we show that a small amount of genetic complexity including both
gene regulation and cell-cell signaling allows one to generate an extraordinary
repertoire of stable spatial patterns of gene expression compatible with
observed anteroposterior patterns in early development of metazoans. The
consequences for the understanding of the tempo and mode of the Cambrian event
are outlined.


title: Determinative degree and nucleotide sequence analysis by trianders

abstract:
  A new version of DNA walks, where nucleotides are regarded unequal in their
contribution to a walk is introduced, which allows us to study thoroughly the
"fine structure" of nucleotide sequences. The approach is based on the
assumption that nucleotides have an inner abstract characteristics, the
determinative degree, which reflects phenomenological properties of genetic
code and is adjusted to nucleotides physical properties. We consider each
position in codon independently, which gives three separate walks being
characterized by different angles and lengths, and such an object is called
triander which reflects the "strength" of branch. A general method of
identification of DNA sequence "by triander", which can be treated as a unique
"genogram", "gene passport" is proposed. The two- and three-dimensional
trianders are considered. The difference of sequence fine structure in genes
and the intergenic space is shown. A clear triplet signal in coding locuses is
found which is absent in the intergenic space and is independent from the
sequence length. The topological classification of trianders is presented which
can allow us to provide a detail working out signatures of functionally
different genomic regions.


title: Stretching of Proteins in the Entropic Limit

abstract:
  Mechanical stretching of six proteins is studied through molecular dynamics
simulations. The model is Go-like, with Lennard-Jones interactions at native
contacts. Low temperature unfolding scenarios are remarkably complex and
sensitive to small structural changes. Thermal fluctuations reduce the peak
forces and the number of metastable states during unfolding. The unfolding
pathways also simplify as temperature rises. In the entropic limit, all
proteins show a monotonic decrease of the extension where bonds rupture with
their separation along the backbone (contact order).


title: Superpositional Quantum Network Topologies

abstract:
  We introduce superposition-based quantum networks composed of (i) the
classical perceptron model of multilayered, feedforward neural networks and
(ii) the algebraic model of evolving reticular quantum structures as described
in quantum gravity. The main feature of this model is moving from particular
neural topologies to a quantum metastructure which embodies many differing
topological patterns. Using quantum parallelism, training is possible on
superpositions of different network topologies. As a result, not only classical
transition functions, but also topology becomes a subject of training. The main
feature of our model is that particular neural networks, with different
topologies, are quantum states. We consider high-dimensional dissipative
quantum structures as candidates for implementation of the model.


title:
Finding regulatory modules through large-scale gene-expression data
  analysis

abstract:
  The use of gene microchips has enabled a rapid accumulation of
gene-expression data. One of the major challenges of analyzing this data is the
diversity, in both size and signal strength, of the various modules in the gene
regulatory networks of organisms. Based on the Iterative Signature Algorithm
[Bergmann, S., Ihmels, J. and Barkai, N. (2002) Phys. Rev. E 67, 031902], we
present an algorithm - the Progressive Iterative Signature Algorithm (PISA) -
that, by sequentially eliminating modules, allows unsupervised identification
of both large and small regulatory modules. We applied PISA to a large set of
yeast gene-expression data, and, using the Gene Ontology annotation database as
a reference, found that our algorithm is much better able to identify
regulatory modules than methods based on high-throughput transcription-factor
binding experiments or on comparative genomics.


title: MAVID: Constrained ancestral alignment of multiple sequences

abstract:
  We describe a new global multiple alignment program capable of aligning a
large number of genomic regions. Our progressive alignment approach
incorporates the following ideas: maximum-likelihood inference of ancestral
sequences, automatic guide-tree construction, protein based anchoring of
ab-initio gene predictions, and constraints derived from a global homology map
of the sequences. We have implemented these ideas in the MAVID program, which
is able to accurately align multiple genomic regions up to megabases long.
MAVID is able to effectively align divergent sequences, as well as incomplete
unfinished sequences. We demonstrate the capabilities of the program on the
benchmark CFTR region which consists of 1.8Mb of human sequence and 20
orthologous regions in marsupials, birds, fish, and mammals. Finally, we
describe two large MAVID alignments: an alignment of all the available HIV
genomes and a multiple alignment of the entire human, mouse and rat genomes.


title:
The topology of the regulatory interactions predics the expression
  pattern of the segment polarity genes in Drosophila melanogaster

abstract:
  Expression of the Drosophila segment polarity genes is initiated by a
prepattern of pair-rule gene products and maintained by a network of regulatory
interactions throughout several stages of embryonic development. Analysis of a
model of gene interactions based on differential equations showed that
wild-type expression patterns of these genes can be obtained for a wide range
of kinetic parameters, which suggests that the steady states are determined by
the topology of the network and the type of regulatory interactions between
components, not the detailed form of the rate laws. To investigate this, we
propose and analyze a Boolean model of this network which is based on a binary
ON/OFF representation of transcription and protein levels, and in which the
interactions are formulated as logical functions. In this model the spatial and
temporal patterns of gene expression are determined by the topology of the
network and whether components are present or absent, rather than the absolute
levels of the mRNAs and proteins and the functional details of their
interactions. The model is able to reproduce the wild type gene expression
patterns, as well as the ectopic expression patterns observed in
over-expression experiments and various mutants. Furthermore, we compute
explicitly all steady states of the network and identify the basin of
attraction of each steady state. The model gives important insights into the
functioning of the segment polarity gene network, such as the crucial role of
the wingless and sloppy paired genes, and the network's ability to correct
errors in the prepattern.


