pwc-archive/papers-with-abstracts huggingface dataset:
A role for ATP-dependent chromatin remodeling in the hierarchical cooperativity between noninteracting transcription factors
Date: 2015-09-24 00:00:00
Tasks: Position

Chromatin remodeling machineries are abundant and diverse in eukaryotic
cells. They have been involved in a variety of situations such as histone
exchange and DNA repair, but their importance in gene expression remains
unclear. Although the influence of nucleosome position on the regulation of
gene expression is generally envisioned under the quasi-equilibrium
perspective, it is proposed that given the ATP-dependence of chromatin
remodeling enzymes, certain mechanisms necessitate non-equilibrium treatments.
Examination of the celebrated chromatin remodeling system of the mouse mammary
tumor virus, in which the binding of transcription factors opens the way to
other ones, reveals that breaking equilibrium offers a subtle mode of
transcription factor cooperativity, avoids molecular trapping phenomena and
allows to reconcile previously conflicting experimental data. This mechanism
provides a control lever of promoter responsiveness to transcription factor
combinations, challenging the classical view of the unilateral influence of
pioneer on secondary transcription factors.
Quadratic Hawkes processes for financial prices
Date: 2015-09-25 00:00:00
Tasks: Time Series, Time Series Analysis

We introduce and establish the main properties of QHawkes ("Quadratic"
Hawkes) models. QHawkes models generalize the Hawkes price models introduced in
E. Bacry et al. (2014), by allowing all feedback effects in the jump intensity
that are linear and quadratic in past returns. A non-parametric fit on NYSE
stock data shows that the off-diagonal component of the quadratic kernel indeed
has a structure that standard Hawkes models fail to reproduce. Our model
exhibits two main properties, that we believe are crucial in the modelling and
the understanding of the volatility process: first, the model is time-reversal
asymmetric, similar to financial markets whose time evolution has a preferred
direction. Second, it generates a multiplicative, fat-tailed volatility
process, that we characterize in detail in the case of exponentially decaying
kernels, and which is linked to Pearson diffusions in the continuous limit.
Several other interesting properties of QHawkes processes are discussed, in
particular the fact that they can generate long memory without necessarily be
at the critical point. Finally, we provide numerical simulations of our
calibrated QHawkes model, which is indeed seen to reproduce, with only a small
amount of quadratic non-linearity, the correct magnitude of fat-tails and time
reversal asymmetry seen in empirical time series.
CYP3A Mediated Ketamine Metabolism is Severely Impaired in Liver S9 Fractions from Aging Sprague Dawley Rats
Date: 2016-06-13 00:00:00

Ketamine is widely used in veterinary medicine and in medicine. Ketamine is
metabolized to its active metabolite norketamine principally by liver CYP3A.
Drug metabolism alterations during aging have severe consequences particularly
in anesthesiology and very few studies on older animals were conducted for
ketamine. The objective of the present study is to assess the influence of
aging on CYP3A metabolism of ketamine. Liver S9 fractions from 3, 6, 12 and 18
month old male Sprague Dawley rats were prepared and Michaelis-Menten
parameters were determined for primary metabolic pathways. The derived maximum
enzyme velocity (i.e. Vmax) suggests a rapid saturation of the CYP3A enzyme
active sites in liver S9 fractions of 18-month old rats. Observed Vmax for
Liver S9 fractions from 3, 6 and 12 month old male Sprague Dawley rats were
2.39 (+-0.23), 2.61 (+-0.18), and 2.07 (+-0.07) respectively compared to 0.68
(+-0.02) for Liver S9 fractions from 18 month old male Sprague Dawley rats.
Interestingly, we observed a 6 to 7 fold change in the derived Km when
comparing Liver S9 fractions from 18 month old male Sprague Dawley rats with
Liver S9 fractions from younger rats. Our results suggest that rat CYP3A enzyme
undergoes conformational changes with age particularly in our geriatric group
(e.g. 18 month rats) leading significant decrease in the rate of formation of
norketamine. Moreover, our results strongly suggest a severe impairment of
CYP3A ketamine mediated metabolism.
Dichotomous noise models of gene switches
Date: 2015-09-25 00:00:00

