dropClust: efficient clustering of ultra-large scRNA-seq data.

Droplet based single cell transcriptomics has recently enabled parallel screening of tens of thousands of single cells. Clustering methods that scale for such high dimensional data without compromising accuracy are scarce. We exploit Locality Sensitive Hashing, an approximate nearest neighbour search technique to develop a de novo clustering algorithm for large-scale single cell data.

Exhaled breath condensate metabolome clusters for endotype discovery in asthma.

Background: Asthma is a complex, heterogeneous disorder with similar presenting symptoms but with varying underlying pathologies. Exhaled breath condensate (EBC) is a relatively unexplored matrix which reflects the signatures of respiratory epithelium, but is difficult to normalize for dilution.

Methods: Here we explored whether internally normalized global NMR spectrum patterns, combined with machine learning, could be useful for diagnostics or endotype discovery.

Dataset on information strategies for energy conservation: A field experiment in India.

The data presented in this article are related to the research article entitled: "Information strategies for energy conservation: a field experiment in India" (Chen et al., 2017) [1]. The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand.

FlavorDB: a database of flavor molecules.

Flavor is an expression of olfactory and gustatory sensations experienced through a multitude of chemical processes triggered by molecules. Beyond their key role in defining taste and smell, flavor molecules also regulate metabolic processes with consequences to health. Such molecules present in natural sources have been an integral part of human history with limited success in attempts to create synthetic alternatives.

Multi-echo reconstruction from partial K-space scans via adaptively learnt basis.

In multi-echo imaging, multiple T1/T2 weighted images of the same cross section is acquired. Acquiring multiple scans is time consuming. In order to accelerate, compressed sensing based techniques have been proposed.

Multivariate brain network graph identification in functional MRI.

Motivated by recent interest in identification of functional brain networks, we develop a new multivariate approach for functional brain network identification and name it as Multivariate Vector Regression-based Connectivity (MVRC). The proposed MVRC method regresses time series of all regions to those of other regions simultaneously and estimates pairwise association between two regions with consideration of influence of other regions and builds the adjacency matrix. Next, modularity method is applied on the adjacency matrix to detect communities or functional brain networks.

Predictors of long-term outcomes in patients with acute severe colitis: A northern Indian cohort study.

Background And Aim: Knowledge of long-term outcomes following an index episode of acute severe colitis (ASC) can help informed decision making at a time of acute exacerbation especially when colectomy is an option. We aimed to identify long-term outcomes and their predictors after a first episode of ASC in a large North Indian cohort.

Methods: Hospitalized patients satisfying Truelove and Witts' criteria under follow-up at a single center from January 2003 to December 2013 were included.

ParSel: Parallel Selection of Micro-RNAs for Survival Classification in Cancers.

It is known that tumor micro-RNAs (miRNA) can define patient survival and treatment response. We present a framework to identify miRNAs which are predictive of cancer survival. The framework attempts to rank the miRNAs by exploring their collaborative role in gene regulation.

Hypothesis driven single cell dual oscillator mathematical model of circadian rhythms.

Molecular mechanisms responsible for 24 h circadian oscillations, entrainment to external cues, encoding of day length and the time-of-day effects have been well studied experimentally. However, it is still debated from the molecular network point of view whether each cell in suprachiasmatic nuclei harbors two molecular oscillators, where one tracks dawn and the other tracks dusk activities. A single cell dual morning and evening oscillator was proposed by Daan et al.

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.

Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA-seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy.

Causal MRI reconstruction via Kalman prediction and compressed sensing correction.

This technical note addresses the problem of causal online reconstruction of dynamic MRI, i.e. given the reconstructed frames till the previous time instant, we reconstruct the frame at the current instant.

Shallow water acoustic channel estimation using two-dimensional frequency characterization.

Shallow water acoustic channel estimation techniques are presented at the intersection of time, frequency, and sparsity. Specifically, a mathematical framework is introduced that translates the problem of channel estimation to non-uniform sparse channel recovery in two-dimensional frequency domain. This representation facilitates disambiguation of slowly varying channel components against high-energy transients, which occupy different frequency ranges and also exhibit significantly different sparsity along their local distribution.

Landscape of warfarin and clopidogrel pharmacogenetic variants in Qatari population from whole exome datasets.

