title:
Chemical and Structural Disorder in Eumelanins - A Possible Explanation
  for Broad Band Absorbance

abstract:
  We report the results of an experimental and theoretical study of the
electronic and structural properties of a key eumelanin precursor -
5,6,-dihydroxyindole-2-carboxylic acid (DHICA) and its dimeric forms. We have
used optical spectroscopy to follow the oxidative polymerization of DHICA to
eumelanin, and observe red shifting and broadening of the absorption spectrum
as the reaction proceeds. First principles density functional theory
calculations indicate that DHICA oligomers (possible reaction products of
oxidative polymerization) have red shifted HOMO-LUMO gaps with respect to the
monomer. Furthermore, different bonding configurations (leading to oligomers
with different structures) produce a range of gaps. These experimental and
theoretical results lend support to the chemical disorder model where the broad
band monotonic absorption characteristic of all melanins is a consequence of
the superposition of a large number of inhomogeneously broadened Gaussian
transitions associated with each of the components of a melanin ensemble. These
results suggest that the traditional model of eumelanin as an amorphous organic
semiconductor is not required to explain its optical properties, and should be
thoroughly re-examined. These results have significant implications for our
understanding of the physics, chemistry and biological function of these
important biological macromolecules. Indeed, one may speculate that the robust
functionality of melanins in vitro is a direct consequence of its
heterogeneity, i.e. chemical disorder is a "low cost" natural resource in these
systems.


title: Dynamic model for failures in biological systems

abstract:
  A dynamic model for failures in biological organisms is proposed and studied
both analytically and numerically. Each cell in the organism becomes dead under
sufficiently strong stress, and is then allowed to be healed with some
probability. It is found that unlike the case of no healing, the organism in
general does not completely break down even in the presence of noise. Revealed
is the characteristic time evolution that the system tends to resist the stress
longer than the system without healing, followed by sudden breakdown with some
fraction of cells surviving. When the noise is weak, the critical stress beyond
which the system breaks down increases rapidly as the healing parameter is
raised from zero, indicative of the importance of healing in biological
systems.


title: Budded membrane microdomains as regulators for cellular tension

abstract:
  We propose a mechanism for mechanical regulation at the membrane of living
cells, based on the exchange of membrane area between the cell membrane and a
membrane reservoir. The reservoir is composed of invaginated membrane
microdomains which are liable to flatten upon increase of membrane strain,
effectively controlling membrane tension. We show that the domain shape
transition is first order, allowing for coexistence between flat and
invaginated domains. During coexistence, the membrane tension is controlled by
the domains elasticity and by the kinetics of the shape transition. We show
that the tension of the plasma membrane of living cells is inherently transient
and dynamical, and that valuable insights into the organization of the cell
membrane can be obtained by studying the variation of the cell membrane tension
upon mechanical perturbation.


title: Allostery in a Coarse-Grained Model of Protein Dynamics

abstract:
  We propose a criterion for optimal parameter selection in coarse-grained
models of proteins, and develop a refined elastic network model (ENM) of bovine
trypsinogen. The unimodal density-of-states distribution of the trypsinogen ENM
disagrees with the bimodal distribution obtained from an all-atom model;
however, the bimodal distribution is recovered by strengthening interactions
between atoms that are backbone neighbors. We use the backbone-enhanced model
to analyze allosteric mechanisms of trypsinogen, and find relatively strong
communication between the regulatory and active sites.


title: Entropic stabilization of proteins and its proteomic consequences

abstract:
  We report here a new entropic mechanism of protein thermostability due to
residual dynamics of rotamer isomerization in native state. All-atom
simulations show that Lysines have much greater number of accessible rotamers
than Arginines in folded states of proteins. This finding suggests that Lysines
would preferentially entropically stabilize the native state. Indeed we show in
computational experiments that Arginine-to-Lysine amino acid substitutions
result in noticeable stabilization of proteins. We then hypothesize that if
evolution uses this physical mechanisms in its strategies of thermophilic
adaptation then hyperthermostable organisms would have much greater content of
Lysines in their proteomes than of comparable in size and similarly charged
Arginines.. Consistent with that, high-throughput comparative analysis of
complete proteomes shows extremely strong bias towards Arginine-to-Lysine
replacement in hyperthermophilic organisms and overall much greater content of
Lysines than Arginines in hyperthermophiles. This finding cannot be explained
by GC compositional biases. Our study provides an example of how analysis of a
delicate physical mechanism of thermostability helps to resolve a puzzle in
comparative genomics as to why aminoacid compositions of hyperthermophilic
proteomes are significantly biased towards Lysines but not Arginines

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


title:
Alternative mechanisms of structuring biomembranes: Self-assembly vs.
  self-organization

abstract:
  We study two mechanisms for the formation of protein patterns near membranes
of living cells by mathematical modelling. Self-assembly of protein domains by
electrostatic lipid-protein interactions is contrasted with self-organization
due to a nonequilibrium biochemical reaction cycle of proteins near the
membrane. While both processes lead eventually to quite similar patterns, their
evolution occurs on very different length and time scales. Self-assembly
produces periodic protein patterns on a spatial scale below 0.1 micron in a few
seconds followed by extremely slow coarsening, whereas self-organization
results in a pattern wavelength comparable to the typical cell size of 100
micron within a few minutes suggesting different biological functions for the
two processes.


title: The Shapley Value of Phylogenetic Trees

abstract:
  Every weighted tree corresponds naturally to a cooperative game that we call
a "tree game"; it assigns to each subset of leaves the sum of the weights of
the minimal subtree spanned by those leaves. In the context of phylogenetic
trees, the leaves are species and this assignment captures the diversity
present in the coalition of species considered. We consider the Shapley value
of tree games and suggest a biological interpretation. We determine the linear
transformation M that shows the dependence of the Shapley value on the edge
weights of the tree, and we also compute a null space basis of M. Both depend
on the "split counts" of the tree. Finally, we characterize the Shapley value
on tree games by four axioms, a counterpart to Shapley's original theorem on
the larger class of cooperative games.


title:
Monte Carlo modeling of the effect of extreme events on the extinction
  dynamics of animal species with 2-year life cycles

abstract:
  Our paper computationally explores the extinction dynamics of an animal
species effected by a sudden spike in mortality due to an extreme event. In our
study, the animal species has a 2-year life cycle and is endowed with a high
survival probability under normal circumstances. Our proposed approach does not
involve any restraining assumptions concerning environmental variables or
predator-prey relationships. Rather it is based on the simple premise that if
observed on an year-to-year basis, the population size will be noted to either
have gone up or come down as compared to last year. The conceptualization is
borrowed from the theory of asset pricing in stochastic finance. Our results
indicate that an extreme event with a maximum shock size (i.e. the maximum
number of immediate mortalities that may be caused by an extreme event)
exceeding two-thirds the size of the pristine population can potentially drive
any animal species with a 2-year life cycle to extinction for any fecundity
level.


title: Turing Pattern with Proportion Preservation

abstract:
  Although Turing pattern is one of the most universal mechanisms for pattern
formation, in its standard model the number of stripes changes with the system
size, since the wavelength of the pattern is invariant: It fails to preserve
the proportionality of the pattern, i.e., the ratio of the wavelength to the
size, that is often required in biological morphogeneis. To get over this
problem, we show that the Turing pattern can preserve proportionality by
introducing a catalytic chemical whose concentration depends on the system
size. Several plausible mechanisms for such size dependence of the
concentration are discussed. Following this general discussion, two models are
studied in which arising Turing patterns indeed preserve the proportionality.
Relevance of the present mechanism to biological morphogenesis is discussed
from the viewpoint of its generality, robustness, and evolutionary
accessibility.


title:
Time Evolution of Non-Lethal Infectious Diseases: A Semi-Continuous
  Approach

abstract:
  A model describing the dynamics related to the spreading of non-lethal
infectious diseases in a fixed-size population is proposed. The model consists
of a non-linear delay-differential equation describing the time evolution of
the increment in the number of infectious individuals and depends upon a
limited number of parameters. Predictions are in good qualitative agreement
with data on influenza.


title: Some protein interaction data do not exhibit power law statistics

abstract:
  It has been claimed that protein-protein interaction (PPI) networks are
scale-free based on the observation that the node degree sequence follows a
power law. Here we argue that these claims are likely to be based on erroneous
statistical analysis. Typically, the supporting data are presented using
frequency-degree plots. We show that such plots can be misleading, and should
correctly be replaced by rank-degree plots. We provide two PPI network examples
in which the frequency-degree plots appear linear on a log-log scale, but the
rank-degree plots demonstrate that the node degree sequence is far from a power
law. We conclude that at least these PPI networks are not scale-free.


title:
Vascular network remodeling via vessel cooption, regression and growth
  in tumors

abstract:
  The transformation of the regular vasculature in normal tissue into a highly
inhomogeneous tumor specific capillary network is described by a theoretical
model incorporating tumor growth, vessel cooption, neo-vascularization, vessel
collapse and cell death. Compartmentalization of the tumor into several regions
differing in vessel density, diameter and in necrosis is observed for a wide
range of parameters in agreement with the vessel morphology found in human
melanoma. In accord with data for human melanoma the model predicts, that
microvascular density (MVD, regarded as an important diagnostic tool in cancer
treatment, does not necessarily determine the tempo of tumor progression.
Instead it is suggested, that the MVD of the original tissue as well as the
metabolic demand of the individual tumor cell plays the major role in the
initial stages of tumor growth.


title:
Symbology from set theory applied to ecological systems: Gause's
  exclusion principle and applications

abstract:
  We introduce a symbolic representation like set theory to consider ecologic
interactions between species (ECOSET). The ecologic exclusion principle (Gause)
is put in a symbolic way and used as operational tool to consider more complex
cases like interaction with sterile species (SIT technique), two species with
two superposed sources (niche differentiation) and N+P species competing by N
resources, etc. Displacement (regional or characters) is also considered by
using this basic tool. Our symbolic notation gives us an operative and easy way
to consider elementary process in ecology. Some experimental data (laboratory
or field) for ecologic process are re-considered under the optic of this
set-theory.