Molecular noise in gene regulatory networks has two intrinsic components, one
part being due to fluctuations caused by the birth and death of protein or mRNA
molecules which are often present in small numbers and the other part arising
from gene state switching, a single molecule event. Stochastic dynamics of gene
regulatory circuits appears to be largely responsible for bifurcations into a
set of multi-attractor states that encode different cell phenotypes. The
interplay of dichotomous single molecule gene noise with the nonlinear
architecture of genetic networks generates rich and complex phenomena. In this
paper we elaborate on an approximate framework that leads to simple hybrid
multi-scale schemes well suited for the quantitative exploration of the steady
state properties of large-scale cellular genetic circuits.Through a path sum
based analysis of trajectory statistics we elucidate the connection of these
hybrid schemes to the underlying master equation and provide a rigorous
justification for using dichotomous noise based models to study genetic
networks. Numerical simulations of circuit models reveal that the contribution
of the genetic noise of single molecule origin to the total noise is
significant for a wide range of kinetic regimes.
Optimal trading strategies - a time series approach
Date: 2016-03-25 00:00:00
Tasks: Portfolio Optimization, Time Series, Time Series Analysis

Motivated by recent advances in the spectral theory of auto-covariance
matrices, we are led to revisit a reformulation of Markowitz' mean-variance
portfolio optimization approach in the time domain. In its simplest incarnation
it applies to a single traded asset and allows to find an optimal trading
strategy which - for a given return - is minimally exposed to market price
fluctuations. The model is initially investigated for a range of synthetic
price processes, taken to be either second order stationary, or to exhibit
second order stationary increments. Attention is paid to consequences of
estimating auto-covariance matrices from small finite samples, and
auto-covariance matrix cleaning strategies to mitigate against these are
investigated. Finally we apply our framework to real world data.
Cortical microtubule nucleation can organise the cytoskeleton of $Drosophila$ oocytes to define the anteroposterior axis
Date: 2015-09-26 00:00:00

Many cells contain non-centrosomal arrays of microtubules (MT), but the
assembly, organisation and function of these arrays are poorly understood. We
present the first theoretical model for the non-centrosomal MT cytoskeleton in
$Drosophila$ oocytes, in which $bicoid$ and $oskar$ mRNAs become localised to
establish the anterior-posterior body axis. Constrained by experimental
measurements, the model shows that a simple gradient of cortical MT nucleation
is sufficient to reproduce the observed MT distribution, cytoplasmic flow
patterns and localisation of $oskar$ and naive $bicoid$ mRNAs. Our simulations
exclude a major role for cytoplasmic flows in localisation and reveal an
organisation of the MT cytoskeleton that is more ordered than previously
thought. Furthermore, modulating cortical MT nucleation induces a bifurcation
in cytoskeletal organisation that accounts for the phenotypes of polarity
mutants. Thus, our three-dimensional model explains many features of the MT
network and highlights the importance of differential cortical MT nucleation
for axis formation.
Unified theory of human genome reveals a constrained spatial chromosomal arrangement in interphase nuclei
Date: 2015-10-19 00:00:00

We investigate a densely packed, non-random arrangement of forty-six
chromosomes (46,XY) in human nuclei. Here, we model systems-level chromosomal
crosstalk by unifying intrinsic parameters (chromosomal length and number of
genes) across all pairs of chromosomes in the genome to derive an extrinsic
parameter called effective gene density. The hierarchical clustering and
underlying degeneracy in the effective gene density space reveal systems-level
constraints for spatial arrangement of clusters of chromosomes that were
previously unknown. Our findings corroborate experimental data on spatial
chromosomal arrangement in human nuclei, from fibroblast and lymphocyte cell
lines, thereby establishing that human genome constrains chromosomal
arrangement. We propose that this unified theory, which requires no additional
experimental input, may be extended to other eukaryotic species with annotated
genomes to infer their constrained self-organized spatial arrangement of
chromosomes.
Performance v. Turnover: A Story by 4,000 Alphas
Date: 2016-03-21 00:00:00

