pwc-archive/papers-with-abstracts huggingface dataset:
Numerical treatment of the Filament Based Lamellipodium Model (FBLM)
Date: 2015-05-16 00:00:00

We describe in this work the numerical treatment of the Filament Based
Lamellipodium Model (FBLM). The model itself is a two-phase two-dimensional
continuum model, describing the dynamics of two interacting families of locally
parallel F-actin filaments. It includes, among others, the bending stiffness of
the filaments, adhesion to the substrate, and the cross-links connecting the
two families. The numerical method proposed is a Finite Element Method (FEM)
developed specifically for the needs of these problem. It is comprised of
composite Lagrange-Hermite two dimensional elements defined over two
dimensional space. We present some elements of the FEM and emphasise in the
numerical treatment of the more complex terms. We also present novel numerical
simulations and compare to in-vitro experiments of moving cells.
A mathematical insight in the epithelial-mesenchymal-like transition in cancer cells and its effect in the invasion of the extracellular matrix
Date: 2015-05-16 00:00:00

Current biological knowledge supports the existence of a secondary group of
cancer cells within the body of the tumour that exhibits stem cell-like
properties. These cells are termed Cancer Stem Cells (CSCs}, and as opposed to
the more usual Differentiated Cancer Cells (DCCs), they exhibit higher
motility, they are more resilient to therapy, and are able to metastasize to
secondary locations within the organism and produce new tumours. The origin of
the CSCs is not completely clear; they seem to stem from the DCCs via a
transition process related to the Epithelial-Mesenchymal Transition (EMT) that
can also be found in normal tissue.
  In the current work we model and numerically study the transition between
these two types of cancer cells, and the resulting "ensemble" invasion of the
extracellular matrix. This leads to the derivation and numerical simulation of
two systems: an algebraic-elliptic system for the transition and an
advection-reaction-diffusion system of Keller-Segel taxis type for the
invasion.
The multi-layer network nature of systemic risk and its implications for the costs of financial crises
Date: 2015-05-16 00:00:00

The inability to see and quantify systemic financial risk comes at an immense
social cost. Systemic risk in the financial system arises to a large extent as
a consequence of the interconnectedness of its institutions, which are linked
through networks of different types of financial contracts, such as credit,
derivatives, foreign exchange and securities. The interplay of the various
exposure networks can be represented as layers in a financial multi-layer
network. In this work we quantify the daily contributions to systemic risk from
four layers of the Mexican banking system from 2007-2013. We show that focusing
on a single layer underestimates the total systemic risk by up to 90%. By
assigning systemic risk levels to individual banks we study the systemic risk
profile of the Mexican banking system on all market layers. This profile can be
used to quantify systemic risk on a national level in terms of nation-wide
expected systemic losses. We show that market-based systemic risk indicators
systematically underestimate expected systemic losses. We find that expected
systemic losses are up to a factor four higher now than before the financial
crisis of 2007-2008. We find that systemic risk contributions of individual
transactions can be up to a factor of thousand higher than the corresponding
credit risk, which creates huge risks for the public. We find an intriguing
non-linear effect whereby the sum of systemic risk of all layers underestimates
the total risk. The method presented here is the first objective data driven
quantification of systemic risk on national scales that reveal its true levels.
BACOM2: a Java tool for detecting normal cell contamination of copy number in heterogeneous tumor
Date: 2015-05-16 00:00:00

We develop a cross-platform open-source Java application (BACOM2) with
graphic user interface (GUI), and users also can use a XML file to set the
parameters of algorithm model, file paths and the dataset of paired samples.
BACOM2 implements the new entire pipeline of copy number change analysis for
heterogeneous cancer tissues, including extraction of raw copy number signals
from CEL files of paired samples, attenuation correction, identification of
balanced AB-genotype loci, copy number detection and segmentation, global
baseline calculation and absolute normalization, differentiation of deletion
types, estimation of the normal tissue fraction and correction of normal tissue
contamination. BACOM2 focuses on the common tools for data preparation and
absolute normalization for copy number analysis of heterogeneous cancer
tissues. The software provides an additional choice for scientists who require
a user-friendly, high-speed processing, cross-platform computing environment
for large copy number data analysis.
Limits to the precision of gradient sensing with spatial communication and temporal integration
Date: 2015-05-17 00:00:00