title: Microbial origin of excess greenhouse gases in glacial ice

abstract:
  We report the discovery of methanogenic archaea that account for abrupt
factor 10 increases in methane concentration found by E. Brook at depths of
2954 and 3036 m in the GISP2 (Greenland Ice Sheet Project 2) ice core. The
total microbial concentration we measured with direct cell counts tracks the
excesses of methanogens that we identified by their F420 fluorescence. The
highly localized (<1 m thick) layers of methanogens suggest flow induced mixing
of layers of microbe laden anaerobic basal ice with glacial ice. The metabolic
rate we found for microbes at 2954 and 3036 m lies roughly on the Arrhenius
line for microbes imprisoned in rock, sediment, and basal ice. Equating the
loss rate of methane recently discovered in the Martian atmosphere to the
production rate by possible methanogens, we estimate that their Martian habitat
would be at a temperature of ~0 degrees C and that the concentration, if
uniformly distributed in a 100 m thick layer, would be 0.04 cell per cubic
centimeter.


title: Towards a Quantitative, Metabolic Theory for Mammalian Sleep

abstract:
  Sleep is one of the most noticeable and widespread phenomena occurring in
multicellular animals. Nevertheless, no consensus for a theory of its origins
has emerged. In particular, no explicit, quantitative theory exists that
elucidates or distinguishes between the myriad hypotheses proposed for sleep.
Here, we develop a general, quantitative theory for mammalian sleep that
relates many of its fundamental parameters to metabolic rate and body size.
Most mechanisms suggested for the function of sleep can be placed in this
framework, e.g., cellular repair of damage caused by metabolic processes and
cortical reorganization to process sensory input. Our theory leads to
predictions for sleep time, sleep cycle time, and REM (rapid-eye-movement) time
as functions of body and brain mass, and explains, for example, why mice sleep
\~14 hours per day relative to the 3.5 hours per day that elephants sleep. Data
for 96 species of mammals, spanning six orders of magnitude in body size, are
consistent with these predictions and provide strong evidence that time scales
for sleep are set by the brain's, not the whole-body, metabolic rate.


title: Characterizing Polygonality in Biological Structures

abstract:
  Several systems involve spatial arrangements of elements such as molecules or
cells, the characterization of which bears important implications to biological
and physical investigations. Traditional approaches to quantify spatial order
and regularity have relied on nearest neighbor distances or the number of sides
of cells. The current work shows that superior features can be achieved by
considering angular regularity. Voronoi tessellations are obtained for each
basic element and the angular regularity is then estimated from the differences
between the angles defined by adjacent cells and a reference angle. In case
this angle is 60 degrees, the measurement quantifies the hexagonality of the
system. Other reference angles can be considered in order to quantify other
types of spatial symmetries. The performance of the angular regularity is
compared with other measurements including the conformity ratio (based on
nearest neighbor distances) and the number of sides of the cells, confirming
its improved sensitivity and discrimination power. The superior performance of
the haxagonality measurement is illustrated also with respect to a real
application concerning the characterization of retinal mosaics.


title:
A learning rule for place fields in a cortical model: theta phase
  precession as a network effect

abstract:
  We show that a model of the hippocampus introduced recently by Scarpetta,
Zhaoping & Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta
phase precession phenomena. In our model, the theta phase precession comes out
as a consequence of the associative-memory-like network dynamics, i.e. the
network's ability to imprint and recall oscillatory patterns, coded both by
phases and amplitudes of oscillation. The learning rule used to imprint the
oscillatory states is a natural generalization of that used for static patterns
in the Hopfield model, and is based on the spike time dependent synaptic
plasticity (STDP), experimentally observed. In agreement with experimental
findings, the place cell's activity appears at consistently earlier phases of
subsequent cycles of the ongoing theta rhythm during a pass through the place
field, while the oscillation amplitude of the place cell's firing rate
increases as the animal approaches the center of the place field and decreases
as the animal leaves the center. The total phase precession of the place cell
is lower than 360 degrees, in agreement with experiments. As the animal enters
a receptive field the place cell's activity comes slightly less than 180
degrees after the phase of maximal pyramidal cell population activity, in
agreement with the findings of Skaggs et al (1996). Our model predicts that the
theta phase is much better correlated with location than with time spent in the
receptive field. Finally, in agreement with the recent experimental findings of
Zugaro et al (2005), our model predicts that theta phase precession persists
after transient intra-hippocampal perturbation.


title:
The Mediterranean deep-sea fauna: historical evolution, bathymetric
  variations and geographical changes

abstract:
  The deep-water fauna of the Mediterranean is characterized by an absence of
distinctive characteristics and by a relative impoverishment. Both are a result
of events after the Messinian salinity crisis (Late Miocene). The three main
classes of phenomena involved in producing or recording these effects are
analysed and discussed: - Historical: Sequential faunal changes during the
Pliocene and thereafter in particular those during the Quaternary glaciations
and still in progress. - Bathymetric: Changes in the vertical aspects of the
Bathyal and Abyssal zones that took place under peculiar conditions, i.e.
homothermy, a relative oligotrophy, the barrier of the Gibraltar sill, and
water mass movement. The deeper the habitat of a species in the Mediterranean,
the more extensive is its distribution elsewhere. - Geographical: There are
strong affinities and relationships between Mediterranean and Atlantic faunas.
Endemic species remain a biogeographical problem. Species always become smaller
in size eastward where they occupy a progressively deeper habitat. Thus, the
existing deep Mediterranean Sea appears to be younger than any other deep-sea
constituent of the World Ocean.


title: Life in solid ice

abstract:
  Some microbes appear to be able to metabolize in glacial ice or permafrost.
The rate depends on temperature, nutrient level, and bioelement availability,
among other factors. I have developed a plausible argument that they do this
while confined in veins filled with acidic or saline solution that provides
nutrients and elements necessary for growth. Here I develop this scenario
further and discuss some of its implications for ice-covered planetary bodies
and for the the origin of life. An accompanying paper in the conference
proceedings (Bay et al.) discusses plans to test this hypothesis using
epifluorescence microscopy of pristine, unmelted ice samples and an optical
biospectrologging tool to assay living and dead microbes in boreholes in
glacial ice.


title:
Probability Models for Degree Distributions of Protein Interaction
  Networks

abstract:
  The degree distribution of many biological and technological networks has
been described as a power-law distribution. While the degree distribution does
not capture all aspects of a network, it has often been suggested that its
functional form contains important clues as to underlying evolutionary
processes that have shaped the network. Generally, the functional form for the
degree distribution has been determined in an ad-hoc fashion, with clear
power-law like behaviour often only extending over a limited range of
connectivities. Here we apply formal model selection techniques to decide which
probability distribution best describes the degree distributions of protein
interaction networks. Contrary to previous studies this well defined approach
suggests that the degree distribution of many molecular networks is often
better described by distributions other than the popular power-law
distribution. This, in turn, suggests that simple, if elegant, models may not
necessarily help in the quantitative understanding of complex biological
processes.\


title:
Does telomere elongation lead to a longer lifespan if cancer is
  considered?

abstract:
  As cell proliferation is limited due to the loss of telomere repeats in DNA
of normal somatic cells during division, telomere attrition can possibly play
an important role in determining the maximum life span of organisms as well as
contribute to the process of biological ageing. With computer simulations of
cell culture development in organisms, which consist of tissues of normal
somatic cells with finite growth, we otain an increase of life span and life
expectancy for longer telomeric DNA in the zygote. By additionally considering
a two-mutation model for carcinogenesis and indefinite proliferation by the
activation of telomerase, we demonstrate that the risk of dying due to cancer
can outweigh the positive effect of longer telomeres on the longevity.


title: Stochastic model for Soj relocation dynamics in Bacillus subtilis

abstract:
  The Bacillus subtilis Spo0J/Soj proteins, implicated in chromosome
segregation and transcriptional regulation, show striking dynamics: Soj
undergoes irregular relocations from pole to pole or nucleoid to nucleoid. Here
we report on a mathematical model of the Soj dynamics. Our model, which is
closely based on the available experimental data, readily generates dynamic Soj
relocations. We show that the irregularity of the relocations may be due to the
stochastic nature of the underlying Spo0J/Soj interactions and diffusion. We
propose explanations for the behavior of several Spo0J/Soj mutants including
the "freezing" of the Soj dynamics observed in filamentous cells. Our approach
underlines the importance of incorporating stochastic effects when modelling
spatiotemporal protein dynamics inside cells.


title: Introns Restructure tRNA Genes of Archaea

abstract: This paper has been withdrawn by the author.


title: Quantitative Measure of Stability in Gene Regulatory Networks

abstract:
  A quantitative measure of stability in stochastic dynamics starts to emerge
in recent experiments on bioswitches. This quantity, similar to the potential
function in mathematics, is deeply rooted in biology, dated back at the
beginning of quantitative description of biological processes: the adaptive
landscape of Wright (1932) and the development landscape of Waddington (1940).
Nevertheless, its quantitative implication has been frequently challenged by
biologists. Recent progresses in quantitative biology begin to meet those
outstanding challenges.


title: Integrin activation - the importance of a positive feedback

abstract:
  Integrins mediate cell adhesion and are essential receptors for the
development and functioning of multicellular organisms. Integrin activation is
known to require both ligand and talin binding and to correlate with cluster
formation but the activation mechanism and precise roles of these processes are
not yet resolved. Here mathematical modeling, with known experimental
parameters, is used to show that the binding of a stabilizing factor, such as
talin, is alone insufficient to enable ligand-dependent integrin activation for
all observed conditions; an additional positive feedback is required.