title: An asymptotic maximum principle for essentially linear evolution models

abstract:
  Recent work on mutation-selection models has revealed that, under specific
assumptions on the fitness function and the mutation rates, asymptotic
estimates for the leading eigenvalue of the mutation-reproduction matrix may be
obtained through a low-dimensional maximum principle in the limit N to infinity
(where N is the number of types). In order to extend this variational principle
to a larger class of models, we consider here a family of reversible N by N
matrices and identify conditions under which the high-dimensional Rayleigh-Ritz
variational problem may be reduced to a low-dimensional one that yields the
leading eigenvalue up to an error term of order 1/N. For a large class of
mutation-selection models, this implies estimates for the mean fitness, as well
as a concentration result for the ancestral distribution of types.


title:
Is prokaryotic complexity limited by accelerated growth in regulatory
  overhead?

abstract:
  Increased biological complexity is generally associated with the addition of
new genetic information, which must be integrated into the existing regulatory
network that operates within the cell. General arguments on network control, as
well as several recent genomic observations, indicate that regulatory gene
number grows disproportionally fast with increasing genome size. We present two
models for the growth of regulatory networks. Both predict that the number of
transcriptional regulators will scale quadratically with total gene number.
This appears to be in good quantitative agreement with genomic data from 89
fully sequenced prokaryotes. Moreover, the empirical curve predicts that any
new non-regulatory gene will be accompanied by more than one additional
regulator beyond a genome size of about 20,000 genes, within a factor of two of
the observed ceiling. Our analysis places transcriptional regulatory networks
in the class of accelerating networks. We suggest that prokaryotic complexity
may have been limited throughout evolution by regulatory overhead, and
conversely that complex eukaryotes must have bypassed this constraint by novel
strategies.


title:
Solvent content of protein crystals from diffraction intensities by
  Independent Component Analysis

abstract:
  An analysis of the protein content of several crystal forms of proteins has
been performed. We apply a new numerical technique, the Independent Component
Analysis (ICA), to determine the volume fraction of the asymmetric unit
occupied by the protein. This technique requires only the crystallographic data
of structure factors as input.


title: Coarse-Grained Model of Entropic Allostery

abstract:
  Many signalling functions in molecular biology require proteins bind to
substrates such as DNA in response to environmental signals such as the
simultaneous binding to a small molecule. Examples are repressor proteins which
may transmit information via a conformational change in response to the ligand
binding. An alternative entropic mechanism of ``allostery'' suggests that the
inducer ligand changes the intramolecular vibrational entropy not just the
static structure. We present a quantitative, coarse-grained model of entropic
allostery that suggests design rules for internal cohesive potentials in
proteins employing this effect. It also addresses the issue of how the signal
information to bind or unbind is transmitted through the protein. The model may
be applicable to a wide range of repressors and also to signalling in
transmembrane proteins.


title: Identification in models of biochemical reactions

abstract:
  We introduce, analyze, and implement a new method for parameter
identification for system of ordinary differential equations that are used to
model sets of biochemical reactions. Our method relies on the integral
formulation of the ODE system and a method of linear least squares applied to
the integral equations. Certain variants of this method are also introduced in
this paper.


title: Evolutionary tradeoff and equilibrium in an aquatic predator-prey system

abstract:
  Due to the conventional distinction between ecological (rapid) and
evolutionary (slow)timescales, ecological and population models to date have
typically ignored the effects of evolution. Yet the potential for rapid
evolutionary change has been recently established and may be critical to
understanding how populations adapt to changing environments. In this paper we
examine the relationship between ecological and evolutionary dynamics, focusing
on a well-studied experimental aquatic predator-prey system (Fussmann et al.
2000; Shertzer et al. 2002; Yoshida et al. 2003). Major properties of
predator-prey cycles in this system are determined by ongoing evolutionary
dynamics in the prey population. Under some conditions, however, the
populations tend to apparently stable steady-state densities. These are the
subject of the present paper. We examine a previously developed model for the
system, to determine how evolution shapes properties of the equilibria, in
particular the number and identity of coexisting prey genotypes. We then apply
these results to explore how evolutionary dynamics can shape the responses of
the system to "management": externally imposed alterations in conditions.
Specifically, we compare the behavior of the system including evolutionary
dynamics, with predictions that would be made if the potential for rapid
evolutionary change is negelected. Finally, we posit some simple experiments to
verify our prediction that evolution can have significant qualitative effects
on observed population-level responses to changing conditions.


title:
Brain neurons as quantum computers: {\it in vivo} support of background
  physics

abstract:
  The question: whether quantum coherent states can sustain decoherence,
heating and dissipation over time scales comparable to the dynamical timescales
of the brain neurons, is actively discussed in the last years. Positive answer
on this question is crucial, in particular, for consideration of brain neurons
as quantum computers. This discussion was mainly based on theoretical
arguments. In present paper nonlinear statistical properties of the Ventral
Tegmental Area (VTA) of genetically depressive limbic brain are studied {\it in
vivo} on the Flinders Sensitive Line of rats (FSL). VTA plays a key role in
generation of pleasure and in development of psychological drug addiction. We
found that the FSL VTA (dopaminergic) neuron signals exhibit multifractal
properties for interspike frequencies on the scales where healthy VTA
dopaminergic neurons exhibit bursting activity. For high moments the observed
multifractal (generalized dimensions) spectrum coincides with the generalized
dimensions spectrum calculated for a spectral measure of a {\it quantum} system
(so-called kicked Harper model, actively used as a model of quantum chaos).
This observation can be considered as a first experimental ({\it in vivo})
indication in the favour of the quantum (at least partially) nature of the
brain neurons activity.