Aim: Pharmacogenetic landscapes of commonly used antiplatelet drugs, warfarin and clopidogrel have been studied in-depth in many countries. However, there is a paucity of data to understand their patterns in the Arab populations.

Materials & Methods: We analyzed the whole exome sequencing datasets of 100 Qatar individuals available in public domain with this perspective.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants.

MAHILA: a protocol for evaluating a nurse-delivered mHealth intervention for women with HIV and psychosocial risk factors in India.

Background: Women living with HIV are vulnerable to a variety of psychosocial barriers that limit access and adherence to treatment. There is little evidence supporting interventions for improving access and treatment adherence among vulnerable groups of women in low- and middle-income countries. The M obile Phone-Based A pproach for H ealth I mprovement, L iteracy and A dherence (MAHILA) trial is assessing the feasibility, acceptability and preliminary efficacy of a novel, theory-guided mobile health intervention delivered by nurses for enhancing self-care and treatment adherence among HIV-infected women in India.

Searching target sites on DNA by proteins: Role of DNA dynamics under confinement.

DNA-binding proteins (DBPs) rapidly search and specifically bind to their target sites on genomic DNA in order to trigger many cellular regulatory processes. It has been suggested that the facilitation of search dynamics is achieved by combining 3D diffusion with one-dimensional sliding and hopping dynamics of interacting proteins. Although, recent studies have advanced the knowledge of molecular determinants that affect one-dimensional search efficiency, the role of DNA molecule is poorly understood.

Effect of acute ethanol administration on zebrafish tail-beat motion.

Zebrafish is becoming a species of choice in neurobiological and behavioral studies of alcohol-related disorders. In these efforts, the activity of adult zebrafish is typically quantified using indirect activity measures that are either scored manually or identified automatically from the fish trajectory. The analysis of such activity measures has produced important insight into the effect of acute ethanol exposure on individual and social behavior of this vertebrate species.

An Ab Initio Method for Designing Multi-Target Specific Pharmacophores using Complementary Interaction Field of Aspartic Proteases.

For past few decades, key objectives of rational drug discovery have been the designing of specific and selective ligands for target proteins. Infectious diseases like malaria are continuously becoming resistant to traditional medicines, which inculcates need for new approaches to design inhibitors for antimalarial targets. A novel method for ab initio designing of multi target specific pharmacophores using the interaction field maps of active sites of multiple proteins has been developed to design 'specificity' pharmacophores for aspartic proteases.

Matrix factorization from non-linear projections: application in estimating T2 maps from few echoes.

This work addresses the problem of estimating T2 maps from very few (two) echoes. Existing multi-parametric non-linear curve fitting techniques require a large number (16 or 32) of echoes to estimate T2 values. We show that our method yields very accurate and robust results from only two echoes, where as the curve-fitting techniques require about 16 echoes to achieve the same level of accuracy.

A jump persistent turning walker to model zebrafish locomotion.

Zebrafish are gaining momentum as a laboratory animal species for the investigation of several functional and dysfunctional biological processes. Mathematical models of zebrafish behaviour are expected to considerably aid in the design of hypothesis-driven studies by enabling preliminary in silico tests that can be used to infer possible experimental outcomes without the use of zebrafish. This study is motivated by observations of sudden, drastic changes in zebrafish locomotion in the form of large deviations in turn rate.

Classification of collective behavior: a comparison of tracking and machine learning methods to study the effect of ambient light on fish shoaling.

Traditional approaches for the analysis of collective behavior entail digitizing the position of each individual, followed by evaluation of pertinent group observables, such as cohesion and polarization. Machine learning may enable considerable advancements in this area by affording the classification of these observables directly from images. While such methods have been successfully implemented in the classification of individual behavior, their potential in the study collective behavior is largely untested.

Influence of robotic shoal size, configuration, and activity on zebrafish behavior in a free-swimming environment.

In animal studies, robots have been recently used as a valid tool for testing a wide spectrum of hypotheses. These robots often exploit visual or auditory cues to modulate animal behavior. The propensity of zebrafish, a model organism in biological studies, toward fish with similar color patterns and shape has been leveraged to design biologically inspired robots that successfully attract zebrafish in preference tests.