title: Power laws of complex systems from Extreme physical information

abstract:
  Many complex systems obey allometric, or power, laws y=Yx^{a}. Here y is the
measured value of some system attribute a, Y is a constant, and x is a
stochastic variable. Remarkably, for many living systems the exponent a is
limited to values +or- n/4, n=0,1,2... Here x is the mass of a randomly
selected creature in the population. These quarter-power laws hold for many
attributes, such as pulse rate (n=-1). Allometry has, in the past, been
theoretically justified on a case-by-case basis. An ultimate goal is to find a
common cause for allometry of all types and for both living and nonliving
systems. The principle I - J = extrem. of Extreme physical information (EPI) is
found to provide such a cause. It describes the flow of Fisher information J =>
I from an attribute value a on the cell level to its exterior observation y.
Data y are formed via a system channel function y = f(x,a), with f(x,a) to be
found. Extremizing the difference I - J through variation of f(x,a) results in
a general allometric law f(x,a)= y = Yx^{a}. Darwinian evolution is presumed to
cause a second extremization of I - J, now with respect to the choice of a. The
solution is a=+or-n/4, n=0,1,2..., defining the particular powers of biological
allometry. Under special circumstances, the model predicts that such biological
systems are controlled by but two distinct intracellular information sources.
These sources are conjectured to be cellular DNA and cellular transmembrane ion
gradients


title:
Activation and Protonation of Dinitrogen at the FeMo-Cofactor of
  Nitrogenase

abstract:
  The protonation of N2 bound to the active center of nitrogenase has been
investigated using state-of-the-art DFT calculations. Dinitrogen in the
bridging mode is activated by forming two bonds to Fe sites, which results in a
reduction of the energy for the first hydrogen transfer by 123 kJ/mol. The
axial binding mode with open sulfur bridge is less reactive by 30 kJ/mol and
the energetic ordering of the axial and bridged binding mode is reversed in
favor of the bridging dinitrogen during the first protonation. Protonation of
the central ligand is thermodynamically favorable but kinetically hindered. If
the central ligand is protonated, the proton is transferred to dinitrogen
following the second protonation. Protonation of dinitrogen at the Mo site does
not lead to low-energy intermediates.


title: Does host contact structure reduce pathogen diversity?

abstract:
  We investigate the dynamics of a simple epidemiological model for the
invasion by a pathogen strain of a population where another strain circulates.
We assume that reinfection by the same strain is possible but occurs at a
reduced rate due to acquired immunity. The rate of reinfection by a distinct
strain is also reduced due to cross-immunity. Individual based simulations of
this model on a `small-world' network show that the host contact network
structure significantly affects the outcome of such an invasion, and as a
consequence will affect the patterns of pathogen evolution. In particular, host
populations interacting through a 'small-world' network of contacts support
lower prevalence of infection than well-mixed populations, and the region in
parameter space for which an invading strain can become endemic and coexist
with the circulating strain is smaller, reducing the potential to accommodate
pathogen diversity. We discuss the underlying mechanisms for the reported
effects, and we propose an effective mean-field model to account for the
contact structure of the host population in 'small-world' networks.


title: Nonlinear brain dynamics and many-body field dynamics

abstract:
  We report measurements of the brain activity of subjects engaged in
behavioral exchanges with their environments. We observe brain states which are
characterized by coordinated oscillation of populations of neurons that are
changing rapidly with the evolution of the meaningful relationship between the
subject and its environment, established and maintained by active perception.
Sequential spatial patterns of neural activity with high information content
found in sensory cortices of trained animals between onsets of conditioned
stimuli and conditioned responses resemble cinematographic frames. They are not
readily amenable to description either with classical integrodifferential
equations or with the matrix algebras of neural networks. Their modeling is
provided by field theory from condensed matter physics.


title: Differential gene expression in Bacillus subtilis

abstract:
  Sporulation in Bacillus subtilis serves as a paradigm for the development of
two different cell types (mother cell and prespore) from a single cell. The
mechanism by which the two different developmental programs are initiated has
been much studied but is not well understood. With the help of existing and new
experimental results, a mathematical model has been developed that reproduces
all published in vitro experiments and makes new predictions about the
properties of the system in vivo.


title:
Spectral Detrended Fluctuation Analysis and Its Application to Heart
  Rate Variability Assessment

abstract:
  Detrend fluctuation analysis (DFA) has become a choice method for effective
analysis of a broad variety of nonstationary signals. We show in the present
article that, provided the nonstationary fluctuations occur at a large enough
time scale, an alternative approach can be obtained by using the Fourier series
of the signal. More specifically, signal reconstructions considering Fourier
series with increasing number of higher spectral components are subtracted from
the signal, while the dispersion of such a difference is calculated. The slope
of the loglog representation of the dispersions in terms of the time scale
(reciprocal of the frequency) is calculated and used for the characterization
of the signal. The detrend action in this methodology is performed by the early
incorporation of the low frequency spectral components in the signal
representation. The application of the spectral DFA to the analysis of heart
rate variability data has yielded results which are similar to those obtained
by traditional DFA. Because of the direct relationship with the spectral
content of the analyzed signal, the spectral DFA may be used as a complementary
resource for characterization and analysis of some types of nonstationary
signals.


title:
New data on the systematics and interrelationships of sawfishes
  (Elasmobranchii, Batoidea, Pristiformes)

abstract:
  New characters based on the arrangement and morphology of dermal denticles
show that sawfishes can be divided into two distinctive groups. The first
group, comprising the knifetooth sawfish Anoxypristis cuspidata, is
characterized by tricuspid denticles variably located on both dorsal and
ventral parts of the body. The second group is represented by species of the
genus Pristis, showing an uniform and homogenous dermal covering of
monocuspidate denticles on both dorsal and ventral sides of the body and within
the buccopharyngeal cavity. Pristis is further divided into two subgroups: the
first comprises species with denticles lacking any keels and furrows (the
smalltooth sawfish Pristis pectinata, the green sawfish Pristis zijsron and the
dwarf sawfish Pristis clavata); the second comprises species with denticles
presenting keels and furrows well differentiated on their anterior part (the
common sawfish Pristis pristis, the largetooth sawfish Pristis perotteti and
the greattooth sawfish Pristis microdon). This investigation of the dermal
covering provides results which agree with studies that separate the same two
species groups of Pristis on the basis of other morphological data.


title:
Bayesian Method for Disease QTL Detection and Mapping, using a Case and
  Control Design and DNA Pooling

abstract:
  This paper describes a Bayesian statistical method for determining the
genetic basis of a complex genetic trait. The method uses a sample of unrelated
individuals classified into two groups, for example cases and controls. Each
group is assumed to have been genotyped at a battery of marker loci using a
laboratory effort efficient technique called DNA pooling. The aim is to detect
and map a quantitative trait locus (QTL) that is not one of the typed markers.
The method works by conducting an exact Bayesian analysis under a number of
simplifying population genetic assumptions that are somewhat unrealistic.
Despite this, the method is shown to perform acceptably on datasets simulated
under a more realistic model, and furthermore is shown to outperform classical
single point methods.


title:
Modeling genome evolution with a diffusion approximation of a
  birth-and-death process

abstract:
  In our previous studies, we developed discrete-space Birth, Death and
Innovation Models (BDIM) of genome evolution. These models explain the origin
of the characteristic Pareto distribution of paralogous gene family sizes in
genomes, and model parameters that provide for the evolution of these
distributions within a realistic timeframe have been identified. Here we
develop the diffusion version of BDIM whose dynamics is described by the
Fokker-Plank equation and the stationary solution could be any specified Pareto
function. The diffusion models have time-dependent solutions of a special kind,
namely, the generalized self-similar solutions, which describe the transition
from one stationary distribution of the system to another; this provides for
the possibility of examining the temporal dynamics of genome evolution.
Analysis of the generalized self-similar solutions of the diffusion BDIM
reveals a biphasic curve of genome growth in which the initial, relatively
short, self-accelerating phase is followed by a prolonged phase of slow
deceleration. In biological terms, this regime of evolution can be tentatively
interpreted as a punctuated-equilibrium-like phenomenon such that whereby
evolutionary transitions are accompanied by rapid gene amplification and
innovation, followed by slow relaxation to a new stationary state.


title:
Simple stochastic birth and death models of genome evolution: Was there
  enough time for us to evolve?

abstract:
  We show that simple stochastic models of genome evolution lead to power law
asymptotics of protein domain family size distribution. These models, called
Birth, Death and Innovation Models (BDIM), represent a special class of
balanced birth-and-death processes, in which domain duplication and deletion
rates are asymptotically equal up to the second order. The simplest, linear
BDIM shows an excellent fit to the observed distributions of domain family size
in diverse prokaryotic and eukaryotic genomes. However, the stochastic version
of the linear BDIM explored here predicts that the actual size of large
paralogous families is reached on an unrealistically long timescale. We show
that introduction of non-linearity, which might be interpreted as interaction
of a particular order between individual family members, allows the model to
achieve genome evolution rates that are much better compatible with the current
estimates of the rates of individual duplication/loss events.


title:
Spontaneous polarization in eukaryotic gradient sensing: A mathematical
  model based on mutual inhibition of frontness and backness pathways

abstract:
  A key problem of eukaryotic cell motility is the signaling mechanism of
chemoattractant gradient sensing. Recent experiments have revealed the
molecular correlate of gradient sensing: Frontness molecules, such as PI3P and
Rac, localize at the front end of the cell, and backness molecules, such as Rho
and myosin II, accumulate at the back of the cell. Importantly, this
frontness-backness polarization occurs "spontaneously" even if the cells are
exposed to uniform chemoattractant profiles. The spontaneous polarization
suggests that the gradient sensing machinery undergoes a Turing bifurcation.
This has led to several classical activator-inhibitor and activator-substrate
models which identify the frontness molecules with the activator. Conspicuously
absent from these models is any accounting of the backness molecules. This
stands in sharp contrast to experiments which show that the backness pathways
inhibit the frontness pathways. Here, we formulate a model based on the
mutually inhibitory interaction between the frontness and backness pathways.
The model builds upon the mutual inhibition model proposed by Bourne and
coworkers (Xu et al, Cell, 114, 201--214, 2003). We show that mutual inhibition
alone, without the help of any positive feedback, can trigger spontaneous
polarization of the frontness and backness pathways. The spatial distribution
of the frontness and backness molecules in response to inhbition and activation
of the frontness and backness pathways are consistent with those observed in
experiments. Furthermore, depending on the parameter values, the model yields
spatial distributions corresponding to chemoattraction (frontness pathways
in-phase with the external gradient) and chemorepulsion (frontness pathways
out-of-phase with the external gradient).


