pwc-archive/papers-with-abstracts huggingface dataset:
Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs
Date: 2016-10-31 00:00:00
Tasks: Functional Connectivity

The large-scale structural ingredients of the brain and neural connectomes
have been identified in recent years. These are, similar to the features found
in many other real networks: the arrangement of brain regions into modules and
the presence of highly connected regions (hubs) forming rich-clubs. Here, we
examine how modules and hubs shape the collective dynamics on networks and we
find that both ingredients lead to the emergence of complex dynamics. Comparing
the connectomes of C. elegans, cats, macaques and humans to surrogate networks
in which either modules or hubs are destroyed, we find that functional
complexity always decreases in the perturbed networks. A comparison between
simulated and empirically obtained resting-state functional connectivity
indicates that the human brain, at rest, lies in a dynamical state that
reflects the largest complexity its anatomical connectome can host. Last, we
generalise the topology of neural connectomes into a new hierarchical network
model that successfully combines modular organisation with rich-club forming
hubs. This is achieved by centralising the cross-modular connections through a
preferential attachment rule. Our network model hosts more complex dynamics
than other hierarchical models widely used as benchmarks.
The Invisible Hand of Laplace: the Role of Market Structure in Price Convergence and Oscillation
Date: 2016-02-24 00:00:00

A fundamental question about a market is under what conditions, and then how
rapidly, does price signaling cause price equilibration. Qualitatively, this
ought to depend on how well-connected the market is. We address this question
quantitatively for a certain class of Arrow-Debreu markets with continuous-time
proportional t\^{a}tonnement dynamics. We show that the algebraic connectivity
of the market determines the effectiveness of price signaling equilibration.
This also lets us study the rate of external noise that a market can tolerate
and still maintain near-equilibrium prices.
Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function
Date: 2016-02-27 00:00:00

The hominid-specific non-LTR retrotransposon termed SINE VNTR Alu (SVA) is
the youngest of the transposable elements in the human genome. The propagation
of the most ancient SVA type A took place about thirteen millions years ago
ago, and the youngest SVA types appeared in the human genome after the
chimpanzee divergence. Functional enrichment analysis of genes associated with
SVA insertions demonstrated their strong link to multiple ontological
categories attributed to brain function and the disorders. SVA types that
expanded their presence in the human genome at different stages of hominoid
life history were also associated with progressively evolving behavioural
features that indicated a potential impact of SVA propagation on a cognitive
ability of a modern human. The SVA-associated genes were highly cross-linked in
functional networks suggesting an accumulative impact of functional alterations
potentially caused by SVA insertions. Our analysis uncovered a potential role
of SVAs in evolution of human CNS and especially emergence of functional trends
relevant to social and parental behaviour. It also supports models which
explain in part how brain function can be modulated by both the immune and
reproductive systems based on the gene expression patterns and gene pathways
potentially altered by SVA insertions.
The role of volume in order book dynamics: a multivariate Hawkes process analysis
Date: 2016-02-24 00:00:00

We show that multivariate Hawkes processes coupled with the nonparametric
estimation procedure first proposed in Bacry and Muzy (2015) can be
successfully used to study complex interactions between the time of arrival of
orders and their size, observed in a limit order book market. We apply this
methodology to high-frequency order book data of futures traded at EUREX.
Specifically, we demonstrate how this approach is amenable not only to analyze
interplay between different order types (market orders, limit orders,
cancellations) but also to include other relevant quantities, such as the order
size, into the analysis, showing also that simple models assuming the
independence between volume and time are not suitable to describe the data.
A geometric invariant for the study of planar curves and its application to spiral tip meander
Date: 2016-02-25 00:00:00
Tasks: ARC