title:
Ocular dominance patterns and the wire length minimization: a numerical
  study

abstract:
  We study a mathematical model for ocular dominance patterns (ODPs) in primary
visual cortex. This model is based on the premise that ODP is an adaptation to
minimize the length of intra-cortical wiring. Thus we attempt to understand the
existing ODPs by solving a wire length minimization problem. We divide all the
neurons into two classes: left- and right-eye dominated. We find that
segregation of neurons into monocular regions reduces wire length if the number
of connections to the neurons of the same class (intraocular) differs from the
number of interocular connections. The shape of the regions depends on the
relative fraction of neurons in the two classes. We find that if both classes
are almost equally represented, the optimal ODP consists of interdigitating
stripes. If one class is less numerous than the other, the optimal ODP consists
of patches of the less abundant class surrounded by the neurons of the other
class. We predict that the transition from stripes to patches occurs when the
fraction of neurons dominated by the underrepresented eye is about 40%. This
prediction agrees with the data in macaque and Cebus monkeys. We also study the
dependence of the periodicity of ODP on the parameters of our model.


title:
Systemic lupus erythematosus in African-American women: Cognitive
  physiological modules, autoimmune disease, and structured psychosocial stress

abstract:
  Examining elevated rates of systemic lupus erythematosus in African-American
women from perspectives of immune cognition suggests the disease constitutes an
internalized physiological image of external structured psychosocial stress, a
'pathogenic social hierarchy' involving the synergism of racism and gender
discrimination in the context of policy-driven social disintegration which has
particularly affected ethnic minorities in the USA. The disorder represents the
punctuated resetting of normal immune self-image to a self-attacking excited
state, a process formally analogous to models of punctuated equilibrium in
evolutionary theory. Both onset and progression of disease may be stratified by
a relation to cyclic physiological responses which are long in comparison with
heartbeat period: circadian, hormonal, and annual light/termperature cycles.


title:
Dynamical Systems Basis of Metamorphosis: Diversity and Plasticity of
  Cellular States in Reaction Diffusion Network

abstract:
  Dynamics maintaining diversity of cell types in a multi-cellular system are
studied in relationship with the plasticity of cellular states. By adopting a
simple theoretical framework for intra-cellular chemical reaction dynamics with
considering the division and death of cells, developmental process from a
single cell is studied. Cell differentiation process is found to occur through
instability in transient dynamics and cell-cell interaction. In a long time
behavior, extinction of multiple cells is repeated, which leads to itinerancy
over successive quasi-stable multi-cellular states consisting of different
types of cells. By defining the plasticity of a cellular state, it is shown
that the plasticity of cells decreases before the large extinction, from which
diversity and plasticity are recovered. After this switching, decrease of
plasticity again occurs, leading to the next extinction of multiple cells. This
cycle of diversification and extinction is repeated. Relevance of our results
to the development and evolution is briefly discussed.


title:
Comparation based bottom-up and top-down filtering model of the
  hippocampus and its environment

abstract:
  Two rate code models -- a reconstruction network model and a control model --
of the hippocampal-entorhinal loop are merged. The hippocampal-entorhinal loop
plays a double role in the unified model, it is part of a reconstruction
network and a controller, too. This double role turns the bottom-up information
flow into top-down control like signals. The role of bottom-up filtering is
information maximization, noise filtering, temporal integration and prediction,
whereas the role of top-down filtering is emphasizing, i.e., highlighting or
`paving of the way' as well as context based pattern completion. In the joined
model, the control task is performed by cortical areas, whereas reconstruction
networks can be found between cortical areas. While the controller is highly
non-linear, the reconstruction network is an almost linear architecture, which
is optimized for noise estimation and noise filtering. A conjecture of the
reconstruction network model -- that the long-term memory of the visual stream
is the linear feedback connections between neocortical areas -- is reinforced
by the joined model. Falsifying predictions are presented; some of them have
recent experimental support. Connections to attention and to awareness are
made.


title:
Homogeneous and Scalable Gene Expression Regulatory Networks with Random
  Layouts of Switching Parameters

abstract:
  We consider a model of large regulatory gene expression networks where the
thresholds activating the sigmoidal interactions between genes and the signs of
these interactions are shuffled randomly. Such an approach allows for a
qualitative understanding of network dynamics in a lack of empirical data
concerning the large genomes of living organisms. Local dynamics of network
nodes exhibits the multistationarity and oscillations and depends crucially
upon the global topology of a "maximal" graph (comprising of all possible
interactions between genes in the network). The long time behavior observed in
the network defined on the homogeneous "maximal" graphs is featured by the
fraction of positive interactions ($0\leq \eta\leq 1$) allowed between genes.
There exists a critical value $\eta_c<1$ such that if $\eta<\eta_c$, the
oscillations persist in the system, otherwise, when $\eta>\eta_c,$ it tends to
a fixed point (which position in the phase space is determined by the initial
conditions and the certain layout of switching parameters). In networks defined
on the inhomogeneous directed graphs depleted in cycles, no oscillations arise
in the system even if the negative interactions in between genes present
therein in abundance ($\eta_c=0$). For such networks, the bidirectional edges
(if occur) influence on the dynamics essentially. In particular, if a number of
edges in the "maximal" graph is bidirectional, oscillations can arise and
persist in the system at any low rate of negative interactions between genes
($\eta_c=1$). Local dynamics observed in the inhomogeneous scalable regulatory
networks is less sensitive to the choice of initial conditions. The scale free
networks demonstrate their high error tolerance.