title: Dynamics of DNA Ejection From Bacteriophage

abstract:
  The ejection of DNA from a bacterial virus (``phage'') into its host cell is
a biologically important example of the translocation of a macromolecular chain
along its length through a membrane. The simplest mechanism for this motion is
diffusion, but in the case of phage ejection a significant driving force
derives from the high degree of stress to which the DNA is subjected in the
viral capsid. The translocation is further sped up by the ratcheting and
entropic forces associated with proteins that bind to the viral DNA in the host
cell cytoplasm. We formulate a generalized diffusion equation that includes
these various pushing and pulling effects and make estimates of the
corresponding speed-ups in the overall translocation process. Stress in the
capsid is the dominant factor throughout early ejection, with the pull due to
binding particles taking over at later stages. Confinement effects are also
investigated, in the case where the phage injects its DNA into a volume
comparable to the capsid size. Our results suggest a series of in vitro
experiments involving the ejection of DNA into vesicles filled with varying
amounts of binding proteins from phage whose state of stress is controlled by
ambient salt conditions or by tuning genome length.


title:
Synchronization and spindle oscillation in noisy
  integrate-and-fire-or-burst neurons with inhibitory coupling

abstract:
  We propose another integrate-and-fire model as a single neuron model. We
study a globally coupled noisy integrate-and-fire model with inhibitory
interaction using the Fokker-Planck equation and the Langevin equation, and
find a reentrant transition of oscillatory states. Intermittent time evolutions
of neuron firing are found in strongly inhibited systems. We propose another
integrate-and-fire-or-burst model including the dynamics of the low-threshold
Ca$^{2+}$ current based on the new integrate-and-fire model. We study a
globally coupled noisy integrate-and-fire-or-burst model with inhibitory
interaction using the Fokker-Planck equation, and find bistability of the tonic
mode and burst mode. Doubly periodic oscillation appears in a coupled system of
two neuron assemblies, which is similar to the spindle oscillation in thalamic
cells.


title: Modeling Human Erythrocyte Shape and Size Abnormalities

abstract:
  We present simple parametric equations in terms of Jacobi elliptic functions
that provide a realistic model of the shape of human normal erythrocytes as
well as of variations in size (anisocytosis) and shape (poikilocytosis)
thereof. We illustrate our results with parameterizations of microcytes,
macrocytes and stomatocytes, and show the applicability of these
parameterizations to the numerical calculation of the induced transmembrane
voltage in microcytes, macrocytes and stomatocytes exposed to an external RF
field of 1800 MHz.


title:
Phi-values in protein folding kinetics have energetic and structural
  components

abstract:
  Phi-values are experimental measures of how the kinetics of protein folding
is changed by single-site mutations. Phi-values measure energetic quantities,
but are often interpreted in terms of the structures of the transition state
ensemble. Here we describe a simple analytical model of the folding kinetics in
terms of the formation of protein substructures. The model shows that
Phi-values have both structural and energetic components. In addition, it
provides a natural and general interpretation of "nonclassical" Phi-values
(i.e., less than zero, or greater than one). The model reproduces the
Phi-values for 20 single-residue mutations in the alpha-helix of the protein
CI2, including several nonclassical Phi-values, in good agreement with
experiments.


title: Biological applications of the theory of birth-and-death processes

abstract:
  In this review, we discuss the applications of the theory of birth-and-death
processes to problems in biology, primarily, those of evolutionary genomics.
The mathematical principles of the theory of these processes are briefly
described. Birth-and-death processes, with some straightforward additions such
as innovation, are a simple, natural formal framework for modeling a vast
variety of biological processes such as population dynamics, speciation, genome
evolution, including growth of paralogous gene families and horizontal gene
transfer, and somatic evolution of cancers. We further describe how empirical
data, e.g., distributions of paralogous gene family size, can be used to choose
the model that best reflects the actual course of evolution among different
versions of birth-death-and-innovation models. It is concluded that
birth-and-death processes, thanks to their mathematical transparency,
flexibility and relevance to fundamental biological process, are going to be an
indispensable mathematical tool for the burgeoning field of systems biology.


title:
Modeling the Role of the Cell Cycle in Regulating Proteus mirabilis
  Swarm-Colony Development

abstract:
  We present models and computational results which indicate that the spatial
and temporal regularity seen in Proteus mirabilis swarm-colony development is
largely an expression of a sharp age of dedifferentiation in the cell cycle
from motile swarmer cells to immotile dividing cells (also called swimmer or
vegetative cells.) This contrasts strongly with reaction-diffusion models of
Proteus behavior that ignore or average out the age structure of the cell
population and instead use only density-dependent mechanisms. We argue the
necessity of retaining the explicit age structure, and suggest experiments that
may help determine the underlying mechanisms empirically. Consequently, we
advocate Proteus as a model organism for a multiscale understanding of how and
to what extent the life cycle of individual cells affects the macroscopic
behavior of a biological system.


title:
Dynamics of Heterogeneous Populations and Communities and Evolution of
  Distributions

abstract:
  Most population models assume that individuals within a given population are
identical, that is, the fundamental role of variation is ignored. Inhomogeneous
models of populations and communities allow for birth and death rates to vary
among individuals; recently, theorems of existence and asymptotic of solutions
of such models were investigated. Here we develop another approach to modeling
heterogeneous populations by reducing the model to the Cauchy problem for a
special system of ODEs. As a result, the total population size and current
distribution of the vector-parameter can be found in explicit analytical form
or computed effectively. The developed approach is extended to the models of
inhomogeneous communities.


title:
Prediction and predictability of global epidemics: the role of the
  airline transportation network

abstract:
  The systematic study of large-scale networks has unveiled the ubiquitous
presence of connectivity patterns characterized by large scale heterogeneities
and unbounded statistical fluctuations. These features affect dramatically the
behavior of the diffusion processes occurring on networks, determining the
ensuing statistical properties of their evolution pattern and dynamics. In this
paper, we investigate the role of the large scale properties of the airline
transportation network in determining the global evolution of emerging disease.
We present a stochastic computational framework for the forecast of global
epidemics that considers the complete world-wide air travel infrastructure
complemented with census population data. We address two basic issues in global
epidemic modeling: i) We study the role of the large scale properties of the
airline transportation network in determining the global diffusion pattern of
emerging diseases; ii) We evaluate the reliability of forecasts and outbreak
scenarios with respect to the intrinsic stochasticity of disease transmission
and traffic flows. In order to address these issues we define a set of novel
quantitative measures able to characterize the level of heterogeneity and
predictability of the epidemic pattern. These measures may be used for the
analysis of containment policies and epidemic risk assessment.


title: Conspiracy in bacterial genomes

abstract:
  The rank ordered distribution of the codon usage frequencies for 123
bacteriae is best fitted by a three parameters function that is the sum of a
constant, an exponential and a linear term in the rank n. The parameters depend
(two parabolically) from the total GC content. The rank ordered distribution of
the amino acids is fitted by a straight line. The Shannon entropy computed over
all the codons is well fitted by a parabola in the GC content, while the
partial entropies computed over subsets of the codons show peculiar different
behavior, exhibiting therefore a first conspiracy effect. Moreover the sum of
the codon usage frequencies over particular sets, e.g. with C and A
(respectively G and U) as i-th nucleotide, shows a clear linear dependence from
the GC content, exhibiting another conspiracy effect.


title:
Detection of confinement and jumps in single molecule membrane
  trajectories

abstract:
  We propose a novel variant of the algorithm by Simson et al. [R. Simson, E.D.
Sheets, K. Jacobson, Biophys. J. 69, 989 (1995)]. Their algorithm was developed
to detect transient confinement zones in experimental single particle tracking
trajectories of diffusing membrane proteins or lipids. We show that our
algorithm is able to detect confinement in a wider class of confining potential
shapes than Simson et al.'s one. Furthermore it enables to detect not only
temporary confinement but also jumps between confinement zones. Jumps are
predicted by membrane skeleton fence and picket models. In the case of
experimental trajectories of $\mu$-opioid receptors, which belong to the family
of G-protein-coupled receptors involved in a signal transduction pathway, this
algorithm confirms that confinement cannot be explained solely by rigid fences.


title:
Parameters of proteome evolution from histograms of amino-acid sequence
  identities of paralogous proteins

abstract:
  The evolution of the full repertoire of proteins encoded in a given genome is
mostly driven by gene duplications, deletions, and sequence modifications of
existing proteins. Indirect information about relative rates and other
intrinsic parameters of these three basic processes is contained in the
proteome-wide distribution of sequence identities of pairs of paralogous
proteins. We introduce a simple mathematical framework based on a stochastic
birth-and-death model that allows one to extract some of this information and
apply it to the set of all pairs of paralogous proteins in seven model
organisms. It was found that the histogram of sequence identities p generated
by an all-to-all alignment of all protein sequences encoded in a genome is well
fitted with a power-law form ~p^(-gamma) with the value of the exponent gamma
around 4 for the majority of organisms used in this study. This implies that
the intra-protein variability of substitution rates is best described by the
Gamma-distribution with the exponent alpha ~ 0.33. We separately measure the
short-term (``raw'') duplication and deletion rates r*_dup, r*_del which
include gene copies that will be removed soon after the duplication event and
their dramatically reduced long-term counterparts r_dup, r_del. Systematic
trends of each of the four duplication/deletion rates with the total number of
genes in the genome were analyzed. All but the deletion rate of recent
duplicates r*_del were shown to systematically increase with N_genes.
Abnormally flat shapes of sequence identity histograms observed for yeast and
human are consistent with lineages leading to these organisms undergoing one or
more whole-genome duplications.