Planar curves with periodically varying curvature arise in the natural
sciences as the result of a wide variety of periodic processes. The total
curvature of a periodic arc in such curves constrains their symmetry. It is
shown how the total curvature can be computed without reparameterizing the
curve to unit speed. The use of the total curvature of the periodic arcs is
demonstrated through a series of four examples from various branches of
science. Insights gained from these examples are applied to improve the
modeling of spiral wave meander.
Dimensional reduction for the general Markov model on phylogenetic trees
Date: 2016-11-28 00:00:00

We present a method of dimensional reduction for the general Markov model of
sequence evolution on a phylogenetic tree. We show that taking certain linear
combinations of the associated random variables (site pattern counts) reduces
the dimensionality of the model from exponential in the number of extant taxa,
to quadratic in the number of taxa, while retaining the ability to
statistically identify phylogenetic divergence events. A key feature is the
identification of an invariant subspace which depends only bilinearly on the
model parameters, in contrast to the usual multi-linear dependence in the full
space. We discuss potential applications including the computation of split
(edge) weights on phylogenetic trees from observed sequence data.
A Study on the usage of Data Structures in Information Retrieval
Authors: Kanagavalli V. R., Maheeja G.
Date: 2016-02-25 00:00:00
Tasks: Information Retrieval, Retrieval

This paper tries to throw light in the usage of data structures in the field
of information retrieval. Information retrieval is an area of study which is
gaining momentum as the need and urge for sharing and exploring information is
growing day by day. Data structures have been the area of research for a long
period in the arena of computer science. The need to have efficient data
structures has become even more important as the data grows in an exponential
nature.
Polynomial Diffusion Models for Life Insurance Liabilities
Date: 2016-09-23 00:00:00

In this paper we study the pricing and hedging problem of a portfolio of life
insurance products under the benchmark approach, where the reference market is
modelled as driven by a state variable following a polynomial diffusion on a
compact state space. Such a model guarantees not only the positivity of the OIS
short rate and the mortality intensity, but also the possibility of
approximating both pricing formula and hedging strategy of a large class of
life insurance products by explicit formulas.
Correcting for Cryptic Relatedness in Genome-Wide Association Studies
Date: 2016-02-25 00:00:00

While the individuals chosen for a genome-wide association study (GWAS) may
not be closely related to each other, there can be distant (cryptic)
relationships that confound the evidence of disease association. These cryptic
relationships violate the GWAS assumption regarding the independence of the
subjects' genomes, and failure to account for these relationships results in
both false positives and false negatives.
  This paper presents a method to correct for these cryptic relationships. We
accurately detect distant relationships using an expectation maximization (EM)
algorithm for finding the identity coefficients from genotype data with know
prior knowledge of relationships. From the identity coefficients we compute the
kinship coefficients and employ a kinship-corrected association test.
  We assess the accuracy of our EM kinship estimation algorithm. We show that
on genomes simulated from a Wright-Fisher pedigree, our method converges
quickly and requires only a relatively small number of sites to be accurate. We
also demonstrate that our kinship coefficient estimates outperform
state-of-the-art covariance-based approaches and PLINK's kinship estimate.
  To assess the kinship-corrected association test, we simulated individuals
from deep pedigrees and drew one site to recessively determine the disease
status. We applied our EM algorithm to estimate the kinship coefficients and
ran a kinship-adjusted association test. Our approach compares favorably with
the state-of-the-art and far out-performs a na\"ive association test.
  We advocate use of our method to detect cryptic relationships and for
correcting association tests. Not only is our model easy to interpret due to
the use of identity states as latent variables, but also inference provides
state-of-the-art accuracy.
Continuum Electrostatics Approaches to Calculating p$K_a$s and $E_m$s in Proteins
Date: 2016-02-25 00:00:00

