Vivek Kohar

NetAct constructs core transcription factor regulatory networks using transcriptomics data and literature databases, outperforming existing methods in network inference.

The paper shows that gene disruption strategies in mice can lead to unexpected exon skipping and translation, resulting in gain-of-function alleles instead of null phenotypes.

The paper uses random parametric perturbations of a gene regulatory circuit in budding yeast to uncover state transitions during the cell cycle, showing consistency with single-cell RNA-seq data.

The paper constructs a gene regulatory network model for EMT hybrid states in mouse embryonic skin cells using scRNA-seq data and literature-based interactions, identifying Wnt signaling as a key pathway.

The paper develops sRACIPE, a method combining stochastic analysis with random circuit perturbation to study noise effects in gene regulatory circuits, finding that high noise merges clusters rather than large parameter variation.