Gradient sensing requires at least two measurements at different points in
space. These measurements must then be communicated to a common location to be
compared, which is unavoidably noisy. While much is known about the limits of
measurement precision by cells, the limits placed by the communication are not
understood. Motivated by recent experiments, we derive the fundamental limits
to the precision of gradient sensing in a multicellular system, accounting for
communication and temporal integration. The gradient is estimated by comparing
a "local" and a "global" molecular reporter of the external concentration,
where the global reporter is exchanged between neighboring cells. Using the
fluctuation-dissipation framework, we find, in contrast to the case when
communication is ignored, that precision saturates with the number of cells
independently of the measurement time duration, since communication establishes
a maximum lengthscale over which sensory information can be reliably conveyed.
Surprisingly, we also find that precision is improved if the local reporter is
exchanged between cells as well, albeit more slowly than the global reporter.
The reason is that while exchange of the local reporter weakens the comparison,
it decreases the measurement noise. We term such a model "regional
excitation--global inhibition" (REGI). Our results demonstrate that fundamental
sensing limits are necessarily sharpened when the need to communicate
information is taken into account.
Coupled Hebbian learning and evolutionary dynamics in a formal model for structural synaptic plasticity
Date: 2015-05-17 00:00:00

Theoretical models of neuronal function consider different mechanisms through
which networks learn, classify and discern inputs. A central focus of these
models is to understand how associations are established amongst neurons, in
order to predict spiking patterns that are compatible with empirical
observations. Although these models have led to major insights and advances,
they still do not account for the astonishing velocity with which the brain
solves certain problems and what lies behind its creativity, amongst others
features. We examine two important components that may crucially aid
comprehensive understanding of said neurodynamical processes. First, we argue
that once presented with a problem, different putative solutions are generated
in parallel by different groups or local neuronal complexes, with the
subsequent stabilization and spread of the best solutions. Using mathematical
models we show that this mechanism accelerates finding the right solutions.
This formalism is analogous to standard replicator-mutator models of evolution
where mutation is analogous to the probability of neuron state switching
(on/off). The second factor that we incorporate is structural synaptic
plasticity, i.e. the making of new and disbanding of old synapses, which we
apply as a dynamical reorganization of synaptic connections. We show that
Hebbian learning alone does not suffice to reach optimal solutions. However,
combining it with parallel evaluation and structural plasticity opens up
possibilities for efficient problem solving. In the resulting networks,
topologies converge to subsets of fully connected components. Imposing costs on
synapses reduces the connectivity, although the number of connected components
remains robust. The average lifetime of synapses is longer for connections that
are established early, and diminishes with synaptic cost.
Evolutionary Fitness in Variable Environments
Date: 2015-05-17 00:00:00
Tasks: Sensitivity

One essential ingredient of evolutionary theory is the concept of fitness as
a measure for a species' success in its living conditions. Here, we quantify
the effect of environmental fluctuations onto fitness by analytical
calculations on a general evolutionary model and by studying corresponding
individual-based microscopic models. We demonstrate that not only larger growth
rates and viabilities, but also reduced sensitivity to environmental
variability substantially increases the fitness. Even for neutral evolution,
variability in the growth rates plays the crucial role of strongly reducing the
expected fixation times. Thereby, environmental fluctuations constitute a
mechanism to account for the effective population sizes inferred from genetic
data that often are much smaller than the census population size.
Remarks on equality of two distributions under some partial orders
Date: 2015-05-18 00:00:00
Tasks: Vocal Bursts Valence Prediction