Proteins change their charge state through protonation and redox reactions as
well as through binding charged ligands. The free energy of these reactions are
dominated by solvation and electrostatic energies and modulated by protein
conformational relaxation in response to the ionization state changes. Although
computational methods for calculating these interactions can provide very
powerful tools for predicting protein charge states, they include several
critical approximations of which users should be aware. This chapter discusses
the strengths, weaknesses, and approximations of popular computational methods
for predicting charge states and understanding their underlying electrostatic
interactions. The goal of this chapter is to inform users about applications
and potential caveats of these methods as well as outline directions for future
theoretical and computational research.
Non-Scanning Fiber-Optic Near-Infrared Beam Led to Two-Photon Optogenetic Stimulation In-Vivo
Date: 2016-02-25 00:00:00

Stimulation of specific neurons expressing opsins in a targeted region to
manipulate brain function has proved to be a powerful tool in neuroscience.
However, the use of visible light for optogenetic stimulation is invasive due
to low penetration depth and tissue damage owing to larger absorption and
scattering. Here, we report, for the first time, in-depth non-scanning
fiber-optic two-photon optogenetic stimulation (FO-TPOS) of neurons in-vivo in
transgenic mouse models. In order to optimize the deep-brain stimulation
strategy, we characterized two-photon activation efficacy at different
nearinfrared laser parameters. The significantly-enhanced in-depth stimulation
efficiency of FO-TPOS as compared to conventional single-photon beam was
demonstrated both by experiments and Monte Carlo simulation. The non-scanning
FO-TPOS technology will lead to better understanding of the in-vivo neural
circuitry because this technology permits more precise and less invasive
anatomical delivery of stimulation.
Introduction of impermeable actin-staining molecules to mammalian cells by optoporation
Date: 2016-02-25 00:00:00

The selective insertion of foreign materials, such as fluorescent markers or
plasmids, into living cells has been a challenging problem in cell
biology.However, it is often necessary that researchers insert such materials
into cells for various dynamical and/or drug delivery studies. This problem
becomes even more challenging if the study is to be limited to specific cells
within a larger population, since other transfection methods, such as viral
transfection and lipofection, are not realizable with a high degree of spatial
selectivity.Here, we have used a focused femtosecond laser beam to create a
small transient hole in the cellular membrane (optoporation) in order to inject
nanomolar concentrations of rhodamine phalloidin (an impermeable dye molecule
for staining filamentous actin) into targeted living mammalian cells (both HEK
and primary cortical neurons).Following optoporation, the bound to the
intracellular actin network and rise in fluorescence intensity was observed...
Statistical Risk Models
Date: 2017-01-25 00:00:00

We give complete algorithms and source code for constructing statistical risk
models, including methods for fixing the number of risk factors. One such
method is based on eRank (effective rank) and yields results similar to (and
further validates) the method set forth in an earlier paper by one of us. We
also give a complete algorithm and source code for computing eigenvectors and
eigenvalues of a sample covariance matrix which requires i) no costly
iterations and ii) the number of operations linear in the number of returns.
The presentation is intended to be pedagogical and oriented toward practical
applications.
Spherical Distance Metrics Applied to Protein Structure Classification
Date: 2015-12-18 00:00:00
Tasks: Classification, Clustering, Drug Design

Structural relationships among proteins are important in the study of their
evolution as well as in drug design and development. The protein 3D structure
has been shown to be effective with respect to classifying proteins. Prior work
has shown that the Double Centroid Reduced Representation (DCRR) model is a
useful geometric representation for protein structure with respect to visual
models, reducing the quantity of modeled information for each amino acid, yet
retaining the most important geometrical and chemical features of each: the
centroids of the backbone and of the side-chain. DCRR has not yet been applied
in the calculation of geometric structural similarity. Meanwhile,
multi-dimensional indexing (MDI) of protein structure combines protein
structural analysis with distance metrics to facilitate structural similarity
queries and is also used for clustering protein structures into related groups.
In this respect, the combination of geometric models with MDI has been shown to
be effective. Prior work, notably Distance and Density based Protein Indexing
(DDPIn), applies MDI to protein models based on the geometry of the CA
backbone. DDPIn distance metrics are based on radial and density functions that
incorporate spherical-based metrics, and the indices are built from metric tree
(M-tree) structures. This work combines DCRR with DDPIn for the development of
new DCRR centroid-based metrics: spherical binning distance and inter-centroid
spherical distance. The use of DCRR models will provide additional significant
structural information via the inclusion of side-chain centroids. Additionally,
the newly developed distance metric functions combined with DCRR and M-tree
indexing attempt to improve upon the performance of prior work (DDPIn), given
the same data set, with respect to both individual k-nearest neighbor (kNN)
search queries as well as clustering all proteins in the index.
A Cancer Biotherapy Resource
Date: 2015-12-15 00:00:00