title:
Persistence length of chromatin determines origin spacing in Xenopus
  early-embryo DNA replication: Quantitative comparisons between theory and
  experiment

abstract:
  In Xenopus early embryos, replication origins neither require specific DNA
sequences nor is there an efficient S/M checkpoint, even though the whole
genome (3 billion bases) is completely duplicated within 10-20 minutes. This
leads to the"random-completion problem" of DNA replication in embryos, where
one needs to find a mechanism that ensures complete, faithful, timely
reproduction of the genome without any sequence dependence of replication
origins. We analyze recent DNA replication data in Xenopus laevis egg extracts
and find discrepancies with models where replication origins are distributed
independently of chromatin structure. Motivated by these discrepancies, we have
investigated the role that chromatin looping may play in DNA replication. We
find that the loop-size distribution predicted from a wormlike-chain model of
chromatin can account for the spatial distribution of replication origins in
this system quantitatively. Together with earlier findings of increasing
frequency of origin firings, our results can explain the random-completion
problem. The agreement between experimental data (molecular combing) and
theoretical predictions suggests that the intrinsic stiffness of chromatin
loops plays a fundamental biological role in DNA replication in early-embryo
Xenopus in regulating the origin spacing.


title:
Localization of DNA damage by current exchanging repair enzymes: effects
  of cooperativity on detection time

abstract:
  How DNA repair enzymes find the relatively rare sites of damage is not known
in great detail. Recent experiments and molecular data suggest that the
individual repair enzymes do not work independently of each other, but rather
interact with each other through currents exchanged along DNA. A damaged site
in DNA hinders this exchange and this makes it possible to quickly free up
resources from error free stretches of DNA. Here the size of the speedup gained
from this current exchange mechanism is calculated and the characteristic
length and time scales are identified. In particular for Escherichia coli we
estimate the speedup to be 50000/N, where N is the number of repair enzymes
participating in the current exchange mechanism. Even though N is not exactly
known a speedup of order 10 is not entirely unreasonable. Furthermore upon over
expression of repair enzymes the detection time only varies as one over the
squareroot of N and not as 1/N. This behavior is of interest in assessing the
impact of stress full and radioactive environments on individual cell mutation
rates.


title:
Coronary heart disease, chronic inflammation, and pathogenic social
  hierarchy: a biological limit to possible reductions in morbidity and
  mortality

abstract:
  We suggest that a particular form of social hierarchy, which we characterize
as 'pathogenic', can, from the earliest stages of life, exert a formal analog
to evolutionary selection pressure, literally writing a permanent developmental
image of itself upon immune function as chronic vascular inflammation and its
consequences. The staged nature of resulting disease emerges 'naturally' as a
rough analog to punctuated equilibrium in evolutionary theory, although
selection pressure is a passive filter rather than an active agent like
structured psychosocial stress. Exposure differs according to the social
constructs of race, class, and ethnicity, accounting in large measure for
observed population-level differences in rates of coronary heart disease across
industrialized societies. American Apartheid, which enmeshes both majority and
minority communities in a social construct of pathogenic hierarchy, appears to
present a severe biological limit to continuing declines in coronary heart
disease for powerful as well as subordinate subgroups: 'Culture', to use the
words of the evolutionary anthropologist Robert Boyd, 'is as much a part of
human biology as the enamel on our teeth'.


title: Cellular automaton for bacterial towers

abstract:
  A simulation approach to the stochastic growth of bacterial towers is
presented, in which a non-uniform and finite nutrient supply essentially
determines the emerging structure through elementary chemotaxis. The method is
based on cellular automata and we use simple, microscopic, local rules for
bacterial division in nutrient-rich surroundings. Stochastic nutrient
diffusion, while not crucial to the dynamics of the total population, is
influential in determining the porosity of the bacterial tower and the
roughness of its surface. As the bacteria run out of food, we observe an
exponentially rapid saturation to a carrying capacity distribution, similar in
many respects to that found in a recently proposed phenomenological
hierarchical population model, which uses heuristic parameters and macroscopic
rules. Complementary to that phenomenological model, the simulation aims at
giving more microscopic insight into the possible mechanisms for one of the
recently much studied bacterial morphotypes, known as "towering biofilm",
observed experimentally using confocal laser microscopy. A simulation
suggesting a mechanism for biofilm resistance to antibiotics is also shown.


title: Peptide size dependent active transport in the proteasome

abstract:
  We investigate the transport of proteins inside the proteasome and propose an
active transport mechanism based on a spatially asymmetric interaction
potential of peptide chains. The transport is driven by fluctuations which are
always present in such systems. We compute the peptide-size dependent transport
rate which is essential for the functioning of the proteasome. In agreement
with recent experiments, varying temperature changes the transport mechanism
qualitatively.


title: Hierarchical Clustering Using Mutual Information

abstract:
  We present a method for hierarchical clustering of data called {\it mutual
information clustering} (MIC) algorithm. It uses mutual information (MI) as a
similarity measure and exploits its grouping property: The MI between three
objects $X, Y,$ and $Z$ is equal to the sum of the MI between $X$ and $Y$, plus
the MI between $Z$ and the combined object $(XY)$. We use this both in the
Shannon (probabilistic) version of information theory and in the Kolmogorov
(algorithmic) version. We apply our method to the construction of phylogenetic
trees from mitochondrial DNA sequences and to the output of independent
components analysis (ICA) as illustrated with the ECG of a pregnant woman.