In this note we establish some appropriate conditions for stochastic equality
of two random variables/vectors which are ordered with respect to convex
ordering or with respect to supermodular ordering. Multivariate extensions of
this result are also considered.
Synaptic sampling: A connection between PSP variability and uncertainty explains neurophysiological observations
Date: 2015-07-12 00:00:00
Tasks: Decision Making

When an action potential is transmitted to a postsynaptic neuron, a small
change in the postsynaptic neuron's membrane potential occurs. These small
changes, known as a postsynaptic potentials (PSPs), are highly variable, and
current models assume that this variability is corrupting noise. In contrast,
we show that this variability could have an important computational role:
representing a synapse's uncertainty about the optimal synaptic weight (i.e.
the best possible setting for the synaptic weight). We show that this link
between uncertainty and variability, that we call synaptic sampling, leads to
more accurate estimates of the uncertainty in task relevant quantities, leading
to more effective decision making. Synaptic sampling makes four predictions,
all of which have some experimental support. First the more variable a synapse
is, the more it should change during LTP protocols. Second, variability should
increase as the presynpatic firing rate falls. Third, PSP variance should be
proportional to PSP mean. Fourth, variability should increase with distance
from the cell soma. We provide support for the first two predictions by
reanalysing existing datasets, and we find preexisting data in support of the
last two predictions.
The efficiency of Anderson-Darling test with limited sample size: an application to Backtesting Counterparty Credit Risk internal model
Date: 2015-05-18 00:00:00

This work presents a theoretical and empirical evaluation of Anderson-Darling
test when the sample size is limited. The test can be applied in order to
backtest the risk factors dynamics in the context of Counterparty Credit Risk
modelling. We show the limits of such test when backtesting the distributions
of an interest rate model over long time horizons and we propose a modified
version of the test that is able to detect more efficiently an underestimation
of the model's volatility. Finally we provide an empirical application.
Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis
Date: 2015-05-18 00:00:00
Tasks: valid

In this article the notion of metabolic turnover is revisited in the light of
recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo
methods we perform an exact uniform sampling of the steady state fluxes in a
genome scale metabolic network of E Coli from which we infer the metabolites
turnover times. However the latter are inferred from net fluxes, and we argue
that this approximation is not valid for enzymes working nearby thermodynamic
equilibrium. We recalculate turnover times from total fluxes by performing an
energy balance analysis of the network and recurring to the fluctuation
theorem. We find in many cases values one of order of magnitude lower, implying
a faster picture of intermediate metabolism.
Quaternionic representation of the genetic code
Date: 2015-12-29 00:00:00

A heuristic diagram of the evolution of the standard genetic code is
presented. It incorporates, in a way that resembles the energy levels of an
atom, the physical notion of broken symmetry and it is consistent with original
ideas by Crick on the origin and evolution of the code as well as with the
chronological order of appearence of the amino acids along the evolution as
inferred from work that mixtures known experimental results with theoretical
speculations. Suggested by the diagram we propose a Hamilton quaternions based
mathematical representation of the code as it stands now-a-days. The central
object in the description is a codon function that assigns to each amino acid
an integer quaternion in such a way that the observed code degeneration is
preserved. We emphasize the advantages of a quaternionic representation of
amino acids taking as an example the folding of proteins. With this aim we
propose an algorithm to go from the quaternions sequence to the protein three
dimensional structure which can be compared with the corresponding experimental
one stored at the Protein Data Bank. In our criterion the mathematical
representation of the genetic code in terms of quaternions merits to be taken
into account because it describes not only most of the known properties of the
genetic code but also opens new perspectives that are mainly derived from the
close relationship between quaternions and rotations.
Untangling the roles of parasites in food webs with generative network models
Date: 2015-05-18 00:00:00