We analyze empirical data for 4,000 real-life trading portfolios (U.S.
equities) with holding periods of about 0.7-19 trading days. We find a simple
scaling C ~ 1/T, where C is cents-per-share, and T is the portfolio turnover.
Thus, the portfolio return R has no statistically significant dependence on the
turnover T. We also find a scaling R ~ V^X, where V is the portfolio
volatility, and the power X is around 0.8-0.85 for holding periods up to 10
days or so. To our knowledge, this is the only publicly available empirical
study on such a large number of real-life trading portfolios/alphas.
Effects of dynamic synapses on noise-delayed response latency of a single neuron
Date: 2015-09-28 00:00:00

Noise-delayed decay (NDD) phenomenon emerges when the first-spike latency of
a periodically forced stochastic neuron exhibits a maximum for a particular
range of noise intensity. Here, we investigate the latency response dynamics of
a single Hodgkin-Huxley neuron that is subject to both a suprathreshold
periodic stimulus and a background activity arriving through dynamic synapses.
We study the first spike latency response as a function of the presynaptic
firing rate f. This constitutes a more realistic scenario than previous works,
since f provides a suitable biophysically realistic parameter to control the
level of activity in actual neural systems. We first report on the emergence of
classical NDD behavior as a function of f for the limit of static synapses.
Secondly, we show that when short-term depression and facilitation mechanisms
are included at synapses, different NDD features can be found due to the their
modulatory effect on synaptic current fluctuations. For example a new
intriguing double NDD (DNDD) behavior occurs for different sets of relevant
synaptic parameters. Moreover, depending on the balance between synaptic
depression and synaptic facilitation, single NDD or DNDD can prevails, in such
a way that synaptic facilitation favors the emergence of DNDD whereas synaptic
depression favors the existence of single NDD. This is the first time it has
been reported the existence of DNDD effect in response latency dynamics of a
neuron.
Correctness of Backtest Engines
Date: 2015-09-28 00:00:00

In recent years several trading platforms appeared which provide a backtest
engine to calculate historic performance of self designed trading strategies on
underlying candle data. The construction of a correct working backtest engine
is, however, a subtle task as shown by Maier-Paape and Platen (cf.
arXiv:1412.5558 [q-fin.TR]). Several platforms are struggling on the
correctness.
  In this work, we discuss the problem how the correctness of backtest engines
can be verified. We provide models for candles and for intra-period prices
which will be applied to conduct a proof of correctness for a given backtest
engine if the here provided tests on specific model candles are successful.
Furthermore, we hint to algorithmic considerations in order to allow for a fast
implementation of these tests necessary for the proof of correctness.
Technical Report: Modelling Multiple Cell Types with Partial Differential Equations
Date: 2015-09-28 00:00:00

Partial differential equations are a convenient way to describe reaction-
advection-diffusion processes of signalling models. If only one cell type is
present, and tissue dynamics can be neglected, the equations can be solved
directly. However, in case of multiple cell types it is not always straight
forward to integrate a continuous description of the tissue dynamics. Here, we
discuss (delayed) differentiation of cells into different cell types and
hypertrophic cell volume change upon differentiation.
Control of complex networks requires both structure and dynamics
Date: 2016-04-18 00:00:00

The study of network structure has uncovered signatures of the organization
of complex systems. However, there is also a need to understand how to control
them; for example, identifying strategies to revert a diseased cell to a
healthy state, or a mature cell to a pluripotent state. Two recent
methodologies suggest that the controllability of complex systems can be
predicted solely from the graph of interactions between variables, without
considering their dynamics: structural controllability and minimum dominating
sets. We demonstrate that such structure-only methods fail to characterize
controllability when dynamics are introduced. We study Boolean network
ensembles of network motifs as well as three models of biochemical regulation:
the segment polarity network in Drosophila melanogaster, the cell cycle of
budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in
Arabidopsis thaliana. We demonstrate that structure-only methods both
undershoot and overshoot the number and which sets of critical variables best
control the dynamics of these models, highlighting the importance of the actual
system dynamics in determining control. Our analysis further shows that the
logic of automata transition functions, namely how canalizing they are, plays
an important role in the extent to which structure predicts dynamics.
Volume Weighted Average Price Optimal Execution
Date: 2015-09-28 00:00:00