title: DNA Renaturation at the Water-Phenol Interface

abstract:
  We study DNA adsorption and renaturation in a water-phenol two-phase system,
with or without shaking. In very dilute solutions, single-stranded DNA is
adsorbed at the interface in a salt-dependent manner. At high salt
concentrations the adsorption is irreversible. The adsorption of the
single-stranded DNA is specific to phenol and relies on stacking and hydrogen
bonding. We establish the interfacial nature of a DNA renaturation at a high
salt concentration. In the absence of shaking, this reaction involves an
efficient surface diffusion of the single-stranded DNA chains. In the presence
of a vigorous shaking, the bimolecular rate of the reaction exceeds the
Smoluchowski limit for a three-dimensional diffusion-controlled reaction. DNA
renaturation in these conditions is known as the Phenol Emulsion Reassociation
Technique or PERT. Our results establish the interfacial nature of PERT. A
comparison of this interfacial reaction with other approaches shows that PERT
is the most efficient technique and reveals similarities between PERT and the
renaturation performed by single-stranded nucleic acid binding proteins. Our
results lead to a better understanding of the partitioning of nucleic acids in
two-phase systems, and should help design improved extraction procedures for
damaged nucleic acids. We present arguments in favor of a role of phenol and
water-phenol interface in prebiotic chemistry. The most efficient renaturation
reactions (in the presence of condensing agents or with PERT) occur in
heterogeneous systems. This reveals the limitations of homogeneous approaches
to the biochemistry of nucleic acids. We propose a heterogeneous approach to
overcome the limitations of the homogeneous viewpoint.


title: Hierarchical Clustering Based on Mutual Information

abstract:
  Motivation: Clustering is a frequently used concept in variety of
bioinformatical applications. We present a new method for hierarchical
clustering of data called mutual information clustering (MIC) algorithm. It
uses mutual information (MI) as a similarity measure and exploits its grouping
property: The MI between three objects X, Y, and Z is equal to the sum of the
MI between X and Y, plus the MI between Z and the combined object (XY).
  Results: We use this both in the Shannon (probabilistic) version of
information theory, where the "objects" are probability distributions
represented by random samples, and in the Kolmogorov (algorithmic) version,
where the "objects" are symbol sequences. We apply our method to the
construction of mammal phylogenetic trees from mitochondrial DNA sequences and
we reconstruct the fetal ECG from the output of independent components analysis
(ICA) applied to the ECG of a pregnant woman.
  Availability: The programs for estimation of MI and for clustering
(probabilistic version) are available at
http://www.fz-juelich.de/nic/cs/software


title:
A continuum treatment of growth in biological tissue: The coupling of
  mass transport and mechanics

abstract:
  Growth (and resorption) of biological tissue is formulated in the continuum
setting. The treatment is macroscopic, rather than cellular or sub-cellular.
Certain assumptions that are central to classical continuum mechanics are
revisited, the theory is reformulated, and consequences for balance laws and
constitutive relations are deduced. The treatment incorporates multiple
species. Sources and fluxes of mass, and terms for momentum and energy transfer
between species are introduced to enhance the classical balance laws. The
transported species include: (\romannumeral 1) a fluid phase, and
(\romannumeral 2) the precursors and byproducts of the reactions that create
and break down tissue. A notable feature is that the full extent of coupling
between mass transport and mechanics emerges from the thermodynamics.
Contributions to fluxes from the concentration gradient, chemical potential
gradient, stress gradient, body force and inertia have not emerged in a unified
fashion from previous formulations of the problem. The present work
demonstrates these effects via a physically-consistent treatment. The presence
of multiple, interacting species requires that the formulation be consistent
with mixture theory. This requirement has far-reaching consequences. A
preliminary numerical example is included to demonstrate some aspects of the
coupled formulation.


title: Material forces in the context of biotissue remodelling

abstract:
  Remodelling of biological tissue, due to changes in microstructure, is
treated in the continuum mechanical setting. Microstructural change is
expressed as an evolution of the reference configuration. This evolution is
expressed as a point-to-point map from the reference configuration to a
remodelled configuration. A ``preferred'' change in configuration is considered
in the form of a globally incompatible tangent map. This field could be
experimentally determined, or specified from other insight. Issues of global
compatibility and evolution equations for the resulting configurations are
addressed. It is hypothesized that the tissue reaches local equilibrium with
respect to changes in microstructure. A governing differential equation and
boundary conditions are obtained for the microstructural changes by posing the
problem in a variational setting. The Eshelby stress tensor, a separate
configurational stress, and thermodynamic driving (material) forces arise in
this formulation, which is recognized as describing a process of self-assembly.
An example is presented to illustrate the theoretical framework.


title:
The cognitive homunculus: do tunable languages-of-thought convey
  adaptive advantage?

abstract:
  We reexamine the generalized cognitive homunculus, an organism's internalized
image of its physiological, psychological, and social state, which, when
properly adjusted, can quickly detect subtle deviations from a reference
configuration. We particularly seek to extend the treatment beyond
'language-of-thought' systems modeled as ergodic information sources. Such
extension would generate an exceedingly rich response repertoire, not limited
by fixed patterns of grammar and syntax. Rather, these would themselves be
tunable according to the changing short-term contextual demands faced by the
organism, possibly providing significant long-term adaptive advantage.


title:
Diffusion Entropy Approach to Dynamical Characteristics of a
  Hodgkin-Huxley Neuron

abstract:
  By means of the concept DE we analyze the responses of a HH neuron to two
types of spike-train inputs. Two characteristic quantities can be extracted,
which can reflect partially the dynamical process of a HH neuron.


