pwc-archive/papers-with-abstracts huggingface dataset:
Bloch spin waves and emergent structure in protein folding with HIV envelope glycoprotein as an example
Date: 2015-11-23 00:00:00
Tasks: Protein Folding

We inquire how structure emerges during the process of protein folding. For
this we scrutinise col- lective many-atom motions during all-atom molecular
dynamics simulations. We introduce, develop and employ various topological
techniques, in combination with analytic tools that we deduce from the concept
of integrable models and structure of discrete nonlinear Schroedinger equation.
The example we consider is an alpha-helical subunit of the HIV envelope
glycoprotein gp41. The helical structure is stable when the subunit is part of
the biological oligomer. But in isolation the helix becomes unstable, and the
monomer starts deforming. We follow the process computationally. We interpret
the evolving structure both in terms of a backbone based Heisenberg spin chain
and in terms of a side chain based XY spin chain. We find that in both cases
the formation of protein super-secondary structure is akin the formation of a
topological Bloch domain wall along a spin chain. During the process we
identify three individual Bloch walls and we show that each of them can be
modelled with a very high precision in terms of a soliton solution to a
discrete nonlinear Schroedinger equation.
Optimal Trading with Linear and (small) Non-Linear Costs
Date: 2016-11-14 00:00:00

We reconsider the problem of optimal trading in the presence of linear and
quadratic costs, for arbitrary linear costs but in the limit where quadratic
costs are small. Using matched asymptotic expansion techniques, we find that
the trading speed vanishes inside a band that is narrower than in the absence
of quadratic costs, by an amount that scales as the one-third power of
quadratic costs. Outside of the band, we find three regimes: a small boundary
layer where the velocity vanishes linearly with the distance to the band, an
intermediate region where the velocity behaves as a square-root of that
distance, and a far region where it becomes linear. Our solution is consistent
with available numerical results. We determine the conditions in which our
expansion is useful in practical applications, and generalize our solution to
other forms of non-linear costs.
Sustainability in the Stochastic Ramsey Model
Date: 2015-11-23 00:00:00
Tasks: model

In this paper we provide a self-contained exposition of the problem of
sustaining a constant consumption level in a Ramsey model. Our focus is on the
case in which the output capital-ratio is random. After a brief review of the
known results on the probabilities of sustaining a target consumption from an
initial stock, we present some new results on estimating the probabilities by
using Chebyshev inequalities. Some numerical calculations for these estimates
are also provided.
Tradeoffs for nearest neighbors on the sphere
Authors: Laarhoven Thijs
Date: 2016-09-10 00:00:00

We consider tradeoffs between the query and update complexities for the
(approximate) nearest neighbor problem on the sphere, extending the recent
spherical filters to sparse regimes and generalizing the scheme and analysis to
account for different tradeoffs. In a nutshell, for the sparse regime the
tradeoff between the query complexity $n^{\rho_q}$ and update complexity
$n^{\rho_u}$ for data sets of size $n$ is given by the following equation in
terms of the approximation factor $c$ and the exponents $\rho_q$ and $\rho_u$:
$$c^2\sqrt{\rho_q}+(c^2-1)\sqrt{\rho_u}=\sqrt{2c^2-1}.$$
  For small $c=1+\epsilon$, minimizing the time for updates leads to a linear
space complexity at the cost of a query time complexity $n^{1-4\epsilon^2}$.
Balancing the query and update costs leads to optimal complexities
$n^{1/(2c^2-1)}$, matching bounds from [Andoni-Razenshteyn, 2015] and [Dubiner,
IEEE-TIT'10] and matching the asymptotic complexities of [Andoni-Razenshteyn,
STOC'15] and [Andoni-Indyk-Laarhoven-Razenshteyn-Schmidt, NIPS'15]. A
subpolynomial query time complexity $n^{o(1)}$ can be achieved at the cost of a
space complexity of the order $n^{1/(4\epsilon^2)}$, matching the bound
$n^{\Omega(1/\epsilon^2)}$ of [Andoni-Indyk-Patrascu, FOCS'06] and
[Panigrahy-Talwar-Wieder, FOCS'10] and improving upon results of
[Indyk-Motwani, STOC'98] and [Kushilevitz-Ostrovsky-Rabani, STOC'98].
  For large $c$, minimizing the update complexity results in a query complexity
of $n^{2/c^2+O(1/c^4)}$, improving upon the related exponent for large $c$ of
[Kapralov, PODS'15] by a factor $2$, and matching the bound $n^{\Omega(1/c^2)}$
of [Panigrahy-Talwar-Wieder, FOCS'08]. Balancing the costs leads to optimal
complexities $n^{1/(2c^2-1)}$, while a minimum query time complexity can be
achieved with update complexity $n^{2/c^2+O(1/c^4)}$, improving upon the
previous best exponents of Kapralov by a factor $2$.
Homophily and missing links in citation networks
Authors: Ciotti Valerio, Bonaventura Moreno, Nicosia Vincenzo, Panzarasa Pietro, Latora Vito
Date: 2015-11-24 00:00:00
Tasks: Articles, Transfer Learning