We study the problem of optimal execution of a trading order under Volume
Weighted Average Price (VWAP) benchmark, from the point of view of a
risk-averse broker. The problem consists in minimizing mean-variance of the
slippage, with quadratic transaction costs. We devise multiple ways to solve
it, in particular we study how to incorporate the information coming from the
market during the schedule. Most related works in the literature eschew the
issue of imperfect knowledge of the total market volume. We instead incorporate
it in our model. We validate our method with extensive simulation of order
execution on real NYSE market data. Our proposed solution, using a simple model
for market volumes, reduces by 10% the VWAP deviation RMSE of the standard
"static" solution (and can simultaneously reduce transaction costs).
Vector-borne diseases models with residence times - a Lagrangian perspective
Date: 2017-03-14 00:00:00

A multi-patch and multi-group modeling framework describing the dynamics of a
class of diseases driven by the interactions between vectors and hosts
structured by groups is formulated. Hosts' dispersal is modeled in terms of
patch-residence times with the nonlinear dynamics taking into account the
\textit{effective} patch-host size. The residence times basic reproduction
number $\mathcal R_0$ is computed and shown to depend on the relative
environmental risk of infection. The model is robust, that is, the disease free
equilibrium is globally asymptotically stable (GAS) if $\mathcal R_0\leq1$ and
a unique interior endemic equilibrium is shown to exist that is GAS whenever
$\mathcal R_0>1$ whenever the configuration of host-vector interactions is
irreducible. The effects of \textit{patchiness} and \textit{groupness}, a
measure of host-vector heterogeneous structure, on the basic reproduction
number $\mathcal R_0$, are explored. Numerical simulations are carried out to
highlight the effects of residence times on disease prevalence.
Griffiths phase and long-range correlations in a biologically motivated V1 model
Date: 2016-11-18 00:00:00

Activity in the brain propagates as waves of firing neurons, namely
avalanches. These waves' size and duration distributions have been
experimentally shown to display a stable power-law profile, long-range
correlations and $1/f^{b}$ power spectrum \textit{in vivo} and \textit{in
vitro}. We study an avalanching biologically motivated model of mammals visual
cortex and find an extended critical-like region -- a Griffiths phase --
characterized by divergent susceptibility and zero order parameter. This phase
lies close to the expected experimental value of the \textit{excitatory
postsynaptic potential} in the cortex suggesting that critical behavior may be
found in the visual system. Avalanches are not perfectly power-law distributed,
but it is possible to collapse the distributions and define a cutoff avalanche
size that diverges as the network size is increased inside the critical region.
The avalanches present long-range correlations and $1/f^{b}$ power spectrum,
matching experiments. The phase transition is analytically determined by a
mean-field approximation.
Distribution approximations for the chemical master equation: comparison of the method of moments and the system size expansion
Date: 2015-09-30 00:00:00

The stochastic nature of chemical reactions involving randomly fluctuating
population sizes has lead to a growing research interest in discrete-state
stochastic models and their analysis. A widely-used approach is the description
of the temporal evolution of the system in terms of a chemical master equation
(CME). In this paper we study two approaches for approximating the underlying
probability distributions of the CME. The first approach is based on an
integration of the statistical moments and the reconstruction of the
distribution based on the maximum entropy principle. The second approach relies
on an analytical approximation of the probability distribution of the CME using
the system size expansion, considering higher-order terms than the linear noise
approximation. We consider gene expression networks with unimodal and
multimodal protein distributions to compare the accuracy of the two approaches.
We find that both methods provide accurate approximations to the distributions
of the CME while having different benefits and limitations in applications.
Dynamics of multivariate default system in random environment
Date: 2016-11-18 00:00:00

We consider a multivariate default system where random environmental
information is available. We study the dynamics of the system in a general
setting and adopt the point of view of change of probability measures. We also
make a link with the density approach in the credit risk modelling. In the
particular case where no environmental information is concerned, we pay a
special attention to the phenomenon of system weakened by failures as in the
classical reliability system.
Stochastic Analysis Of An Incoherent Feedforward Genetic Motif
Date: 2015-09-30 00:00:00