title: Simulation of Rapoport's rule for latitudinal species spread

abstract:
  Rapoport's rule claims that latitudinal ranges of plant and animal species
are generally smaller at low than at high latitudes. However, doubts as to the
generality of the rule have been expressed, because studies providing evidence
against the rule are more numerous than those in support of it. In groups for
which support has been provided, the trend of increasing latitudinal ranges
with latitude is restricted to or at least most distinct at high latitudes,
suggesting that the effect may be a local phenomenon, for example the result of
glaciations. Here we test the rule using two models, a simple one-dimensional
one with a fixed number of animals expanding in a northern or southerly
direction only, and the evolutionary/ecological Chowdhury model using birth,
ageing, death, mutation, speciation, prey-predator relations and food levels.
Simulations with both models gave results contradicting Rapoport's rule. In the
first, latitudinal ranges were roughly independent of latitude, in the second,
latitudinal ranges were greatest at low latitudes, as also shown empirically
for some well studied groups of animals.


title: Dynamics and pattern formation in invasive tumor growth

abstract:
  In this work, we study the in-vitro dynamics of the most malignant form of
the primary brain tumor: Glioblastoma Multiforme. Typically, the growing tumor
consists of the inner dense proliferating zone and the outer less dense
invasive region. Experiments with different types of cells show qualitatively
different behavior. Wild-type cells invade a spherically symmetric manner, but
mutant cells are organized in tenuous branches. We formulate a model for this
sort of growth using two coupled reaction-diffusion equations for the cell and
nutrient concentrations. When the ratio of the nutrient and cell diffusion
coefficients exceeds some critical value, the plane propagating front becomes
unstable with respect to transversal perturbations. The instability threshold
and the full phase-plane diagram in the parameter space are determined. The
results are in a good agreement with experimental findings for the two types of
cells.


title: A stochastic model for wound healing

abstract:
  We present a discrete stochastic model which represents many of the salient
features of the biological process of wound healing. The model describes fronts
of cells invading a wound. We have numerical results in one and two dimensions.
In one dimension we can give analytic results for the front speed as a power
series expansion in a parameter, p, that gives the relative size of
proliferation and diffusion processes for the invading cells. In two dimensions
the model becomes the Eden model for p near 1. In both one and two dimensions
for small p, front propagation for this model should approach that of the
Fisher-Kolmogorov equation. However, as in other cases, this discrete model
approaches Fisher-Kolmogorov behavior slowly.


title: A helicoidal transfer matrix model for inhomogeneous DNA melting

abstract:
  An inhomogeneous helicoidal nearest-neighbor model with continuous degrees of
freedom is shown to predict the same DNA melting properties as traditional
long-range Ising models, for free DNA molecules in solution, as well as
superhelically stressed DNA with a fixed linking number constraint. Without
loss of accuracy, the continuous degrees of freedom can be discretized using a
minimal number of discretization points, yielding an effective transfer matrix
model of modest dimension (d=36). The resulting algorithms to compute DNA
melting profiles are both simple and efficient.


title: Neuromodulation Influences Synchronization and Intrinsic Read-out

abstract:
  Background: The roles of neuromodulation in a neural network, such as in a
cortical microcolumn, are still incompletely understood. Neuromodulation
influences neural processing by presynaptic and postsynaptic regulation of
synaptic efficacy. Neuromodulation also affects ion channels and intrinsic
excitability. Methods: Synaptic efficacy modulation is an effective way to
rapidly alter network density and topology. We alter network topology and
density to measure the effect on spike synchronization. We also operate with
differently parameterized neuron models which alter the neurons intrinsic
excitability, i.e., activation function. Results: We find that (a) fast
synaptic efficacy modulation influences the amount of correlated spiking in a
network. Also, (b) synchronization in a network influences the read-out of
intrinsic properties. Highly synchronous input drives neurons, such that
differences in intrinsic properties disappear, while asynchronous input lets
intrinsic properties determine output behavior. Thus, altering network topology
can alter the balance between intrinsically vs. synaptically driven network
activity. Conclusion: We conclude that neuromodulation may allow a network to
shift between a more synchronized transmission mode and a more asynchronous
intrinsic read-out mode. This has significant implications for our
understanding of the flexibility of cortical computations.


title: Bacteriophage-mediated competition in Bordetella bacteria

abstract:
  Apparent competition between species is believed to be one of the principle
driving forces that structure ecological communities, although the precise
mecha nisms have yet to be characterized. Here we develop a model system that
isolates phage-mediated interactions by neutralizing resource competition using
two genetically identical Bordetella bronchiseptica strains that differ only in
that one is the carrier of a phage and the other is susceptible to the phage.
We observe and quantify the competitive advantage of the bacterial strain
bearing the prophage in both invading and in resisting invasion by bacteria
susceptible to the phage, and use our measurements to develop a mathematical
model of phage-mediated competition. The model predicts, and experimental
evidence confirms, that the competitive advantage conferred by the phage
depends only on the relative phage pathology and is independent of other phage
and host parameters. This work combines experimental and mathematical
approaches to the study of phage-driven competition, and provides an
experimentally tested framework for evaluation of the effects of
pathogens/parasites on interspecific competition.


title: A complex adaptive systems approach to the kinetic folding of RNA

abstract:
  The kinetic folding of RNA sequences into secondary structures is modeled as
a complex adaptive system, the components of which are possible RNA structural
rearrangements (SRs) and their associated bases and base pairs. RNA bases and
base pairs engage in local stacking interactions that determine the
probabilities (or fitnesses) of possible SRs. Meanwhile, selection operates at
the level of SRs; an autonomous stochastic process periodically (i.e., from one
time step to another) selects a subset of possible SRs for realization based on
the fitnesses of the SRs. Using examples based on selected natural and
synthetic RNAs, the model is shown to qualitatively reproduce characteristic
(nonlinear) RNA folding dynamics such as the attainment by RNAs of alternative
stable states. Possible applications of the model to the analysis of properties
of fitness landscapes, and of the RNA sequence to structure mapping are
discussed.


title:
Effects of correlated interactions in a biological coevolution model
  with individual-based dynamics

abstract:
  Models of coevolution have recently been studied, in which a species is
defined by a genome in the form of a bitstring, and the interactions between
species i and j are given by a fixed matrix with independent, randomly
distributed elements M_{ij}. A consequence of the stochastic independence is
that species whose genotypes differ even by a single bit may have completely
different phenotypes. This is clearly unrealistic, as closely related species
should be similar in their interactions with the rest of the ecosystem. Here we
therefore study a model, in which the M_{ij} are correlated to a controllable
degree. We calculate, both analytically and numerically, the correlation
function for matrix elements M_{ij} and M_{kl} versus the Hamming distance
between the bitstrings representing the species. We compare Monte Carlo
simulations of coevolution models with uncorrelated and correlated
interactions. In particular, we consider the lifetimes of individual species.
The species-lifetime distribution is close to a power law with an exponent near
-2 in both uncorrelated and correlated cases. The durations of quasi-steady
states and power spectral densities for the diversity indices display
noticeable differences. However, some qualitative features, like 1/f behaviour
in power spectral densities for the diversity indices, are not affected by the
correlations in the interaction matrix.


title:
A base pairing model of duplex formation I: Watson-Crick pairing
  geometries

abstract:
  We present a base-pairing model of oligonuleotide duplex formation and show
in detail its equivalence to the Nearest-Neighbour dimer methods from fits to
free energy of duplex formation data for short DNA-DNA and DNA-RNA hybrids
containing only Watson Crick pairs. In this approach the connection between
rank-deficient polymer and rank-determinant oligonucleotide parameter, sets for
DNA duplexes is transparent. The method is generalised to include RNA/DNA
hybrids where the rank-deficient model with 11 dimer parameters in fact
provides marginally improved predictions relative to the standard method with
16 independent dimer parameters ($\Delta G$ mean errors of 4.5 and 5.4 %
respectively).


title:
Signal analysis of impulse response functions in MR- and CT-measurements
  of cerebral blood flow

abstract:
  The impulse response function (IRF) of a localized bolus in cerebral blood
flow codes important information on the tissue type. It is indirectly
accessible both from MR- and CT-imaging methods, at least in principle. In
practice, however, noise and limited signal resolution render standard
deconvolution techniques almost useless. Parametric signal descriptions look
more promising, and it is the aim of this contribution to develop some
improvements along this line.


title: Flow correlated percolation during vascular network formation in tumors

abstract:
  A theoretical model based on the molecular interactions between a growing
tumor and a dynamically evolving blood vessel network describes the
transformation of the regular vasculature in normal tissues into a highly
inhomogeneous tumor specific capillary network. The emerging morphology,
characterized by the compartmentalization of the tumor into several regions
differing in vessel density, diameter and necrosis, is in accordance with
experimental data for human melanoma. Vessel collapse due to a combination of
severely reduced blood flow and solid stress exerted by the tumor, leads to a
correlated percolation process that is driven towards criticality by the
mechanism of hydrodynamic vessel stabilization.


title: A core genetic module : the Mixed Feedback Loop

abstract:
  The so-called Mixed Feedback Loop (MFL) is a small two-gene network where
protein A regulates the transcription of protein B and the two proteins form a
heterodimer. It has been found to be statistically over-represented in
statistical analyses of gene and protein interaction databases and to lie at
the core of several computer-generated genetic networks. Here, we propose and
mathematically study a model of the MFL and show that, by itself, it can serve
both as a bistable switch and as a clock (an oscillator) depending on kinetic
parameters. The MFL phase diagram as well as a detailed description of the
nonlinear oscillation regime are presented and some biological examples are
discussed. The results emphasize the role of protein interactions in the
function of genetic modules and the usefulness of modelling RNA dynamics
explicitly.