Citation networks have been widely used to study the evolution of science
through the lenses of the underlying patterns of knowledge flows among academic
papers, authors, research sub-fields, and scientific journals. Here we focus on
citation networks to cast light on the salience of homophily, namely the
principle that similarity breeds connection, for knowledge transfer between
papers. To this end, we assess the degree to which citations tend to occur
between papers that are concerned with seemingly related topics or research
problems. Drawing on a large data set of articles published in the journals of
the American Physical Society between 1893 and 2009, we propose a novel method
for measuring the similarity between articles through the statistical
validation of the overlap between their bibliographies. Results suggest that
the probability of a citation made by one article to another is indeed an
increasing function of the similarity between the two articles. Our study also
enables us to uncover missing citations between pairs of highly related
articles, and may thus help identify barriers to effective knowledge flows. By
quantifying the proportion of missing citations, we conduct a comparative
assessment of distinct journals and research sub-fields in terms of their
ability to facilitate or impede the dissemination of knowledge. Findings
indicate that knowledge transfer seems to be more effectively facilitated by
journals of wide visibility, such as Physical Review Letters, than by
lower-impact ones. Our study has important implications for authors, editors
and reviewers of scientific journals, as well as public preprint repositories,
as it provides a procedure for recommending relevant yet missing references and
properly integrating bibliographies of papers.
Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations
Date: 2015-11-24 00:00:00
Tasks: Dimensionality Reduction

Adhesion processes of biological membranes that enclose cells and cellular
organelles are essential for immune responses, tissue formation, and signaling.
These processes depend sensitively on the binding constant K2D of the
membrane-anchored receptor and ligand proteins that mediate adhesion, which is
difficult to measure in the 'two-dimensional' (2D) membrane environment of the
proteins. An important problem therefore is to relate K2D} to the binding
constant K3D} of soluble variants of the receptors and ligands that lack the
membrane anchors and are free to diffuse in three dimensions (3D). In this
article, we present a general theory for the binding constants K2D and K3D of
rather stiff proteins whose main degrees of freedom are translation and
rotation, along membranes and around anchor points 'in 2D', or unconstrained
'in 3D'. The theory generalizes previous results by describing how K2D depends
both on the average separation and thermal nanoscale roughness of the apposing
membranes, and on the length and anchoring flexibility of the receptors and
ligands. Our theoretical results for the ratio K2D/K3D of the binding constants
agree with detailed results from Monte Carlo simulations without any data
fitting, which indicates that the theory captures the essential features of the
'dimensionality reduction' due to membrane anchoring. In our Monte Carlo
simulations, we consider a novel coarse-grained model of biomembrane adhesion
in which the membranes are represented as discretized elastic surfaces, and the
receptors and ligands as anchored molecules that diffuse continuously along the
membranes and rotate at their anchor points.
Binding kinetics of membrane-anchored receptors and ligands: molecular dynamics simulations and theory
Date: 2015-11-24 00:00:00