Food webs represent the set of consumer-resource interactions among a set of
species that co-occur in a habitat, but most food web studies have omitted
parasites and their interactions. Recent studies have provided conflicting
evidence on whether including parasites changes food web structure, with some
suggesting that parasitic interactions are structurally distinct from those
among free-living species while others claim the opposite. Here, we describe a
principled method for understanding food web structure that combines an
efficient optimization algorithm from statistical physics called parallel
tempering with a probabilistic generalization of the empirically well-supported
food web niche model. This generative model approach allows us to rigorously
estimate the degree to which interactions that involve parasites are
statistically distinguishable from interactions among free-living species,
whether parasite niches behave similarly to free-living niches, and the degree
to which existing hypotheses about food web structure are naturally recovered.
We apply this method to the well-studied Flensburg Fjord food web and show that
while predation on parasites, concomitant predation of parasites, and parasitic
intraguild trophic interactions are largely indistinguishable from free-living
predation interactions, parasite-host interactions are different. These results
provide a powerful new tool for evaluating the impact of classes of species and
interactions on food web structure to shed new light on the roles of parasites
in food webs
Actuarial Applications and Estimation of Extended~CreditRisk$^+$
Date: 2017-04-30 00:00:00
Tasks: parameter estimation

We introduce an additive stochastic mortality model which allows joint
modelling and forecasting of underlying death causes. Parameter families for
mortality trends can be chosen freely. As model settings become high
dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation.
We then link our proposed model to an extended version of the credit risk model
CreditRisk$^+$. This allows exact risk aggregation via an efficient numerically
stable Panjer recursion algorithm and provides numerous applications in credit,
life insurance and annuity portfolios to derive P\&L distributions.
Furthermore, the model allows exact (without Monte Carlo simulation error)
calculation of risk measures and their sensitivities with respect to model
parameters for P\&L distributions such as value-at-risk and expected shortfall.
Numerous examples, including an application to partial internal models under
Solvency II, using Austrian and Australian data are shown.
A Much better replacement of the Michaelis-Menten equation and its application
Date: 2015-05-14 00:00:00

Michaelis-Menten equation is a basic equation of enzyme kinetics and gives an
acceptable approximation of real chemical reaction processes. Analyzing the
derivation of this equation yields the fact that its good performance of
approximating real reaction processes is due to Michaelis-Menten curve (15).
This curve is derived from Quasi-Steady-State Assumption(QSSA), which has been
proved always true and called Quasi-Steady-State Law by Banghe Li et al [19].
  Here, we found a quartic equation A(S,E)=0 (22), which gives more accurate
approximation of the reaction process in two aspects: during the quasi-steady
state of a reaction, Michaelis-Menten curve approximates the reaction well,
while our quartic equation $A(S,E)=0$ gives better approximation; near the end
of the reaction, our equation approaches the end of the reaction with a tangent
line same to that of the reaction, while Michaelis-Menten curve does not. In
addition, our quartic equation A(S,E)=0 differs to Michaelis-Menten curve less
than the order of $1/S^3$ as S approaches $+\infty$.
  By considering the above merits of A(S,E)=0, we suggest it as a replacement
of Michaelis-Menten curve. Intuitively, this new equation is more complex and
harder to understand. But, just because its complexity, it provides more
information about the rate constants than Michaelis-Menten curve does.
  Finally, we get a better replacement of the Michaelis-Menten equation by
combing A(S,E)=0 and the equation $dP/dt=k_2C(t)$.
Path Similarity Analysis: a Method for Quantifying Macromolecular Pathways
Date: 2015-10-23 00:00:00

