Vinay K. Kartha

A Multispecies, Modality-Agnostic Scalable In Vivo Mosaic Screening Platform for Therapeutic Target Discovery

The paper presents an in vivo screening platform for validating therapeutic targets across species and modalities, identifying functional targets in fibrosis and osteoarthritis models.

Low Dose GLP-1 Therapy Attenuates Pathological Cardiac and Hepatic Remodelling in HFpEF Independent of Weight Loss

This study shows low-dose GLP-1RA therapy improves cardiac and hepatic function in HFpEF without weight loss, through mechanisms like reduced fibrosis and lipid accumulation.

Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements

The paper introduces PRINT, a deep learning method to correct chromatin accessibility data and analyze DNA-protein interactions, revealing structural and functional changes in cis-regulatory elements during hematopoiesis and aging.

Functional Inference of Gene Regulation using Single-Cell Multi-Omics

This paper develops FigR, a framework to integrate scATAC-seq and scRNA-seq data to infer gene regulatory networks and identify TF regulators in immune responses.

Chromatin potential identified by shared single cell profiling of RNA and chromatin

The paper introduces SHARE-seq, a method to profile RNA and chromatin in single cells, and identifies DORCs that predict lineage commitment by chromatin accessibility changes.

Droplet-based combinatorial indexing for massive scale single-cell epigenomics

The paper introduces a droplet-based combinatorial indexing method for high-throughput scATAC-seq, enabling large-scale single-cell chromatin accessibility profiling in mouse and human cells.

Interrogation of human hematopoiesis at single-cell and single-variant resolution

This study fine-maps genetic variants associated with blood cell traits and identifies cell types and causal mechanisms using single-cell chromatin accessibility data from the UK Biobank.

CaDrA: A computational framework for performing candidate driver analyses using binary genomic features

CaDrA identifies functionally relevant subsets of binary genomic features associated with specific outcomes, showing sensitivity and specificity in cancer datasets.