The adhesion of biological membranes is mediated by the binding of
membrane-anchored receptor and ligand proteins. Central questions are how the
binding kinetics of these proteins is affected by the membranes and by the
membrane anchoring of the proteins. In this article, we (i) present detailed
data for the binding of membrane-anchored proteins from coarse-grained
molecular dynamics simulations, and (ii) provide a theory that describes how
the binding kinetics depends on the average separation and thermal roughness of
the adhering membranes, and on the anchoring, lengths, and length variations of
the proteins. An important element of our theory is the tilt of bound
receptor-ligand complexes and transition-state complexes relative to the
membrane normals. This tilt results from an interplay of the anchoring energy
and rotational entropy of the complexes and facilitates the formation of
receptor-ligand bonds at membrane separations smaller than the preferred
separation for binding. In our simulations, we have considered both
lipid-anchored and transmembrane receptor and ligand proteins. We find that the
binding equilibrium constant and binding on-rate constant of lipid-anchored
proteins are considerably smaller than the binding constant and on-rate
constant of rigid transmembrane proteins with identical binding domains.
Beat regulation in twisted axonemes
Date: 2015-11-24 00:00:00
Tasks: Open-Ended Question Answering

Cilia and flagella are hairlike organelles that propel cells through fluid.
The active motion of the axoneme, the motile structure inside cilia and
flagella, is powered by molecular motors of the dynein family. These motors
generate forces and torques that slide and bend the microtubule doublets within
the axoneme. To create regular waveforms the activities of the dyneins must be
coordinated. It is thought that coordination is mediated by stresses due to
radial, transverse, or sliding deformations, that build up within the moving
axoneme. However, which particular component of the stress regulates the motors
to produce the observed flagellar waveforms remains an open question. To
address this question, we describe the axoneme as a three-dimensional bundle of
filaments and characterize its mechanics. We show that regulation of the motors
by radial and transverse stresses can lead to a coordinated flagellar motion
only in the presence of twist. By comparison, regulation by shear stress is
possible without twist. We calculate emergent beating patterns in twisted
axonemes resulting from regulation by transverse stresses. The waveforms are
similar to those observed in flagella of Chlamydomonas and sperm. Due to the
twist, the waveform has non-planar components, which result in swimming
trajectories such as twisted ribbons and helices that agree with observations.
Spatial social dilemmas: dilution, mobility and grouping effects with imitation dynamics
Date: 2015-11-24 00:00:00

We present an extensive, systematic study of the Prisoner's Dilemma and
Snowdrift games on a square lattice under a synchronous, noiseless imitation
dynamics. We show that for both the occupancy of the network and the (random)
mobility of the agents there are intermediate values that may increase the
amount of cooperators in the system and new phases appear. We analytically
determine the transition lines between these phases and compare with the mean
field prediction and the observed behavior on a square lattice. We point out
which are the more relevant microscopic processes that entitle cooperators to
invade a population of defectors in the presence of mobility and discuss the
universality of these results.
Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets
Date: 2015-11-24 00:00:00
Tasks: Decision Making

The protein-protein interaction (PPI) network is crucial for cellular
information processing and decision-making. With suitable inputs, PPI networks
drive the cells to diverse functional outcomes such as cell proliferation or
cell death. Here we characterize the structural controllability of a large
directed human PPI network comprised of 6,339 proteins and 34,813 interactions.
This allows us to classify proteins as "indispensable", "neutral" or
"dispensable", which correlates to increasing, no effect, or decreasing the
number of driver nodes in the network upon removal of that protein. We find
that 21% of the proteins in the PPI network are indispensable. Interestingly,
these indispensable proteins are the primary targets of disease-causing
mutations, human viruses, and drugs, suggesting that altering a network's
control property is critical for the transition between healthy and disease
states. Furthermore, analyzing copy number alterations data from 1,547 cancer
patients reveals that 56 genes that are frequently amplified or deleted in nine
different cancers are indispensable. Among the 56 genes, 46 of them have not
been previously associated with cancer. This suggests that controllability
analysis is very useful in identifying novel disease genes and potential drug
targets.
The behavior of dealers and clients on the European corporate bond market: the case of Multi-Dealer-to-Client platforms
Date: 2017-03-22 00:00:00