Diverse classes of proteins function through large-scale conformational
changes; sophisticated enhanced sampling methods have been proposed to generate
these macromolecular transition paths. As such paths are curves in a
high-dimensional space, they have been difficult to compare quantitatively, a
prerequisite to, for instance, assess the quality of different sampling
algorithms. The Path Similarity Analysis (PSA) approach alleviates these
difficulties by utilizing the full information in 3N-dimensional trajectories
in configuration space. PSA employs the Hausdorff or Fr\'echet path
metrics---adopted from computational geometry---enabling us to quantify path
(dis)similarity, while the new concept of a Hausdorff-pair map permits the
extraction of atomic-scale determinants responsible for path differences.
Combined with clustering techniques, PSA facilitates the comparison of many
paths, including collections of transition ensembles. We use the closed-to-open
transition of the enzyme adenylate kinase (AdK)---a commonly used testbed for
the assessment enhanced sampling algorithms---to examine multiple microsecond
equilibrium molecular dynamics (MD) transitions of AdK in its substrate-free
form alongside transition ensembles from the MD-based dynamic importance
sampling (DIMS-MD) and targeted MD (TMD) methods, and a geometrical targeting
algorithm (FRODA). A Hausdorff pairs analysis of these ensembles revealed, for
instance, that differences in DIMS-MD and FRODA paths were mediated by a set of
conserved salt bridges whose charge-charge interactions are fully modeled in
DIMS-MD but not in FRODA. We also demonstrate how existing trajectory analysis
methods relying on pre-defined collective variables, such as native contacts or
geometric quantities, can be used synergistically with PSA, as well as the
application of PSA to more complex systems such as membrane transporter
proteins.
Dynamics of Order Positions and Related Queues in a Limit Order Book
Date: 2015-10-13 00:00:00
Tasks: Algorithmic Trading

Order positions are key variables in algorithmic trading. This paper studies
the limiting behavior of order positions and related queues in a limit order
book. In addition to the fluid and diffusion limits for the processes,
fluctuations of order positions and related queues around their fluid limits
are analyzed. As a corollary, explicit analytical expressions for various
quantities of interests in a limit order book are derived.
An exact method to compute a $p$-value for the beyond-pairwise correlations among cancer gene mutations
Date: 2015-05-18 00:00:00

The increasing observation of mutual exclusivity correlations among cancer
gene mutations is a key component for identifying driver events or pathways in
cancer genome analysis. Here we report a rigorous statistical method to compute
an exact $p$-value for the beyond-pairwise mutual exclusivity or co-occurrence
relationships among cancer gene mutations by enumerating a null distribution of
overlapping mutations across more than two genes. The validity and the
advantage of our method is explicitly demonstrated in both cancer gene
mutations and simulation data through the comparison to the permutation test.
An evaluation of DNA-damage response and cell-cycle pathways for breast cancer classification
Date: 2015-05-19 00:00:00
Tasks: Cancer Classification, feature selection, Prognosis

Accurate subtyping or classification of breast cancer is important for
ensuring proper treatment of patients and also for understanding the molecular
mechanisms driving this disease. While there have been several gene signatures
proposed in the literature to classify breast tumours, these signatures show
very low overlaps, different classification performance, and not much relevance
to the underlying biology of these tumours. Here we evaluate DNA-damage
response (DDR) and cell cycle pathways, which are critical pathways implicated
in a considerable proportion of breast tumours, for their usefulness and
ability in breast tumour subtyping. We think that subtyping breast tumours
based on these two pathways could lead to vital insights into molecular
mechanisms driving these tumours. Here, we performed a systematic evaluation of
DDR and cell-cycle pathways for subtyping of breast tumours into the five known
intrinsic subtypes. Homologous Recombination (HR) pathway showed the best
performance in subtyping breast tumours, indicating that HR genes are strongly
involved in all breast tumours. Comparisons of pathway based signatures and two
standard gene signatures supported the use of known pathways for breast tumour
subtyping. Further, the evaluation of these standard gene signatures showed
that breast tumour subtyping, prognosis and survival estimation are all closely
related. Finally, we constructed an all-inclusive super-signature by combining
(union of) all genes and performing a stringent feature selection, and found it
to be reasonably accurate and robust in classification as well as prognostic
value. Adopting DDR and cell cycle pathways for breast tumour subtyping
achieved robust and accurate breast tumour subtyping, and constructing a
super-signature which contains feature selected mix of genes from these
molecular pathways as well as clinical aspects is valuable in clinical
practice.