Kedar Nath Natarajan

Inferring large networks with matrix factorisation to capture non-linear dependencies among genes using sparse single-cell profiles

The paper introduces NIRD, a method for inferring gene networks from sparse single-cell data, showing improved performance and consistency across datasets.

Extensive folding variability between homologous chromosomes in mammalian cells

The paper uses GAM to study haplotype-specific 3D chromatin structures in mESCs, finding extensive allelic differences in chromatin architecture and gene expression mediated by Polycomb repression.

Modelling dynamics of human NDPK hexamer structure, stability and interactions

The paper identifies key residues and structural features that stabilize NDPK hexamers and heterohexamers, revealing their role in enzyme activity and complex formation.

A single-cell, time-resolved profiling of Xenopus mucociliary epithelium reveals non-hierarchical model of development

This study uses single-cell transcriptomics to reveal a non-hierarchical model of mucociliary epithelium development in Xenopus, identifying multipotent progenitors and distinct cell-type programs.

Searching match for single-cell open-chromatin profiles in large pools of single-cell transcriptomes and epigenomes for reference supported analysis

scEpiSearch enables accurate matching of single-cell open-chromatin profiles to large reference datasets, improving co-embedding and classification of epigenomic states across species and platforms.

scmTE: multivariate transfer entropy builds interpretable compact gene regulatory networks by reducing false predictions

scmTE infers gene regulatory networks from scRNA-seq data by reducing false predictions, identifying known and novel regulatory interactions in biological processes.

TENET: Gene network reconstruction using transfer entropy reveals key regulatory factors from single cell transcriptomic data

TENET reconstructs gene regulatory networks from scRNA-seq data using transfer entropy, identifying key regulators with better performance than existing methods.

Predicting gene regulatory networks from cell atlases

The paper reconstructs gene regulatory networks from three mouse cell atlases to identify global and cell-type specific regulatory modules and their roles in cellular identity.

Single-cell RNA-seq of differentiating iPS cells reveals dynamic genetic effects on gene expression

The paper uses single-cell RNA-seq of differentiating iPS cells from 125 donors to identify expression quantitative trait loci influencing gene expression during endoderm differentiation.

Single-cell transcriptomics identifies CD44 as a new marker and regulator of haematopoietic stem cells development

The paper identifies CD44 as a marker and regulator of haematopoietic stem cell development through single-cell transcriptomics and functional experiments.

The Malaria Cell Atlas: a comprehensive reference of single parasite transcriptomes across the complete Plasmodium life cycle

The paper creates a comprehensive single-cell transcriptome atlas of the Plasmodium berghei life cycle and applies it to define stages in human malaria parasites.

A rapid and robust method for single cell chromatin accessibility profiling

Upfront bulk Tn5 tagging then single-nucleus sorting into plates gives scATAC-seq libraries with higher complexity than Fluidigm C1, resolving 12 clusters among 3,385 mouse splenocytes.

Comparative analysis of sequencing technologies platforms for single-cell transcriptomics

This study compares the sensitivity and accuracy of the BGISEQ-500 and Illumina HiSeq platforms for single-cell RNA sequencing using a standardized resource of 468 unique single-cells and 1,297 matched single cDNA samples.

Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression

The paper investigates how flipping between Polycomb-repressed and active transcriptional states affects gene expression noise using integrated histone modification and single-cell RNA-seq data.