title: Computational Consequences of Neglected First-Order van der Waals Forces

abstract:
  We have computed the widely neglected first-order interaction between neutral
atoms. At interatomic separations typical of condensed media, it is nearly
equal to the 1/r^6 second-order London energy inferred from interactions in
gasses. Our results, without the exchange forces that lead to covalent bonding,
suggest that the quality of non-bonding attraction between neutral atoms of
molecules in condensed media differs from the 1/r^6 form usually ascribed to
it. If we add first-order and all second-order terms, we obtain energies nearly
five times the 1/r^6 London energies which dominate only at the atomic
separations found in gasses. For computation, we propose a practical, accurate
form of energy to replace the qualitatively inaccurate Lennard-Jones and
harmonic forms casually assumed to hold at the interatomic separations found in
condensed media.


title:
Relevance Vector Machines for classifying points and regions in
  biological sequences

abstract:
  The Relevance Vector Machine (RVM) is a recently developed machine learning
framework capable of building simple models from large sets of candidate
features. Here, we describe a protocol for using the RVM to explore very large
numbers of candidate features, and a family of models which apply the power of
the RVM to classifying and detecting interesting points and regions in
biological sequence data. The models described here have been used successfully
for predicting transcription start sites and other features in genome
sequences.


title: What can we learn from noncoding regions of similarity between genomes?

abstract:
  Background: In addition to known protein-coding genes, large amount of
apparently non-coding sequence are conserved between the human and mouse
genomes. It seems reasonable to assume that these conserved regions are more
likely to contain functional elements than less-conserved portions of the
genome. Here we used a motif-oriented machine learning method to extract the
strongest signal from a set of non-coding conserved sequences.
  Results: We successfully fitted models to reflect the non-coding sequences,
and showed that the results were quite consistent for repeated training runs.
Using the learned model to scan genomic sequence, we found that it often made
predictions close to the start of annotated genes. We compared this method with
other published promoter-prediction systems, and show that the set of promoters
which are detected by this method seems to be substantially similar to that
detected by existing methods.
  Conclusions: The results presented here indicate that the promoter signal is
the strongest single motif-based signal in the non-coding functional fraction
of the genome. They also lend support to the belief that there exists a
substantial subset of promoter regions which share common features and are
detectable by a variety of computational methods.


title:
Stabilization of microtubules due to microtubule-associated proteins: A
  simple model

abstract:
  A theoretical model of stabilization of a microtubule assembly due to
microtubule-associated-proteins(MAP) is presented. MAPs are assumed to bind to
the microtubule filaments, thus preventing their disintegration following
hydrolysis and enhancing further polymerization. Using mean-field rate
equations and explicit numerical simulations, we show that the density of MAP
(number of MAP per tubulin in the microtubule) has to exceed a critical value
$\rho_{c}$ to stabilize the structure against de-polymerization. At lower
densities $\rho < \rho_{c}$, the microtubule population consists mostly of
short polymers with exponentially decaying length distribution, whereas at
$\rho > \rho_{c}$ the average length increases linearly with time and the
microtubules ultimately extend to the cell boundary. Using experimentally
measured values of various parameters, the critical ratio of MAP to tubulin
required for unlimited growth is seen to be of the order of 1:100 or even
smaller.


title:
Evolution of the Protein Interaction Network of Budding Yeast: Role of
  the Protein Family Compatibility Constraint

abstract:
  Understanding of how protein interaction networks (PIN) of living organisms
have evolved or are organized can be the first stepping stone in unveiling how
life works on a fundamental ground. Here we introduce a hybrid network model
composed of the yeast PIN and the protein family interaction network. The
essential ingredient of the model includes the protein family identity and its
robustness under evolution, as well as the three previously proposed ones: gene
duplication, divergence, and mutation. We investigate diverse structural
properties of our model with parameter values relevant to yeast, finding that
the model successfully reproduces the empirical data.


title:
Correlation between sequence hydrophobicity and surface-exposure pattern
  of database proteins

abstract:
  Hydrophobicity is thought to be one of the primary forces driving the folding
of proteins. On average, hydrophobic residues occur preferentially in the core,
whereas polar residues tends to occur at the surface of a folded protein. By
analyzing the known protein structures, we quantify the degree to which the
hydrophobicity sequence of a protein correlates with its pattern of surface
exposure. We have assessed the statistical significance of this correlation for
several hydrophobicity scales in the literature, and find that the computed
correlations are significant but far from optimal. We show that this less than
optimal correlation arises primarily from the large degree of mutations that
naturally occurring proteins can tolerate. Lesser effects are due in part to
forces other than hydrophobicity and we quantify this by analyzing the surface
exposure distributions of all amino acids. Lastly we show that our database
findings are consistent with those found from an off-lattice hydrophobic-polar
model of protein folding.


title: Structured psychosocial stress and the US obesity epidemic

abstract:
  We examine the accelerating 'obesity epidemic' in the US from the perspective
of generalized language-of-thought arguments relating a cognitive
hypothalamic-pituitary-adrenal axis to an embedding context of structured
psychosocial stress. From a Rate Distortion perspective, the obesity epidemic
is an image of ratcheting social pathology -- indexed by massive,
policy-driven, deurbanization and deindustrialization -- impressed upon the
bodies of American adults and children. The resulting pattern of developmental
disorder, while stratified by expected divisions of class and ethnicity, is
nonetheless relentlessly engulfing even affluent majority populations.


title:
Dynamic receptor team formation can explain the high signal transduction
  gain in E. coli

abstract:
  Evolution has provided many organisms with sophisticated sensory systems that
enable them to respond to signals in their environment. The response frequently
involves alteration in the pattern of movement, such as the chemokinesis of the
bacterium Escherichia coli, which swims by rotating its flagella. When rotated
counterclockwise (CCW) the flagella coalesce into a propulsive bundle,
producing a relatively straight ``run'', and when rotated clockwise (CW) they
fly apart, resulting in a ``tumble'' which reorients the cell with little
translocation. A stochastic process generates the runs and tumbles, and in a
chemoeffector gradient runs that carry the cell in a favorable direction are
extended. The overall structure of the signal transduction pathways is
well-characterized in E. coli, but important details are still not understood.
Only recently has a source of gain in the signal transduction network been
identified experimentally, and here we present a mathematical model based on
dynamic assembly of receptor teams that can explain this observation.


