Chintan Jagdishchandra Joshi

The paper evaluates algorithms for generating context-specific metabolic models using gene expression data and identifies guidelines for selecting the best models.

The paper introduces a computational framework to infer the spatial code of cell-cell interactions using transcriptomic data from C. elegans, validated with experimental confirmation.

The paper introduces a framework to predict how changes in omics data affect metabolic functions in mammalian cells using curated metabolic tasks and genome-scale networks.

StanDep improves context-specific metabolic models by using transcriptomic variability to identify core reactions, increasing inclusion of housekeeping and lowly expressed reactions.

The paper evaluates how different decisions in transcriptomic data integration affect the identification of active reactions in biochemical networks across tissues.