Ashish Kumar Jaiswal

The paper uses a protein language model to analyze proteomic data and shows that underrepresented protein families in reference databases are strongly coupled to oceanographic conditions.

The paper identifies conserved metabolic vulnerabilities across SARS-CoV, SARS-CoV-2, and MERS-CoV using transcriptomic data and metabolic models, revealing druggable host targets.

The paper identifies genome-environment associations in macroalgae by integrating remote sensing data with deep learning to uncover genomic signatures of ecological adaptation.

The paper identifies mutations and multi-omic changes in a Chlamydomonas mutant (H5) that enhance lipid production without affecting growth.