title:
Noise-driven transition to quasi-deterministic limit cycle dynamics in
  excitable systems

abstract:
  The effect of small-amplitude noise on excitable systems with large
time-scale separation is analyzed. It is found that small random perturbations
of the fast excitatory variable result in the onset of a quasi-deterministic
limit cycle behavior, absent without noise. The limit cycle is established at a
critical value of the amplitude of the noise, and its period is nontrivially
determined by the relationship between the noise amplitude and the time scale
ratio. It is argued that this effect might provide a mechanism by which the
function of biological systems operating in noisy environments can be robustly
controlled by the level of the noise.


title: Adaptation and enslavement in endosymbiont-host associations

abstract:
  The evolutionary persistence of symbiotic associations is a puzzle.
Adaptation should eliminate cooperative traits if it is possible to enjoy the
advantages of cooperation without reciprocating - a facet of cooperation known
in game theory as the Prisoner's Dilemma. Despite this barrier, symbioses are
widespread, and may have been necessary for the evolution of complex life. The
discovery of strategies such as tit-for-tat has been presented as a general
solution to the problem of cooperation. However, this only holds for
within-species cooperation, where a single strategy will come to dominate the
population. In a symbiotic association each species may have a different
strategy, and the theoretical analysis of the single species problem is no
guide to the outcome. We present basic analysis of two-species cooperation and
show that a species with a fast adaptation rate is enslaved by a slowly
evolving one. Paradoxically, the rapidly evolving species becomes highly
cooperative, whereas the slowly evolving one gives little in return. This helps
understand the occurrence of endosymbioses where the host benefits, but the
symbionts appear to gain little from the association.


title: A mechanism for polar protein localization in bacteria

abstract:
  We investigate a mechanism for the polar localization of proteins in
bacteria. We focus on the MinCD/DivIVA system regulating division site
placement in the rod-shaped bacterium Bacillus subtilis. Our model relies on a
combination of geometric effects and reaction-diffusion dynamics to direct
proteins to both cell poles, where division is then blocked. We discuss
similarities and differences with related division models in Escherichia coli
and also develop extensions of the model to asymmetric polar protein
localization. We propose that our mechanism for polar localization may be
employed more widely in bacteria, especially in outgrowing spores, which do not
possess any pre-existing polar division apparatus from prior division events.


title: Modelling of SARS for Hong Kong

abstract:
  A simplified susceptible-infected-recovered (SIR) epidemic model and a
small-world model are applied to analyse the spread and control of Severe Acute
Respiratory Syndrome (SARS) for Hong Kong in early 2003. From data available in
mid April 2003, we predict that SARS would be controlled by June and nearly
1700 persons would be infected based on the SIR model. This is consistent with
the known data. A simple way to evaluate the development and efficacy of
control is described and shown to provide a useful measure for the future
evolution of an epidemic. This may contribute to improve strategic response
from the government. The evaluation process here is universal and therefore
applicable to many similar homogeneous epidemic diseases within a fixed
population. A novel model consisting of map systems involving the Small-World
network principle is also described. We find that this model reproduces
qualitative features of the random disease propagation observed in the true
data. Unlike traditional deterministic models, scale-free phenomena are
observed in the epidemic network. The numerical simulations provide theoretical
support for current strategies and achieve more efficient control of some
epidemic diseases, including SARS.


title:
Clone-array pooled shotgun mapping and sequencing: design and analysis
  of experiments

abstract:
  This paper studies sequencing and mapping methods that rely solely on pooling
and shotgun sequencing of clones. First, we scrutinize and improve the recently
proposed Clone-Array Pooled Shotgun Sequencing (CAPSS) method, which delivers a
BAC-linked assembly of a whole genome sequence. Secondly, we introduce a novel
physical mapping method, called Clone-Array Pooled Shotgun Mapping (CAPS-MAP),
which computes the physical ordering of BACs in a random library. Both CAPSS
and CAPS-MAP construct subclone libraries from pooled genomic BAC clones.
  We propose algorithmic and experimental improvements that make CAPSS a viable
option for sequencing a set of BACs. We provide the first probabilistic model
of CAPSS sequencing progress. The model leads to theoretical results supporting
previous, less formal arguments on the practicality of CAPSS. We demonstrate
the usefulness of CAPS-MAP for clone overlap detection with a probabilistic
analysis, and a simulated assembly of the Drosophila melanogaster genome. Our
analysis indicates that CAPS-MAP is well-suited for detecting BAC overlaps in a
highly redundant library, relying on a low amount of shotgun sequence
information. Consequently, it is a practical method for computing the physical
ordering of clones in a random library, without requiring additional clone
fingerprinting. Since CAPS-MAP requires only shotgun sequence reads, it can be
seamlessly incorporated into a sequencing project with almost no experimental
overhead.