For the last two decades, most financial markets have undergone an evolution
toward electronification. The market for corporate bonds is one of the last
major financial markets to follow this unavoidable path. Traditionally
quote-driven i.e., dealer-driven) rather than order-driven, the market for
corporate bonds is still mainly dominated by voice trading, but a lot of
electronic platforms have emerged. These electronic platforms make it possible
for buy-side agents to simultaneously request several dealers for quotes, or
even directly trade with other buy-siders. The research presented in this
article is based on a large proprietary database of requests for quotes (RFQ)
sent, through the multi-dealer-to-client (MD2C) platform operated by Bloomberg
Fixed Income Trading, to one of the major liquidity providers in European
corporate bonds. Our goal is (i) to model the RFQ process on these platforms
and the resulting competition between dealers, and (ii) to use our model in
order to implicit from the RFQ database the behavior of both dealers and
clients on MD2C platforms.
Towards life-long learning of posture control for s-EMG prostheses
Date: 2015-11-20 00:00:00
Tasks: valid

Surface electromyography (s-EMG) sensors are a promising way to control
upper-limb prostheses. However a training session is necessary in order to set
up the controller that will make s-EMG based movement possible. All data
recorded during the training session are used by a machine learning algorithm
to make a posture classification, that will allow the controller to distinguish
each posture. The aim of this study is to investigate if it's possible to make
a posture classification which can remain valid over time. The next step will
be the study of how it varies depending on the amount of information submitted
to it during the training session in view of real life everyday use of the
upper-limb prosthesis.
An Application of Correlation Clustering to Portfolio Diversification
Date: 2015-11-25 00:00:00
Tasks: Clustering

This paper presents a novel application of a clustering algorithm developed
for constructing a phylogenetic network to the correlation matrix for 126
stocks listed on the Shanghai A Stock Market. We show that by visualizing the
correlation matrix using a Neighbor-Net network and using the circular ordering
produced during the construction of the network we can reduce the risk of a
diversified portfolio compared with random or industry group based selection
methods in times of market increase.
Information-theoretic neuro-correlates boost evolution of cognitive systems
Date: 2015-11-25 00:00:00

Genetic Algorithms (GA) are a powerful set of tools for search and
optimization that mimic the process of natural selection, and have been used
successfully in a wide variety of problems, including evolving neural networks
to solve cognitive tasks. Despite their success, GAs sometimes fail to locate
the highest peaks of the fitness landscape, in particular if the landscape is
rugged and contains multiple peaks. Reaching distant and higher peaks is
difficult because valleys need to be crossed, in a process that (at least
temporarily) runs against the fitness maximization objective. Here we propose
and test a number of information-theoretic (as well as network-based) measures
that can be used in conjunction with a fitness maximization objective
(so-called ``neuro-correlates") to evolve neural controllers for two widely
different tasks: a behavioral task that requires information integration, and a
cognitive task that requires memory and logic. We find that judiciously chosen
neuro-correlates can significantly aid GAs to find the highest peaks.
Importance of method validation: Implications of non-correlated observables in sweet taste receptor studies
Date: 2015-11-25 00:00:00

Validation of research methodology is critical in research design.
Correlation between experimental observables must be established before
undertaking extensive experiments or propose mechanisms. This article shows
that, observables in the popular calcium flux strength assay used in the
characterization of sweetener-sweet taste receptor (STR) interaction are
uncorrelated. In pursuit to find potential sweeteners and enhancers, calcium
flux generated via G-protein coupling for wildtype and mutant receptors
expressed on cell surface is measured to identify and localize sweetener
binding sites. Results are channeled for sweetener development with direct
impact on public health.
  We show that flux strength is independent of EC50 and sweet potency. Sweet
potency-EC50 relation is non-linear and anti-correlated. Single point mutants
affecting receptor efficiency, without significant shift in EC50 have been
published, indicating flux strength is independent of ligand binding. G-protein
coupling step is likely observed in the assay. Thus, years have been spent
generating uncorrelated data. Data from uncorrelated observables does not give
meaningful results. Still, majority of research in the field, uses change in
calcium flux strength to study the receptor. Methodology away from flux
strength monitor is required for sweetener development, reestablish binding
localization of sweeteners established by flux strength method. This article
serves to remind researchers to validate methodology before plunging into long
term projects. Ignoring validation test on methodology, have been a costly
mistake in the field. Concepts discussed here is applicable, whenever
observable in biological systems are many steps moved from the event of
interest.
One-Dimensional Structural Properties of Proteins in the Coarse-Grained CABS Model
Date: 2016-10-29 00:00:00

