Chirag Gupta

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

Pipette is a multi-agent AI framework that generates reproducible bioinformatics workflows using a literature-derived Skill Graph, outperforming LLMs without such constraints across multiple domains.

The paper constructs a gene regulatory network resource across species and brain regions to study neurogenesis dynamics and their links to neurodevelopmental disorders.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

The paper uses single-cell multi-omics data to predict gene regulatory networks in Alzheimer's disease and control, identifying cell-type-specific dysregulation and potential drug targets.

The paper uses a network-based supervised machine learning framework to predict and rank transcription factors involved in drought tolerance in plants.

The paper develops a genome-scale regulatory network for Arabidopsis seed development, identifies key transcription factors, and provides a webtool for analyzing transcriptomes and predicting TF regulatory effects.

RECoN is a web resource that uses gene coexpression networks to analyze abiotic stress responses in rice, revealing functional and regulatory insights from new transcriptome datasets.