Anagha Joshi

ADTD improves estimation of cellular compositions from bulk transcriptomics data by adapting reference profiles to the molecular environment and identifying hidden contributions.

The paper analyzes epigenetic modifications and transcription features across human cell lines and tissues to uncover their interplay and generate new hypotheses.

The paper infers causal gene regulatory networks using enhancer RNA expression as a causal anchor and validates predictions against experimental data.

The paper uses transcriptomic data from mouse and rat liver and heart to identify functionally equivalent orthologs using co-expression network analysis.

Heat*seq enables genome-scale comparison of user-generated high-throughput sequencing experiments with public data through interactive heatmaps and dynamic dataset subsetting.