Keerthi Krishnan

Computer ScienceMedicineBiochemistry, Genetics and Molecular BiologyMaterials Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 1 paper. Top paper: “From Latent Manifolds to Functional Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Targeted Kinase Inhibitor Design”.

From Latent Manifolds to Functional Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Targeted Kinase Inhibitor Design

Preprints.org(2025)10.20944/preprints202511.1117.v1

N/A

0DataRank · unranked

0 citations

Ryan Kassab, Keerthi Krishnan, Gennady M. Verkhivker