Sushmita Roy

This study uses single-cell RNA sequencing to identify gene regulatory networks in mucilage-producing roots across maize, sorghum, and Medicago truncatula, revealing shared and species-specific regulators.

The paper demonstrates that hiPSC-derived cardiac progenitor cells injected into swine hearts after MI form grafts that improve stress-induced contractile reserve without causing arrhythmias.

This study identifies TXNIP as a downstream effector of EPAC signaling in primary melanoma, showing its role in redox regulation and melanoma progression through mTORC1 and HIF-1 pathways.

This study identifies the pyruvate branch point as a metabolic checkpoint controlling lymphoid cancer cell migration and dissemination via mROS/HIF-1a signaling.

This paper constructs a gene regulatory network for Aspergillus fumigatus using RNA-seq data, validates it with experimental cases, and provides an online resource called GRAsp.

The paper introduces MERLIN+P+TFA to robustly estimate transcription factor activity and infer gene regulatory networks from bulk and single-cell data, showing improved accuracy in yeast and mammalian systems.

The paper identifies that PVY temporally regulates NbTPS1, which influences aphid attraction through volatile organic compounds.

This paper introduces TGIF, a multi-task NMF method for analyzing 3D genome dynamics across Hi-C datasets, identifying structural changes linked to regulatory signals and gene expression.

The paper develops L-HiC-Reg to predict long-range regulatory interactions in new cell lines and applies it to interpret GWAS SNPs in complex diseases.

The paper benchmarks eleven network inference methods on scRNA-seq datasets to evaluate their performance in recovering gene regulatory networks.

The paper analyzes RELA-bound transposable elements across species to show their ancient and lineage-specific contributions to NF-κB binding and inflammation.

This paper introduces scMTNI, a framework to infer cell type-specific gene regulatory networks on cell lineages using scRNA-seq and scATAC-seq data, showing its effectiveness on simulated and real datasets.

The paper investigates miRNA and TF binding site evolution in cichlids, linking regulatory site turnover to GRN rewiring and adaptive traits.

The paper develops a modular differentiation system to generate diverse human hindbrain and spinal neurons and uses computational methods to identify region-specific transcriptomic patterns.

GRiNCH identifies and smooths topological units from sparse chromatin contact data, improving TAD detection and structural recovery across different sequencing depths.

The paper identifies novel risk genes for autism spectrum disorder using transcriptome-wide transmission disequilibrium analysis across 7,805 ASD proband-parent trios.

This paper introduces DRMN, a method to infer cell type-specific transcriptional networks from multi-omic data, showing it accurately predicts cis-regulators and models network dynamics.

This study uses iPSC-RPE models to evaluate gene augmentation and editing for Best disease, finding that some mutations respond to gene therapy while others require genome editing.

HiC-Reg predicts high-resolution Hi-C interaction matrices from regulatory signals, identifying topologically associated domains and CTCF motifs.

This study identifies reprogramming checkpoints in iPSC generation by analyzing single-cell transcriptomes and reveals key gene interactions and regulatory mechanisms.

The paper identifies trans-acting genes associated with complex traits by correlating cis-predicted gene expression with observed expression across tissues.