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

Akram Mohammed

University of Tennessee Health Science Center

ORCID: 0000-0001-8093-8637
MedicineBiochemistry, 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 6%percentile
0.208Author 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.

Top 65%3 citations

Franco Mársico, Akram Mohammed, Lokesh Chinthala, Ernestine K Amos-Abanyie, Aris Baras +95 more

Papers

Driven by 4 papers — median percentile 35. Top paper: Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

69 citations

Akram Mohammed, Hector R. Wong, Nades Palaniyar, Rishikesan Kamaleswaran, Shayantan Banerjee

Top 65%3 citations

Franco Mársico, Akram Mohammed, Lokesh Chinthala, Ernestine K Amos-Abanyie, Aris Baras +95 more

0 citations

Akram Mohammed, Surabhi Naik, Daniel Faradji, Kenneth I. Ataga, Jeffrey D. Lebensburger +2 more