Despite the significant increase in computational power, molecular modeling
of protein structure using classical all-atom approaches remains inefficient,
at least for most of the protein targets in the focus of biomedical research.
Perhaps the most successful strategy to overcome the inefficiency problem is
multiscale modeling to merge all-atom and coarse-grained models. This chapter
describes a well-established CABS coarse-grained protein model. The CABS
(C-Alpha, C-Beta and Side chains) model assumes a 2-4 united-atom
representation of amino acids, knowledge-based force field (derived from the
statistical regularities seen in known protein sequences and structures) and
efficient Monte Carlo sampling schemes (MC dynamics, MC replica-exchange, and
combinations). A particular emphasis is given to the unique design of the CABS
force-field, which is largely defined using one-dimensional structural
properties of proteins, including protein secondary structure. This chapter
also presents CABS-based modeling methods, including multiscale tools for de
novo structure prediction, modeling of protein dynamics and prediction of
protein-peptide complexes. CABS-based tools are freely available at
http://biocomp.chem.uw.edu.pl/tools
Adaptability of non-genetic diversity in bacterial chemotaxis
Date: 2015-11-25 00:00:00
Tasks: Diversity

Bacterial chemotaxis systems are as diverse as the environments that bacteria
inhabit, but how much environmental variation can cells tolerate with a single
system? Diversification of a single chemotaxis system could serve as an
alternative, or even evolutionary stepping-stone, to switching between multiple
systems. We hypothesized that mutations in gene regulation could lead to
heritable control of chemotactic diversity. By simulating foraging and
colonization of E. coli using a single-cell chemotaxis model, we found that
different environments selected for different behaviors. The resulting
trade-offs show that populations facing diverse environments would ideally
diversify behaviors when time for navigation is limited. We show that
advantageous diversity can arise from changes in the distribution of protein
levels among individuals, which could occur through mutations in gene
regulation. We propose experiments to test our prediction that chemotactic
diversity in a clonal population could be a selectable trait that enables
adaptation to environmental variability.
Commet: comparing and combining multiple metagenomic datasets
Date: 2015-11-26 00:00:00
Tasks: Diversity

Metagenomics offers a way to analyze biotopes at the genomic level and to
reach functional and taxonomical conclusions. The bio-analyzes of large
metagenomic projects face critical limitations: complex metagenomes cannot be
assembled and the taxonomical or functional annotations are much smaller than
the real biological diversity. This motivated the development of de novo
metagenomic read comparison approaches to extract information contained in
metagenomic datasets.
  However, these new approaches do not scale up large metagenomic projects, or
generate an important number of large intermediate and result files. We
introduce Commet ("COmpare Multiple METagenomes"), a method that provides
similarity overview between all datasets of large metagenomic projects.
  Directly from non-assembled reads, all against all comparisons are performed
through an efficient indexing strategy. Then, results are stored as bit
vectors, a compressed representation of read files, that can be used to further
combine read subsets by common logical operations. Finally, Commet computes a
clusterization of metagenomic datasets, which is visualized by dendrogram and
heatmaps.
  Availability: http://github.com/pierrepeterlongo/commet
On the Existence of Martingale Measures in Jump Diffusion Market Models
Date: 2015-11-26 00:00:00

In the context of jump-diffusion market models we construct examples that
satisfy the weaker no-arbitrage condition of NA1 (NUPBR), but not NFLVR. We
show that in these examples the only candidate for the density process of an
equivalent local martingale measure is a supermartingale that is not a
martingale, not even a local martingale. This candidate is given by the
supermartingale deflator resulting from the inverse of the discounted growth
optimal portfolio. In particular, we con- sider an example with constraints on
the portfolio that go beyond the standard ones for admissibility.