Gene products (RNAs, proteins) often occur at low molecular counts inside
individual cells, and hence are subject to considerable random fluctuations
(noise) in copy number over time. Not surprisingly, cells encode diverse
regulatory mechanisms to buffer noise. One such mechanism is the incoherent
feedforward circuit. We analyze a simplistic version of this circuit, where an
upstream regulator X affects both the production and degradation of a protein
Y. Thus, any random increase in X's copy numbers would increase both production
and degradation, keeping Y levels unchanged. To study its stochastic dynamics,
we formulate this network into a mathematical model using the Chemical Master
Equation formulation. We prove that if the functional dependence of Y's
production and degradation on X is similar, then the steady-distribution of Y's
copy numbers is independent of X. To investigate how fluctuations in Y
propagate downstream, a protein Z whose production rate only depend on Y is
introduced. Intriguingly, results show that the extent of noise in Z increases
with noise in X, in spite of the fact that the magnitude of noise in Y is
invariant of X. Such counter intuitive results arise because X enhances the
time-scale of fluctuations in Y, which amplifies fluctuations in downstream
processes. In summary, while feedforward systems can buffer a protein from
noise in its upstream regulators, noise can propagate downstream due to changes
in the time-scale of fluctuations.
Retarded action principle and self-financing portfolio dynamics
Date: 2016-06-21 00:00:00

We derive a consistent differential representation for the dynamics of a
self-financing portfolio for different hedging strategies. In the basis of the
derivation there is the so called "retarded action principle", which represents
the causality in the evolution of dependent stochastic variables. We
demonstrate this principle on example of a vanilla and a storage option.
A homotopic mapping between current-based and conductance-based synapses in a mesoscopic neural model of epilepsy
Date: 2018-12-16 00:00:00

Changes in brain states, as found in many neurological diseases such as
epilepsy, are often described as bifurcations in mesoscopic neural models.
Nearly all of these models rely on a mathematically convenient, but
biophysically inaccurate, description of the synaptic input to neurons called
current-based synapses. We develop a novel analytical framework to analyze the
effects of a more biophysically realistic description, known as
conductance-based synapses. These are implemented in a mesoscopic neural model
and compared to the standard approximation via a single parameter homotopic
mapping. A bifurcation analysis using the homotopy parameter demonstrates that
if a more realistic synaptic coupling mechanism is used in this class of
models, then a bifurcation or transition to an abnormal brain state does not
occur in the same parameter space. We show that the more realistic coupling has
additional mathematical parameters that require a fundamentally different
biophysical mechanism to undergo a state transition. These results demonstrate
the importance of incorporating more realistic synapses in mesoscopic neural
models and challenge the accuracy of previous models, especially those
describing brain state transitions such as epilepsy.
Demographic Transition Theory Contradicted Repeatedly by Data
Date: 2016-01-20 00:00:00

In the absence of convincing evidence, data for Sweden and Mauritius are used
in academic publications to illustrate the Demographic Transition Theory. These
data are closely examined and found to be in clear contradiction of this
theory. Demographic Transition Theory is also contradicted by the best
available data for England. Other examples of contradicting evidence are also
discussed.
Influenza Evolution and H3N2 Vaccine Effectiveness, with Application to the 2014/2015 Season
Date: 2016-03-18 00:00:00

Influenza A is a serious disease that causes significant morbidity and
mortality, and vaccines against the seasonal influenza disease are of variable
effectiveness. In this paper, we discuss use of the $p_{\rm epitope}$ method to
predict the dominant influenza strain and the expected vaccine effectiveness in
the coming flu season. We illustrate how the effectiveness of the 2014/2015
A/Texas/50/2012 [clade 3C.1] vaccine against the A/California/02/2014 [clade
3C.3a] strain that emerged in the population can be estimated via pepitope. In
addition, we show by a multidimensional scaling analysis of data collected
through 2014, the emergence of a new A/New Mexico/11/2014-like cluster [clade
3C.2a] that is immunologically distinct from the A/California/02/2014-like
strains.