🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Matthew K. Matlock

James S. McDonnell Foundation

ORCID: 0000-0003-3087-4027
Computer ScienceMaterials ScienceMedicinePharmacology, Toxicology and PharmaceuticsBiochemistry, Genetics and Molecular Biology

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

1in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

ProteomeScout: a repository and analysis resource for post-translational modifications and proteins

Nucleic Acids Research(2015)10.1093/nar/gku1154
Top 33%
0.601DataRank
Top 33%54 citations

Alex S. Holehouse, Kristen M. Naegle, Matthew K. Matlock

Papers

Driven by 6 papers — median percentile 67. Top paper: “The Metabolic Rainbow: Deep Learning Phase I Metabolism in Five Colors”.

The Metabolic Rainbow: Deep Learning Phase I Metabolism in Five Colors

Journal of Chemical Information and Modeling(2020)10.1021/acs.jcim.9b00836
N/A
0.633DataRank · unranked
67 citations

Matthew K. Matlock, Tyler B. Hughes, S. Joshua Swamidass, Na Le Dang

ProteomeScout: a repository and analysis resource for post-translational modifications and proteins

Nucleic Acids Research(2015)10.1093/nar/gku1154
Top 33%
0.601DataRank
Top 33%54 citations

Alex S. Holehouse, Kristen M. Naegle, Matthew K. Matlock

Site-Level Bioactivity of Small-Molecules from Deep-Learned Representations of Quantum Chemistry

The Journal of Physical Chemistry A(2020)10.1021/acs.jpca.0c06231
N/A
0.292DataRank · unranked
6 citations

Matthew K. Matlock, S. Joshua Swamidass, Kathryn Sarullo

Dual mechanisms suppress meloxicam bioactivation relative to sudoxicam

Toxicology(2020)10.1016/j.tox.2020.152478
N/A
0DataRank · unranked
19 citations

Mary A. Schleiff, Laura Osborn, Noah R. Flynn, Matthew K. Matlock, S. Joshua Swamidass +2 more

‘Black Box’ to ‘Conversational’ Machine Learning: Ondansetron Reduces Risk of Hospital-Acquired Venous Thromboembolism

IEEE Journal of Biomedical and Health Informatics(2020)10.1109/jbhi.2020.3033405
N/A
0DataRank · unranked
31 citations

Matthew K. Matlock, Na Le Dang, Thiago A. Moulin, Keith F. Woeltje, Elizabeth L. Yanik +2 more

Deep Learning Coordinate-Free Quantum Chemistry

The Journal of Physical Chemistry A(2021)10.1021/acs.jpca.1c04462
N/A
0DataRank · unranked
7 citations

Max Hoffman, Na Le Dang, Dakota Folmsbee, Luke Langkamp, Geoffrey Hutchison +4 more