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

Darrell E. Hurt

National Institutes of Health

ORCID: 0000-0002-9829-8567

Also affiliated with National Institute of Allergy and Infectious Diseases, Brazilian Biosciences National Laboratory

MedicineImmunology and Microbiology

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

6in 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 6 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.

“METAGENOTE: a simplified web platform for metadata annotation of genomic samples and streamlined submission to NCBI’s sequence read archive”

BMC Bioinformatics(2020)10.1186/s12859-020-03694-0
Top 13%
1.6DataRank
Top 13%33 citations

David Liou, Conrad Shyu, Wongyu Kim, Ivan Vujkovic-Cvijin, Yasmine Belkaid +2 more

Papers

Driven by 20 papers — median percentile 47. Top paper: ““METAGENOTE: a simplified web platform for metadata annotation of genomic samples and streamlined submission to NCBI’s sequence read archive””.

“METAGENOTE: a simplified web platform for metadata annotation of genomic samples and streamlined submission to NCBI’s sequence read archive”

BMC Bioinformatics(2020)10.1186/s12859-020-03694-0
Top 13%
1.6DataRank
Top 13%33 citations

David Liou, Conrad Shyu, Wongyu Kim, Ivan Vujkovic-Cvijin, Yasmine Belkaid +2 more

Radiologist observations of computed tomography (CT) images predict treatment outcome in TB Portals, a real-world database of tuberculosis (TB) cases

PLoS ONE(2021)10.1371/journal.pone.0247906
Top 24%
0.835DataRank
Top 24%14 citations

Andrei Gabrielian, Qinlu Wang, Jingwen Gu, Darrell E. Hurt, Alyssa Long +2 more

The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration

Journal of the American Medical Informatics Association(2020)10.1093/jamia/ocaa228
Top 34%
0.583DataRank
Top 34%7 citations

Alexander Glogowski, Matthew Meppiel, Lisa M. Vito, Eric Engle, Michael A. Harris +6 more

Patterns of genomic interrelatedness of publicly available samples in the TB portals database

Tuberculosis(2022)10.1016/j.tube.2022.102171
Top 72%
0.116DataRank
Top 72%1 citations

Brendan M. Jeffrey, Michael A. Harris, Andrei Gabrielian, Darrell E. Hurt, Alex Rosenthal +1 more

Analysis of a Large Patient-Level Dataset to Predict Outcome of Treatment for Drug-Resistant Tuberculosis

medRxiv(2022)10.1101/2022.09.14.22279738
Top 78%
0.104DataRank
Top 78%1 citations

Jingwen Gu, Andrei Gabrielian, Gabriel Rosenfeld, Mariam Quiñones, Darrell E. Hurt +2 more

Current challenges in microbiome metadata collection

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.05.05.442781
N/A
0DataRank · unranked
5 citations

Angelina Angelova, Chris Shin, Mariam Quiñones, Darrell E. Hurt, Gabriel Rosenfeld

Feasibility of virtual reality based training for optimising COVID-19 case handling in Uganda

BMC Medical Education(2022)10.1186/s12909-022-03294-x
N/A
0DataRank · unranked
44 citations

Elizabeth Katwesigye, Grace Kebirungi, Mike Nsubuga, Shirley Nakyejwe, Phillip Cruz +7 more

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction

Briefings in Bioinformatics(2022)10.1093/bib/bbac233
N/A
0DataRank · unranked
38 citations

Maya Grigolava, Grigol Managadze, Andrei Gabrielian, Alex Rosenthal, Darrell E. Hurt +3 more

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.01.28.478081
N/A
0DataRank · unranked
1 citations

Maya Grigolava, Grigol Managadze, Andrei Gabrielian, Alex Rosenthal, Darrell E. Hurt +3 more

Predictive capabilities of baseline radiological findings for early and late disease outcomes within sensitive and multi-drug resistant tuberculosis cases

European Journal of Radiology Open(2023)10.1016/j.ejro.2023.100518
N/A
0DataRank · unranked
3 citations

Andrei Gabrielian, Darrell E. Hurt, Alex Rosenthal, Gabriel Rosenfeld

Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis

IEEE Access(2023)10.1109/access.2023.3298750
N/A
0DataRank · unranked
5 citations

Ziv Yaniv, Michael A. Harris, Feng Yang, Karthik Kantipudi, Darrell E. Hurt +3 more

WGSA2 workflow - a tutorial v1

(2023)10.17504/protocols.io.n92ldm98xl5b/v1
N/A
0DataRank · unranked
5 citations

Duc Doan, Poorani Subramanian, Mariam Quiñones, Michael Dolan, Darrell E. Hurt +1 more

Tuberculosis chest x-ray image retrieval system using deep learning based biomarker predictions

PubMed(2024)10.1117/12.3006848
N/A
0DataRank · unranked
1 citations

Andrei Gabrielian, Darrell E. Hurt, Alex Rosenthal, Ziv Yaniv, Bradley Lowekamp

Ten simple rules for building and maintaining sustainable high-performance computing infrastructure for research in resource-limited settings

PLoS Computational Biology(2025)10.1371/journal.pcbi.1013481
N/A
0DataRank · unranked
2 citations

Christopher Whalen, Grace Kebirungi, Mugume T. Atwine, Rodgers Kimera, Alfred Ssekagiri +21 more

Low-tech solutions for the COVID-19 supply chain crisis

Nature Reviews Materials(2020)10.1038/s41578-020-0205-1
N/A
0DataRank · unranked
118 citations

Darrell E. Hurt, Darryl Hwang, Meghan Coakley McCarthy, Alexis Scholtz, Andrea M. Armani

Automated multi-lesion annotation in chest x-rays: annotating over 450,000 images from public datasets using the AI-based smart imagery framing and truthing (SIFT) system

PubMed(2025)10.1117/12.3047189
Top 100%
0DataRank
Top 100%0 citations

Fleming Lure, Teresa Hoi-Yee Wu, Fulin Cai, Stefan Jaeger, Bin Zheng +11 more

A retrospective genomic analysis of drug-resistant strains of M. tuberculosis in a high-burden setting, with an emphasis on comparative diagnostics and reactivation and reinfection status

BMC Infectious Diseases(2020)10.1186/s12879-019-4739-z
N/A
0DataRank · unranked
20 citations

Michael A. Harris, Andrei Gabrielian, Nelly Ciobanu, Dumitru Chesov, Alyssa Long +6 more

Metabolic Fate of Human Immunoactive Sterols in Mycobacterium tuberculosis

Journal of Molecular Biology(2020)10.1016/j.jmb.2020.166763
N/A
0DataRank · unranked
28 citations

Sergey Bukhdruker, Irina Grabovec, Egor Marin, Anton Kavaleuski, Anastasiia Gusach +29 more

Metabolic fate of human immunoactive sterols in Mycobacterium tuberculosis

bioRxiv (Cold Spring Harbor Laboratory)(2020)10.1101/2020.07.07.192294
N/A
0DataRank · unranked
4 citations

Sergey Bukhdruker, Irina Grabovec, Egor Marin, Anton Kavaleuski, Anastasiia Gusach +29 more

Differentiating between drug-sensitive and drug-resistant tuberculosis with machine learning for clinical and radiological features

Quantitative Imaging in Medicine and Surgery(2021)10.21037/qims-21-290
N/A
0DataRank · unranked
32 citations

Hang Yu, Karthik Kantipudi, Manohar Karki, Yasmin M. Kassim, Alex Rosenthal +4 more