Cancer Biotherapy (CB), as opposed to cancer chemotherapy, is the use of
macromolecular, biological agents instead of organic chemicals or drugs to
treat cancer. Biological agents usually have higher selectivity and have less
toxic side effects than chemical agents. The I.S.B.T.C., being the only major
information database for CB, seems lacking in some crucial information on
various cancer biotherapy regimens. It is thus necessary to have a
comprehensive curated CB database. The database accessible to cancer patients
and also should be a sounding board for scientific ideas by cancer researchers.
The database/web server has information about main families of cancer
biotherapy regimens to date, namely, Protein Kinase Inhibitors, Ras Pathway
Inhibitors, Cell-Cycle Active Agents, MAbs (monoclonal antibodies), ADEPT
(Antibody-Directed Enzyme Pro-Drug Therapy), Cytokines, Anti-Angiogenesis
Agents, Cancer Vaccines, Cell-based Immunotherapeutics, Gene Therapy,
Hematopoietic Growth Factors, Retinoids, and CAAT. For each biotherapy regimen,
we will extract the following attributes in populating the database: Cancer
type, Gene/s and gene product/s involved, Gene sequence, Organs affected,
Reference papers, Clinical phase/stage, Survival rate, Clinical test center
locations, Cost, Patient blogs, Researcher blogs, and Future work. The database
will be accessible to public through a website and had FAQs for making it
understandable to the laymen and discussion page for researchers to express
their views and ideas. In addition to information about the biotherapy
regimens, the website will link to other biologically significant databases
like structural proteomics, metabolomics, glycomics, and lipidomics databases,
as well as to news around the world regarding cancer therapy results. The
database attributes would be regularly updated for novel attributes as
discoveries are made.
Representing Rod-Shaped Protein 3D Structures in Cylindrical Coordinates
Date: 2015-12-15 00:00:00

Based on overall 3D structure, proteins may be grouped into two broad
categories, namely, globular proteins (spheroproteins), and elongated or
rod-shaped proteins (RSP). The former comprises a significant majority of
proteins. This work concerns the second category. Unlike a spheroprotein, an
RSP possesses a conspicuous axis along its longest dimension. To take advantage
of this symmetry element, we decided to represent RSPs using cylindrical
coordinates, (rho, theta, z), with the z-axis as the main axis, and one tip of
the protein at the origin. A "tip" is one of two extreme points in the protein
lying along the protein axis along its longest dimension. We first identify the
two tips, T1 and T2, of the RSP using a protein graphics software, then
determine their (Cartesian) coordinates, (h, k, l) and (m, n, o), respectively.
Arbitrarily selecting T1 as the tip at the origin, we translate the protein by
subtracting (h, k, l) from all structural coordinates. We then find the angle
alpha between vector T1-T2 and the positive z-axis by computing the scalar
product of vectors T1- T2 and OP where P is an arbitrary point along the
positive z-axis. We typically use (0, 0, p) where p is a suitable positive
number. Then we compute the cross product of the two vectors to determine the
axis about which we should rotate vector T1-T2 to make it coincide with the
positive z-axis. We use a matrix form of Rodrigues' formula to do the rotation.
We then apply the Cartesian to cylindrical coordinate transformation equations
to the system. We have applied the above transformation to 15 RSPs: 1QCE, 2JJ7,
2KPE, 3K2A, 3LHP, 2LOE, 2L3H, 2L1P, 1KSG, 1KSJ, 1KSH, 2KOL, 2KZG, 2KPF and
3MQC. We have also created a web server that can take the PDB coordinate file
of an RSP and output its cylindrical coordinates. The URL of our web server
will be announced publicly in due course.
Size-Independent Quantification of Ligand Binding Site Depth in Receptor Proteins
Date: 2015-12-15 00:00:00