title:
A framework for detection and classification of events in neural
  activity

abstract:
  We present a method for the real time prediction of punctate events in neural
activity, based on the time-frequency spectrum of the signal, applicable both
to continuous processes like local field potentials (LFP) as well as to spike
trains. We test it on recordings of LFP and spiking activity acquired
previously from the lateral intraparietal area (LIP) of macaque monkeys
performing a memory-saccade task. In contrast to earlier work, where trials
with known start times were classified, our method detects and classifies
trials directly from the data. It provides a means to quantitatively compare
and contrast the content of LFP signals and spike trains: we find that the
detector performance based on the LFP matches the performance based on spike
rates. The method should find application in the development of neural
prosthetics based on the LFP signal. Our approach uses a new feature vector,
which we call the 2D cepstrum.


title: Chromosome Oscillations in Mitosis

abstract:
  Successful cell division requires a tight regulation of chromosome motion via
the activity of molecular motors. Many of the key players at the origin of the
forces generating the movement have been identified, but their spatial and
temporal organization remains elusive. The protein complex Kinetochore on the
chromosome associates with microtubules emanating from one of the spindle poles
and drives the chromosome toward the pole. Chromokinesin motors on the
chromosome arms also interact with microtubules, ejecting the chromosome away
from the pole. In animal cells, a monooriented chromosome (associated to a
single pole) periodically switches between phases of poleward and away from the
pole movement[, a behavior tentatively explained so far by the existence of a
complex switching mechanism within the kinetochore itself. Here we show that
the interplay between the morphology of the mitotic spindle and the collective
kinetics of chromokinesins can account for the highly non-linear periodic
chromosome motion. Our analysis provides a natural explanation for the origin
of chromosome directional instability and for the mechanism by which
chromosomes feel their position in space.


title: Neighbor joining with phylogenetic diversity estimates

abstract:
  The Neighbor-Joining algorithm is a recursive procedure for reconstructing
trees that is based on a transformation of pairwise distances between leaves.
We present a generalization of the neighbor-joining transformation, which uses
estimates of phylogenetic diversity rather than pairwise distances in the tree.
This leads to an improved neighbor-joining algorithm whose total running time
is still polynomial in the number of taxa. On simulated data, the method
outperforms other distance-based methods.
  We have implemented neighbor-joining for subtree weights in a program called
MJOIN which is freely available under the Gnu Public License at
http://bio.math.berkeley.edu/mjoin/ .


title: Food Webs: Experts Consuming Families of Experts

abstract:
  The question what determines the structure of natural food webs has been
listed among the nine most important unanswered questions in ecology. It arises
naturally from many problems related to ecosystem stability and resilience. The
traditional view is that population-dynamical stability is crucial for
understanding the observed structures. But phylogeny (evolutionary history) has
also been suggested as the dominant mechanism. Here we show that observed
topological features of predatory food webs can be reproduced to unprecedented
accuracy by a mechanism taking into account only phylogeny, size constraints,
and the heredity of the trophically relevant traits of prey and predators. The
analysis reveals a tendency to avoid resource competition rather than apparent
competition. In food webs with many parasites this pattern is reversed.


title:
High local genetic diversity and low outcrossing rate in Caenorhabditis
  elegans natural populations

abstract:
  Background: Caenorhabditis elegans is a major model system in biology, yet
very little is known about its biology outside the laboratory. Especially, its
unusual mode of reproduction with self-fertile hermaphrodites and facultative
males raises the question of its frequency of outcrossing in natural
populations. Results: We describe the first analysis of C. elegans individuals
sampled directly from natural populations. C. elegans is found predominantly in
the dauer stage and with a very low frequency of males compared with
hermaphrodites. While C. elegans was previously shown to display a low
worldwide genetic diversity, we find by comparison a surprisingly high local
genetic diversity of C. elegans populations; this local diversity is
contributed in great part by immigration of new alleles rather than by
mutation. Our results on heterozygote frequency, male frequency and linkage
disequilibrium furthermore show that selfing is the predominant mode of
reproduction in C. elegans natural populations, yet that infrequent outcrossing
events occur, at a rate of approximately 1%. Conclusions: Our results give a
first insight in the biology of C. elegans in the natural populations. They
demonstrate that local populations of C. elegans are genetically diverse and
that a low frequency of outcrossing allows for the recombination of these
locally diverse genotypes.


title: Coupled dynamics of RNA folding and nanopore translocation

abstract:
  The translocation of structured RNA or DNA molecules through narrow pores
necessitates the opening of all base pairs. Here, we study the interplay
between the dynamics of translocation and base-pairing theoretically, using
kinetic Monte Carlo simulations and analytical methods. We find that the
transient formation of basepairs that do not occur in the ground state can
significantly speed up translocation.


title:
An inversion in the wiring of an intercellular signal: evolution of Wnt
  signaling in the nematode vulva

abstract:
  Signal transduction pathways are largely conserved throughout the animal
kingdom. The repertoire of pathways is limited and each pathway is used in
different intercellular signaling events during the development of a given
animal. For example, Wnt signaling is recruited, sometimes redundantly with
other molecular pathways, in four cell specification events during
Caenorhabditis elegans vulva development, including the activation of vulval
differentiation. Strikingly, a recent study finds that Wnts act to repress
vulval differentiation in the nematode Pristionchus pacificus, demonstrating
evolutionary flexibility in the use of intercellular signaling pathways.


title: Computational Fluid Dynamic Approach for Biological System Modeling

abstract:
  Various biological system models have been proposed in systems biology, which
are based on the complex biological reactions kinetic of various components.
These models are not practical because we lack of kinetic information. In this
paper, it is found that the enzymatic reaction and multi-order reaction rate is
often controlled by the transport of the reactants in biological systems. A
Computational Fluid Dynamic (CFD) approach, which is based on transport of the
components and kinetics of biological reactions, is introduced for biological
system modeling. We apply this approach to a biological wastewater treatment
system for the study of metabolism of organic carbon substrates and the
population of microbial. The results show that CFD model coupled with reaction
kinetics is more accurate and more feasible than kinetic models for biological
system modeling.


title: Hierarchical Features of Large-Scale Cortical Connectivity

abstract:
  The analysis of complex networks has revealed patterns of organization in a
variety of natural and artificial systems, including neuronal networks of the
brain at multiple scales. In this paper, we describe a novel analysis of the
large-scale connectivity between regions of the mammalian cerebral cortex,
utilizing a set of hierarchical measurements proposed recently. We examine
previously identified functional clusters of brain regions in macaque visual
cortex and cat cortex and find significant differences between such clusters in
terms of several hierarchical measures, revealing differences in how these
clusters are embedded in the overall cortical architecture. For example, the
ventral cluster of visual cortex maintains structurally more segregated, less
divergent connections than the dorsal cluster, which may point to functionally
different roles of their constituent brain regions.


title: Adaptation in simple and complex fitness landscapes

abstract:
  This is an introductory review of deterministic mutation-selection models for
asexual populations (i.e., quasispecies theory) and related topics. First, the
basic concepts of fitness, mutations, and sequence space are introduced.
Different types of mutation-selection dynamics are defined and their relation
to problems of statistical physics are outlined. Then the stationary population
distribution in simple, single peak fitness landscapes is discussed at length,
with particular emphasis on the error threshold phenomenon. Extensions of the
theory covering e.g. epistatic interactions, diploid organisms,
semiconservative replication and time-dependent fitness peaks are briefly
described. A further section is devoted to randomly rugged fitness landscapes,
which may display fitness correlations of various degree as well as extended
neutral networks. The final two sections address evolutionary dynamics in both
rugged and smooth fitness landscapes, and provide a brief overview of pertinent
experiments.


title: Proteins and polymers

abstract:
  Proteins, chain molecules of amino acids, behave in ways which are similar to
each other yet quite distinct from standard compact polymers. We demonstrate
that the Flory theorem, derived for polymer melts, holds for compact protein
native state structures and is not incompatible with the existence of
structured building blocks such as $\alpha$-helices and $\beta$-strands. We
present a discussion on how the notion of the thickness of a polymer chain,
besides being useful in describing a chain molecule in the continuum limit,
plays a vital role in interpolating between conventional polymer physics and
the phase of matter associated with protein structures.


title: First passage times and asymmetry of DNA translocation

abstract:
  Motivated by experiments in which single-stranded DNA with a short hairpin
loop at one end undergoes unforced diffusion through a narrow pore, we study
the first passage times for a particle, executing one-dimensional brownian
motion in an asymmetric sawtooth potential, to exit one of the boundaries. We
consider the first passage times for the case of classical diffusion,
characterized by a mean-square displacement of the form $< (\Delta x)^2> \sim
t$, and for the case of anomalous diffusion or subdiffusion, characterized by a
mean-square displacement of the form $< (\Delta x)^2> \sim t^{\gamma}$ with
$0<\gamma<1$. In the context of classical diffusion, we obtain an expression
for the mean first passage time and show that this quantity changes when the
direction of the sawtooth is reversed or, equivalently, when the reflecting and
absorbing boundaries are exchanged. We discuss at which numbers of `teeth' $N$
(or number of DNA nucleotides) and at which heights of the sawtooth potential
this difference becomes significant. For large $N$, it is well known that the
mean first passage time scales as $N^2$. In the context of subdiffusion, the
mean first passage time does not exist. Therefore we obtain instead the
distribution of first passage times in the limit of long times. We show that
the prefactor in the power relation for this distribution is simply the
expression for the mean first passage time in classical diffusion. We also
describe a hypothetical experiment to calculate the average of the first
passage times for a fraction of passage events that each end within some time
$t^*$. We show that this average first passage time scales as $N^{2/\gamma}$ in
subdiffusion.