title: Evolutionary model with genetics, aging and knowledge

abstract:
  We represent a process of learning by using bit strings, where 1-bits
represent the knowledge acquired by individuals. Two ways of learning are
considered: individual learning by trial-and-error; and social learning by
copying knowledge from other individuals, or from parents in the case of
species with parental care. The age-structured bit string allows us to study
how knowledge is accumulated during life and its influence over the genetic
pool of a population after many generations. We use the Penna model to
represent the genetic inheritance of each individual. In order to study how the
accumulated knowledge influences the survival process, we include it to help
individuals to avoid the various death situations. Modifications in the
Verhulst factor do not show any special feature due to its random nature.
However, by adding years to life as a function of the accumulated knowledge, we
observe an improvement of the survival rates while the genetic fitness of the
population becomes worse. In this latter case, knowledge becomes more important
in the last years of life where individuals are threatened by diseases. Effects
of offspring overprotection and differences between individual and social
learning can also be observed. Sexual selection as a function of knowledge
shows some effects when fidelity is imposed.


title: Topological Generalizations of network motifs

abstract:
  Biological and technological networks contain patterns, termed network
motifs, which occur far more often than in randomized networks. Network motifs
were suggested to be elementary building blocks that carry out key functions in
the network. It is of interest to understand how network motifs combine to form
larger structures. To address this, we present a systematic approach to define
'motif generalizations': families of motifs of different sizes that share a
common architectural theme. To define motif generalizations, we first define
'roles' in a subgraph according to structural equivalence. For example, the
feedforward loop triad, a motif in transcription, neuronal and some electronic
networks, has three roles, an input node, an output node and an internal node.
The roles are used to define possible generalizations of the motif. The
feedforward loop can have three simple generalizations, based on replicating
each of the three roles and their connections. We present algorithms for
efficiently detecting motif generalizations. We find that the transcription
networks of bacteria and yeast display only one of the three generalizations,
the multi-output feedforward generalization. In contrast, the neuronal network
of \emph{C. elegans} mainly displays the multi-input generalization.
Forward-logic electronic circuits display a multi-input, multi-output hybrid.
Thus, networks which share a common motif can have very different
generalizations of that motif. Using mathematical modelling, we describe the
information processing functions of the different motif generalizations in
transcription, neuronal and electronic networks.


title: The stochastic behavior of a molecular switching circuit with feedback

abstract:
  Background: Using a statistical physics approach, we study the stochastic
switching behavior of a model circuit of multisite phosphorylation and
dephosphorylation with feedback. The circuit consists of a kinase and
phosphatase acting on multiple sites of a substrate that, contingent on its
modification state, catalyzes its own phosphorylation and, in a symmetric
scenario, dephosphorylation. The symmetric case is viewed as a cartoon of
conflicting feedback that could result from antagonistic pathways impinging on
the state of a shared component.
  Results: Multisite phosphorylation is sufficient for bistable behavior under
feedback even when catalysis is linear in substrate concentration, which is the
case we consider. We compute the phase diagram, fluctuation spectrum and
large-deviation properties related to switch memory within a statistical
mechanics framework. Bistability occurs as either a first-order or second-order
non-equilibrium phase transition, depending on the network symmetries and the
ratio of phosphatase to kinase numbers. In the second-order case, the circuit
never leaves the bistable regime upon increasing the number of substrate
molecules at constant kinase to phosphatase ratio.
  Conclusions: The number of substrate molecules is a key parameter controlling
both the onset of the bistable regime, fluctuation intensity, and the residence
time in a switched state. The relevance of the concept of memory depends on the
degree of switch symmetry, as memory presupposes information to be remembered,
which is highest for equal residence times in the switched states.
  Reviewers: This article was reviewed by Artem Novozhilov (nominated by Eugene
Koonin), Sergei Maslov, and Ned Wingreen.


title:
Inherent size constraints on prokaryote gene networks due to
  "accelerating" growth

abstract:
  Networks exhibiting "accelerating" growth have total link numbers growing
faster than linearly with network size and can exhibit transitions from
stationary to nonstationary statistics and from random to scale-free to regular
statistics at particular critical network sizes. However, if for any reason the
network cannot tolerate such gross structural changes then accelerating
networks are constrained to have sizes below some critical value. This is of
interest as the regulatory gene networks of single celled prokaryotes are
characterized by an accelerating quadratic growth and are size constrained to
be less than about 10,000 genes encoded in DNA sequence of less than about 10
megabases. This paper presents a probabilistic accelerating network model for
prokaryotic gene regulation which closely matches observed statistics by
employing two classes of network nodes (regulatory and non-regulatory) and
directed links whose inbound heads are exponentially distributed over all nodes
and whose outbound tails are preferentially attached to regulatory nodes and
described by a scale free distribution. This model explains the observed
quadratic growth in regulator number with gene number and predicts an upper
prokaryote size limit closely approximating the observed value.


title: Failed "nonaccelerating" models of prokaryote gene regulatory networks

abstract:
  Much current network analysis is predicated on the assumption that important
biological networks will either possess scale free or exponential statistics
which are independent of network size allowing unconstrained network growth
over time. In this paper, we demonstrate that such network growth models are
unable to explain recent comparative genomics results on the growth of
prokaryote regulatory gene networks as a function of gene number. This failure
largely results as prokaryote regulatory gene networks are "accelerating" and
have total link numbers growing faster than linearly with network size and so
can exhibit transitions from stationary to nonstationary statistics and from
random to scale-free to regular statistics at particular critical network
sizes. In the limit, these networks can undergo transitions so marked as to
constrain network sizes to be below some critical value. This is of interest as
the regulatory gene networks of single celled prokaryotes are indeed
characterized by an accelerating quadratic growth with gene count and are size
constrained to be less than about 10,000 genes encoded in DNA sequence of less
than about 10 megabases. We develop two "nonaccelerating" network models of
prokaryote regulatory gene networks in an endeavor to match observation and
demonstrate that these approaches fail to reproduce observed statistics.