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

Shujun He

Texas A&M University

ORCID: 0000-0003-1010-536X
Biochemistry, Genetics and Molecular BiologyPhysics and AstronomyMaterials 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 3%percentile
1.3Author 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.

Ribonanza: deep learning of RNA structure through dual crowdsourcing

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.02.24.581671
Top 16%
1.3DataRank
Top 16%35 citations

Rui Huang, Jill Townley, Rachael C. Kretsch, Thomas G. Karagianes, David B.T. Cox +31 more

Papers

Driven by 7 papers — median percentile 84. Top paper: “Ribonanza: deep learning of RNA structure through dual crowdsourcing”.

Ribonanza: deep learning of RNA structure through dual crowdsourcing

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.02.24.581671
Top 16%
1.3DataRank
Top 16%35 citations

Rui Huang, Jill Townley, Rachael C. Kretsch, Thomas G. Karagianes, David B.T. Cox +31 more

Deep learning models for predicting RNA degradation via dual crowdsourcing

Nature Machine Intelligence(2022)10.1038/s42256-022-00571-8
N/A
0DataRank · unranked
55 citations

Wipapat Kladwang, Andrew M. Watkins, Do Soon Kim, Bojan Tunguz, Walter Reade +24 more

RNAdegformer: accurate prediction of mRNA degradation at nucleotide resolution with deep learning

Briefings in Bioinformatics(2023)10.1093/bib/bbac581
N/A
0DataRank · unranked
38 citations

Baizhen Gao, Rushant Sabnis, Qing Sun, Shujun He

Insights into the interactions of bisphenol and phthalate compounds with unamended and carnitine-amended montmorillonite clays

Computers & Chemical Engineering(2020)10.1016/j.compchemeng.2020.107063
N/A
0DataRank · unranked
16 citations

Shujun He, Meichen Wang, Alicia Goodall, Sara E. Hearon, Timothy D. Phillips +2 more

Assessment of Nucleic Acid Structure Prediction in CASP16

Proteins Structure Function and Bioinformatics(2025)10.1002/prot.70072
N/A
0DataRank · unranked
21 citations

Alissa M. Hummer, Shujun He, Rongqing Yuan, Jing Zhang, Thomas G. Karagianes +4 more

Template-based RNA structure prediction advanced through a blind code competition

bioRxiv (Cold Spring Harbor Laboratory)(2025)10.64898/2025.12.30.696949
N/A
0DataRank · unranked
2 citations

Shujun He, Toshiyuki Oda, G Gangadhareswar Rao, Yehyun Kim, Raehyun Kim +54 more

Nucleic Transformer: Classifying DNA Sequences with Self-Attention and Convolutions

ACS Synthetic Biology(2023)10.1021/acssynbio.3c00154
N/A
0DataRank · unranked
24 citations

Baizhen Gao, Rushant Sabnis, Qing Sun, Shujun He