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

Yuanqing Wang

Cornell University

ORCID: 0000-0003-4403-2015
Materials ScienceBiochemistry, Genetics and Molecular BiologyComputer ScienceMedicineAgricultural and Biological Sciences

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 2%percentile
3.3Author 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.

SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials

Scientific Data(2023)10.1038/s41597-022-01882-6
Top 7%
3.3DataRank
Top 7%171 citations

Pavan Kumar Behara, David Dotson, Raimondas Galvelis, John E. Herr, Joshua T. Horton +7 more

Papers

Driven by 4 papers — median percentile 93. Top paper: “SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials”.

SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials

Scientific Data(2023)10.1038/s41597-022-01882-6
Top 7%
3.3DataRank
Top 7%171 citations

Pavan Kumar Behara, David Dotson, Raimondas Galvelis, John E. Herr, Joshua T. Horton +7 more

End-to-end differentiable construction of molecular mechanics force fields

Chemical Science(2022)10.1039/d2sc02739a
N/A
0DataRank · unranked
92 citations

Josh Fass, Benjamin Kaminow, John E. Herr, Dominic A. Rufa, Ivy Zhang +6 more

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

The Journal of Physical Chemistry B(2023)10.1021/acs.jpcb.3c06662
N/A
0DataRank · unranked
495 citations

Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio +20 more

Machine-learned molecular mechanics force fields from large-scale quantum chemical data

Chemical Science(2024)10.1039/d4sc00690a
N/A
0DataRank · unranked
40 citations

Anika J. Friedman, Chapin E. Cavender, Pavan Kumar Behara, Iván Pulido, Michael M. Henry +9 more