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

Haim Bar

University of Connecticut

ORCID: 0000-0002-5496-9699
Biochemistry, Genetics and Molecular BiologyMathematics

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 4%percentile
0.779Author DataRank

Indexed papers

2in 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 2 indexed papers 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.

Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX

F1000Research(2020)10.12688/f1000research.22400.1
Top 42%
0.444DataRank
Top 42%6 citations

Jacob Kames, Gaya Hettiarachchi, John C. Athey, Upendra Katneni, Ryan Hunt +7 more

Papers

Driven by 8 papers — median percentile 53. Top paper: “Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX”.

Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX

F1000Research(2020)10.12688/f1000research.22400.1
Top 42%
0.444DataRank
Top 42%6 citations

Jacob Kames, Gaya Hettiarachchi, John C. Athey, Upendra Katneni, Ryan Hunt +7 more

Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX

F1000Research(2020)10.12688/f1000research.22400.2
Top 52%
0.335DataRank
Top 52%3 citations

Jacob Kames, Gaya Hettiarachchi, John C. Athey, Upendra Katneni, Ryan Hunt +7 more

1MO A proteomics-based platform for predicting response to immunotherapy and personalising treatment plans

Annals of Oncology(2020)10.1016/j.annonc.2020.08.2160
N/A
0DataRank · unranked
0 citations

Coren Lahav, Michal Harel, Eyal Jacob, Eran Issler, Ella Fremder +7 more

Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

Genome Medicine(2021)10.1186/s13073-021-00935-6
N/A
0DataRank · unranked
29 citations

Jacob Kames, Haim Bar, Anton A. Komar, Aikaterini Alexaki, Juan C. Ibla +6 more

Structural, functional, and immunogenicity implications of F9 gene recoding

Blood Advances(2022)10.1182/bloodadvances.2022007094
N/A
0DataRank · unranked
14 citations

Aikaterini Alexaki, Ryan Hunt, Nobuko Hamasaki‐Katagiri, Gaya Hettiarachchi, Jacob Kames +15 more

A phenotypic screen for compounds that reverse cAMP-mediated suppression of T cell functions

SLAS DISCOVERY(2022)10.1016/j.slasd.2022.03.008
N/A
0DataRank · unranked
1 citations

Meghan Wyatt, Haim Bar, Mark K. Haynes, Bruce S. Edwards, Larry A. Sklar +2 more

On graphical models and convex geometry

Computational Statistics & Data Analysis(2023)10.1016/j.csda.2023.107800
N/A
0DataRank · unranked
3 citations

Martin T. Wells, Haim Bar

Uncovering position-specific patterns in codon and codon-pair usage in candidate genes associated with blood coagulation diseases

NAR Genomics and Bioinformatics(2025)10.1093/nargab/lqaf169
N/A
0DataRank · unranked
0 citations

Nobuko Hamasaki‐Katagiri, Brian Lin, Anton A. Komar, Michael DiCuccio, Haim Bar +2 more