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


title:
Time Reversal of the Increasing Geometrical Progression of the
  Population of a Simple Biological Specie

abstract:
  In this work we consider time reversal of the increasing geometrical
progression of the population of a simple biological species without any
enemies (predators) in the appropriate environment with unlimited resources
(food, territory, etc.). It is shown that such time reversal corresponds to
appearance of the cannibalism, i.e. self-predaciousness or self-damping
phenomena which can be described by a type of difference Verhulst equation.


title: On the Complexity of the Single Individual SNP Haplotyping Problem

abstract:
  We present several new results pertaining to haplotyping. These results
concern the combinatorial problem of reconstructing haplotypes from incomplete
and/or imperfectly sequenced haplotype fragments. We consider the complexity of
the problems Minimum Error Correction (MEC) and Longest Haplotype
Reconstruction (LHR) for different restrictions on the input data.
Specifically, we look at the gapless case, where every row of the input
corresponds to a gapless haplotype-fragment, and the 1-gap case, where at most
one gap per fragment is allowed. We prove that MEC is APX-hard in the 1-gap
case and still NP-hard in the gapless case. In addition, we question earlier
claims that MEC is NP-hard even when the input matrix is restricted to being
completely binary. Concerning LHR, we show that this problem is NP-hard and
APX-hard in the 1-gap case (and thus also in the general case), but is
polynomial time solvable in the gapless case.


title: Effects of fast presynaptic noise in attractor neural networks

abstract:
  We study both analytically and numerically the effect of presynaptic noise on
the transmission of information in attractor neural networks. The noise occurs
on a very short-time scale compared to that for the neuron dynamics and it
produces short-time synaptic depression. This is inspired in recent
neurobiological findings that show that synaptic strength may either increase
or decrease on a short-time scale depending on presynaptic activity. We thus
describe a mechanism by which fast presynaptic noise enhances the neural
network sensitivity to an external stimulus. The reason for this is that, in
general, the presynaptic noise induces nonequilibrium behavior and,
consequently, the space of fixed points is qualitatively modified in such a way
that the system can easily scape from the attractor. As a result, the model
shows, in addition to pattern recognition, class identification and
categorization, which may be relevant to the understanding of some of the brain
complex tasks.


title:
Selective advantage for multicellular replicative strategies: A two-cell
  example

abstract:
  This paper develops a quasispecies model where cells can adopt a two-cell
survival strategy. Within this strategy, pairs of cells join together, at which
point one of the cells sacrifices its own replicative ability for the sake of
the other cell. We develop a simplified model for the evolutionary dynamics of
this process, allowing us to solve for the steady-state using standard
approaches from quasispecies theory. We find that our model exhibits two
distinct regimes of behavior: At low concentrations of limiting resource, the
two-cell strategy outcompetes the single-cell survival strategy, while at high
concentrations of limiting resource, the single-cell survival strategy
dominates. Associated with the two solution regimes of our model is a
localization to delocalization transition over the portion of the genome coding
for the multicell strategy, analogous to the error catastrophe in standard
quasispecies models. The existence of such a transition indicates that
multicellularity can emerge because natural selection does not act on specific
cells, but rather on replicative strategies. Within this framework, individual
cells become the means by which replicative strategies are propagated. Such a
framework is therefore consistent with the concept that natural selection does
not act on individuals, but rather on populations.


title:
A toolkit for the construction of icosahedral particles with local
  symmetry axes

abstract:
  A formalism is developed which allows to determine the locations of all local
symmetry axes of three-dimensional particles with overall icosahedral symmetry.
It relies on the fact that the root system of the non-crystallographic Coxeter
group H_3 encodes the locations of the planes of reflection that generate the
discrete rotational symmetries of the particles. Via an appropriate extension
of the root system, new planes of reflection are introduced which determine
local axes of rotational symmetry. An easy-to-implement formalism is derived
that allows to compute the surface structure of any three-dimensional
icosahedral particle with local symmetries. It can be used also for particles
with overall octahedral and tetrahedral symmetry in conjunction with the root
systems of the corresponding reflection groups.
  Applications to viruses are discussed explicitly. It is shown that the
concept of quasi-equivalence in Caspar-Klug Theory corresponds to the special
case of local six-fold symmetry axes contained in the theory developed here,
and the corresponding geometries can hence be obtained with this formalism
based on the root system of H_3.
  Moreover, as a by-product, the theory answers the long-standing open question
why only certain types of capsomeres, i.e. clusters of protein subunits, are
observed in the surface structures of viruses. Since the types of the
capsomeres are determined by the orders of the local symmetry axes on which
they are located, the possible types of capsomeres are restricted by the
spectrum of local symmetry axes allowed by the theory. Based on this we
determine the spectrum of all capsomere types that may occur in viral capsids
and give explicit examples for the lower-order cases.


title: Phase transition in a mean-field model for sympatric speciation

abstract:
  We introduce an analytical model for population dynamics with intra-specific
competition, mutation and assortative mating as basic ingredients. The set of
equations that describes the time evolution of population size in a mean-field
approximation may be decoupled. We find a phase transition leading to sympatric
speciation as a parameter that quantifies competition strength is varied. This
transition, previously found in a computational model, occurs to be of first
order.


title: Monte carlo simulations of parapatric speciation

abstract:
  Parapatric speciation is studied using an individual--based model with sexual
reproduction. We combine the theory of mutation accumulation for biological
ageing with an environmental selection pressure that varies according to the
individuals geographical positions and phenotypic traits. Fluctuations and
genetic diversity of large populations are crucial ingredients to model the
features of evolutionary branching and are intrinsic properties of the model.
Its implementation on a spatial lattice gives interesting insights into the
population dynamics of speciation on a geographical landscape and the
disruptive selection that leads to the divergence of phenotypes. Our results
suggest that assortative mating is not an obligatory ingredient to obtain
speciation in large populations at low gene flow.


title: Complex Network Approach to Human Promoter Sequences

abstract:
  Based upon the correlation matrix of the human promoter sequences, a complex
network is constructed to capture the principal relationships between these
promoters. It is a complex network has the properties of the right-skewed
degree distribution and the clustering simultaneously, i.e., a hierarchical
structure. An eigenvector centrality (EC) based method is used to reconstruct
this hierarchical structure.


title: Positioning Crenarchaeal tRNA-Introns

abstract:
  We precisely position a noncanonical intron in the odd second copy of
tRNAAsp(GTC) gene in the newly sequenced crenarchaea S.acidocaldarius. The
uniform assortment of some features from normal aspartate tDNA and some from
those corresponding to non-standard amino acids conduce us to conjecture it to
be a novel tRNA gene, probably coding for a modified aspartate residue. Further
we reposition intron in tRNAHis(GUG) gene in P.aerophilum.The BHB motif at the
exon-intron boundaries are re-analyzed and found to support our conjectures.


title:
Glassy Dynamics in the Adaptive Immune Response Prevents Autoimmune
  Disease

abstract:
  The immune system normally protects the human host against death by
infection. However, when an immune response is mistakenly directed at self
antigens, autoimmune disease can occur. We describe a model of protein
evolution to simulate the dynamics of the adaptive immune response to antigens.
Computer simulations of the dynamics of antibody evolution show that different
evolutionary mechanisms, namely gene segment swapping and point mutation, lead
to different evolved antibody binding affinities. Although a combination of
gene segment swapping and point mutation can yield a greater affinity to a
specific antigen than point mutation alone, the antibodies so evolved are
highly cross-reactive and would cause autoimmune disease, and this is not the
chosen dynamics of the immune system. We suggest that in the immune system a
balance has evolved between binding affinity and specificity in the mechanism
for searching the amino acid sequence space of antibodies.


title:
Connectivity and expression in protein networks: Proteins in a complex
  are uniformly expressed

abstract:
  We explore the interplay between the protein-protein interactions network and
the expression of the interacting proteins. It is shown that interacting
proteins are expressed in significantly more similar cellular concentrations.
This is largely due to interacting pairs which are part of protein complexes.
We solve a generic model of complex formation and show explicitly that
complexes form most efficiently when their members have roughly the same
concentrations. Therefore, the observed similarity in interacting protein
concentrations could be attributed to optimization for efficiency of complex
formation.


title:
Sensitive predators and endurant preys in an ecosystem driven by
  correlated noises

abstract:
  We investigate the Volterra ecosystem driven by correlated noises. The
competition of the predators induces an increasing in population density of the
predators. The competition of the preys, however, leads the predators to decay.
The predators may have better stability under strong correlated noises. The
predators undergo a sensitivity to a random environment, whereas the preys
exhibit a surprising endurance to this stochasticity.


title: Rank Statistics in Biological Evolution

abstract:
  We present a statistical analysis of biological evolution processes.
Specifically, we study the stochastic replication-mutation-death model where
the population of a species may grow or shrink by birth or death, respectively,
and additionally, mutations lead to the creation of new species. We rank the
various species by the chronological order by which they originate. The average
population N_k of the kth species decays algebraically with rank, N_k ~ M^{mu}
k^{-mu}, where M is the average total population. The characteristic exponent
mu=(alpha-gamma)/(alpha+beta-gamma)$ depends on alpha, beta, and gamma, the
replication, mutation, and death rates. Furthermore, the average population P_k
of all descendants of the kth species has a universal algebraic behavior, P_k ~
M/k.