We have developed a web server that implements two complementary methods to
quantify the depth of ligand binding site (LBS) in protein-ligand complexes:
the "secant plane" (SP) and "tangent sphere" (TS) methods. The protein
molecular centroid (global centroid, GC), and the LBS centroid (local centroid,
LC) are first determined. The SP is the plane passing through the LC and normal
to the line passing through the LC and the GC. The "exterior side" of the SP is
the side opposite GC. The TS is the sphere with center at GC and tangent to the
SP at LC. The percentage of protein atoms inside the TS (TS index) and on the
exterior side of the SP (SP index), are complementary measures of LBS depth.
The SPi is directly proportional to LBS depth while the TSi is inversely
proportional. We tested the two methods using a test set of 67
well-characterized protein-ligand structures (Laskowski, et al. 1996), as well
as that of an artificial protein in the form of a grid of points in the overall
shape of a sphere and in which LBS of any depth can be specified. Results from
both the SP and TS methods agree well with reported data (ibid.), and results
from the artificial case confirm that both methods are suitable measures of LBS
depth. The web server may be used in two modes. In the "ligand mode", user
inputs the protein PDB coordinates as well as those of the ligand. The "LBS
mode" is the same as the former, except that the ligand coordinates are assumed
to be unavailable; hence the user inputs what s/he believes to be the
coordinates of the LBS amino acid residues. In both cases, the web server
outputs the SP and TS indices. LBS depth is usually directly related to the
amount of conformational change a protein undergoes upon ligand binding -
ability to quantify it could allows meaningful comparison of protein
flexibility and dynamics. The URL of our web server will be announced publicly
in due course.
Non-Identifiable Pedigrees and a Bayesian Solution
Date: 2016-02-26 00:00:00

Some methods aim to correct or test for relationships or to reconstruct the
pedigree, or family tree. We show that these methods cannot resolve ties for
correct relationships due to identifiability of the pedigree likelihood which
is the probability of inheriting the data under the pedigree model. This means
that no likelihood-based method can produce a correct pedigree inference with
high probability. This lack of reliability is critical both for health and
forensics applications.
  In this paper we present the first discussion of multiple typed individuals
in non-isomorphic pedigrees, $\mathcal{P}$ and $\mathcal{Q}$, where the
likelihoods are non-identifiable, $Pr[G~|~\mathcal{P},\theta] =
Pr[G~|~\mathcal{Q},\theta]$, for all input data $G$ and all recombination rate
parameters $\theta$. While there were previously known non-identifiable pairs,
we give an example having data for multiple individuals.
  Additionally, deeper understanding of the general discrete structures driving
these non-identifiability examples has been provided, as well as results to
guide algorithms that wish to examine only identifiable pedigrees. This paper
introduces a general criteria for establishing whether a pair of pedigrees is
non-identifiable and two easy-to-compute criteria guaranteeing identifiability.
Finally, we suggest a method for dealing with non-identifiable likelihoods: use
Bayes rule to obtain the posterior from the likelihood and prior. We propose a
prior guaranteeing that the posterior distinguishes all pairs of pedigrees.
  Shortened version published as: B. Kirkpatrick. Non-identifiable pedigrees
and a Bayesian solution. Int. Symp. on Bioinformatics Res. and Appl. (ISBRA),
7292:139-152 2012.