categories: q-bio.PE cond-mat.stat-mech math.PR q-bio.GN


title: Reading Sequences of Interspike Intervals in Biological Neural Circuits

abstract:
  Sensory systems pass information about an animal's environment to higher
nervous system units through sequences of action potentials. When these action
potentials have essentially equivalent waveforms, all information is contained
in the interspike intervals (ISIs) of the spike sequence. We address the
question: How do neural circuits recognize and read these ISI sequences?
  Our answer is given in terms of a biologically inspired neural circuit that
we construct using biologically realistic neurons. The essential ingredients of
the ISI Reading Unit (IRU) are (i) a tunable time delay circuit modelled after
one found in the anterior forebrain pathway of the birdsong system and (ii) a
recently observed rule for inhibitory synaptic plasticity. We present a circuit
that can both learn the ISIs of a training sequence using inhibitory synaptic
plasticity and then recognize the same ISI sequence when it is presented on
subsequent occasions. We investigate the ability of this IRU to learn in the
presence of two kinds of noise: jitter in the time of each spike and random
spikes occurring in the ideal spike sequence. We also discuss how the circuit
can be detuned by removing the selected ISI sequence and replacing it by an ISI
sequence with ISIs drawn from a probability distribution.
  We have investigated realizations of the time delay circuit using
Hodgkin-Huxley conductance based neurons connected by realistic excitatory and
inhibitory synapses. Our models for the time delay circuit are tunable from
about 10 ms to 100 ms allowing one to learn and recognize ISI sequences within
that range of ISIs. ISIs down to a few ms and longer than 100 ms are possible
with other intrinsic and synaptic currents in the component neurons.


title:
Self-optimization, community stability, and fluctuations in two
  individual-based models of biological coevolution

abstract:
  We compare and contrast the long-time dynamical properties of two
individual-based models of biological coevolution. Selection occurs via
multispecies, stochastic population dynamics with reproduction probabilities
that depend nonlinearly on the population densities of all species resident in
the community. New species are introduced through mutation. Both models are
amenable to exact linear stability analysis, and we compare the analytic
results with large-scale kinetic Monte Carlo simulations, obtaining the
population size as a function of an average interspecies interaction strength.
Over time, the models self-optimize through mutation and selection to
approximately maximize a community fitness function, subject only to
constraints internal to the particular model. If the interspecies interactions
are randomly distributed on an interval including positive values, the system
evolves toward self-sustaining, mutualistic communities. In contrast, for the
predator-prey case the matrix of interactions is antisymmetric, and a nonzero
population size must be sustained by an external resource. Time series of the
diversity and population size for both models show approximate 1/f noise and
power-law distributions for the lifetimes of communities and species. For the
mutualistic model, these two lifetime distributions have the same exponent,
while their exponents are different for the predator-prey model. The difference
is probably due to greater resilience toward mass extinctions in the food-web
like communities produced by the predator-prey model.


title: Shock waves in virus fitness evolution

abstract:
  We consider a nonlinear partial differential equation of conservation type to
describe the dynamics of vesicular stomatitis virus observed in aliquots of
fixed particle number taken from an evolving clone at periodic intervals of
time \cite{novella 95}. The changes in time behavior of fitness function
noticed in experimental data are related to a crossover exhibited by the
solutions to this equation in the transient regime for pulse-like initial
conditions. As a consequence, the average replication rate of the population is
predicted to reach a plateau as a power t^{-(1/2)}.


title:
Signal detection, modularity and the correlation between extrinsic and
  intrinsic noise in biochemical networks

abstract:
  Understanding cell function requires an accurate description of how noise is
transmitted through biochemical networks. We present an analytical result for
the power spectrum of the output signal of a biochemical network that takes
into account the correlations between the noise in the input signal (the
extrinsic noise) and the noise in the reactions that constitute the network
(the intrinsic noise). These correlations arise from the fact that the
reactions by which biochemical signals are detected necessarily affect the
signaling molecules and the detection components of the network simultaneously.
We show that anti-correlation between the extrinsic and intrinsic noise
enhances the robustness of zero-order ultrasensitive networks to biochemical
noise. We discuss the consequences of the correlation between extrinsic and
intrinsic noise for a modular description of noise transmission through large
biochemical networks in the context of the mitogen-activated protein kinase
cascade.


title:
Excluded-Volume Effects in Tethered-Particle Experiments: Bead Size
  Matters

abstract:
  The tethered-particle method is a single-molecule technique that has been
used to explore the dynamics of a variety of macromolecules of biological
interest. We give a theoretical analysis of the particle motions in such
experiments. Our analysis reveals that the proximity of the tethered bead to a
nearby surface (the microscope slide) gives rise to a volume-exclusion effect,
resulting in an entropic force on the molecule. This force stretches the
molecule, changing its statistical properties. In particular, the proximity of
bead and surface brings about intriguing scaling relations between key
observables (statistical moments of the bead) and parameters such as the bead
size and contour length of the molecule. We present both approximate analytic
solutions and numerical results for these effects in both flexible and
semiflexible tethers. Finally, our results give a precise,
experimentally-testable prediction for the probability distribution of the
distance between the polymer attachment point and the center of the mobile
bead.


title:
Directed motion emerging from two coupled random processes:
  Translocation of a chain through a membrane nanopore driven by binding
  proteins

abstract:
  We investigate the translocation of a stiff polymer consisting of M monomers
through a nanopore in a membrane, in the presence of binding particles
(chaperones) that bind onto the polymer, and partially prevent backsliding of
the polymer through the pore. The process is characterized by the rates: k for
the polymer to make a diffusive jump through the pore, q for unbinding of a
chaperone, and the rate q kappa for binding (with a binding strength kappa);
except for the case of no binding kappa=0 the presence of the chaperones give
rise to an effective force that drives the translocation process. Based on a
(2+1) variate master equation, we study in detail the coupled dynamics of
diffusive translocation and (partial) rectification by the binding proteins. In
particular, we calculate the mean translocation time as a function of the
various physical parameters.


title: Master equation approach to the assembly of viral capsids

abstract:
  The distribution of inequivalent geometries occurring during self-assembly of
the major capsid protein in thermodynamic equilibrium is determined based on a
master equation approach. These results are implemented to characterize the
assembly of SV40 virus and to obtain information on the putative pathways
controlling the progressive build-up of the SV40 capsid. The experimental
testability of the predictions is assessed and an analysis of the geometries of
the assembly intermediates on the dominant pathways is used to identify targets
for antiviral drug design.


title: Assembly Models for Papovaviridae based on Tiling Theory

abstract:
  A vital constituent of a virus is its protein shell, called the viral capsid,
that encapsulates and hence provides protection for the viral genome. Assembly
models are developed for viral capsids built from protein building blocks that
can assume different local bonding structures in the capsid. This situation
occurs, for example, for viruses in the family of Papovaviridae, which are
linked to cancer and are hence of particular interest for the health sector.
More specifically, the viral capsids of the (pseudo-) T=7 particles in this
family consist of pentamers that exhibit two different types of bonding
structures. While this scenario cannot be described mathematically in terms of
Caspar-Klug Theory (Caspar and Klug 1962), it can be modelled via tiling theory
(Twarock 2004). The latter is used to encode the local bonding environment of
the building blocks in a combinatorial structure, called the assembly tree,
which is a basic ingredient in the derivation of assembly models for
Papovaviridae along the lines of the equilibrium approach of Zlotnick (Zlotnick
1994). A phase space formalism is introduced to characterize the changes in the
assembly pathways and intermediates triggered by the variations in the
association energies characterizing the bonds between the building blocks in
the capsid. Furthermore, the assembly pathways and concentrations of the
statistically dominant assembly intermediates are determined. The example of
Simian Virus 40 is discussed in detail.


title: Self-Sustained Thought Processes in a Dense Associative Network

abstract:
  Several guiding principles for thought processes are proposed and a
neural-network-type model implementing these principles is presented and
studied. We suggest to consider thinking within an associative network built-up
of overlapping memory states. We consider a homogeneous associative network as
biological considerations rule out distinct conjunction units between the
information (the memories) stored in the brain. We therefore propose that
memory states have a dual functionality: They represent on one side the stored
information and serve, on the other side, as the associative links in between
the different dynamical states of the network which consists of transient
attractors.
  We implement these principles within a generalized winners-take-all neural
network with sparse coding and an additional coupling to local reservoirs. We
show that this network is capable to generate autonomously a self-sustained
time-series of memory states which we identify with a thought process. Each
memory state is associatively connected with its predecessor.
  This system shows several emerging features, it is able (a) to recognize
external patterns in a noisy background, (b) to focus attention autonomously
and (c) to represent hierarchical memory states with an internal structure.


title: Spatial Scaling in Model Plant Communities

abstract:
  We present an analytically tractable variant of the voter model that provides
a quantitatively accurate description of beta-diversity (two-point correlation
function) in two tropical forests. The model exhibits novel scaling behavior
that leads to links between ecological measures such as relative species
abundance and the species area relationship.


title: Towards Structure-Property-Function Relationships for Eumelanin

abstract:
  We discuss recent progress towards the establishment of important
structure-property-function relationships in eumelanins - key functional
bio-macromolecular systems responsible for photo-protection and immune response
in humans, and implicated in the development of melanoma skin cancer. We focus
on the link between eumelanin's secondary structure and optical properties such
as broad band UV-visible absorption and strong non-radiative relaxation; both
key features of the photo-protective function. We emphasise the insights gained
through a holistic approach combining optical spectroscopy with first
principles quantum chemical calculations, and advance the hypothesis that the
robust functionality characteristic of eumelanin is related to extreme chemical
and structural disorder at the secondary level. This inherent disorder is a low
cost natural resource, and it is interesting to speculate as to whether it may
play a role in other functional bio-macromolecular systems.


title: Fully Complex Magnetoencephalography

abstract:
  Complex numbers appear naturally in biology whenever a system can be analyzed
in the frequency domain, such as physiological data from magnetoencephalography
(MEG). For example, the MEG steady state response to a modulated auditory
stimulus generates a complex magnetic field for each MEG channel, equal to the
Fourier transform at the stimulus modulation frequency. The complex nature of
these data sets, often not taken advantage of, is fully exploited here with new
methods. Whole-head, complex magnetic data can be used to estimate complex
neural current sources, and standard methods of source estimation naturally
generalize for complex sources. We show that a general complex neural vector
source is described by its location, magnitude, and direction, but also by a
phase and by an additional perpendicular component. We give natural
interpretations of all the parameters for the complex equivalent-current dipole
by linking them to the underlying neurophysiology. We demonstrate complex
magnetic fields, and their equivalent fully complex current sources, with both
simulations and experimental data.