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

William Z. Potter

ORCID: 0000-0003-2529-6568
MedicineNeuroscience

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
0.924Author 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.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

Communications Biology(2022)10.1038/s42003-022-03795-x
Top 22%
0.924DataRank
Top 22%16 citations

Elizabeth Vance, Matthew Cloward, Ed Ringger, Louisa Dayton, Mark Ebbert +94 more

Papers

Driven by 14 papers — median percentile 78. Top paper: “Longitudinal Associations of Blood Phosphorylated Tau181 and Neurofilament Light Chain With Neurodegeneration in Alzheimer Disease”.

Longitudinal Associations of Blood Phosphorylated Tau181 and Neurofilament Light Chain With Neurodegeneration in Alzheimer Disease

JAMA Neurology(2021)10.1001/jamaneurol.2020.4986
N/A
7.4DataRank · unranked
328 citations

Michel J. Grothe, Nicholas J. Ashton, Thomas K. Karikari, Juan Lantero‐Rodriguez, Anniina Snellman +79 more

Deep learning-based polygenic risk analysis for Alzheimer’s disease prediction

Communications Medicine(2023)10.1038/s43856-023-00269-x
N/A
1.5DataRank · unranked
70 citations

Yu Chen, Fanny C.F. Ip, Yuanbing Jiang, Han Cao, Ge Lv +95 more

Higher CSF sTNFR1-related proteins associate with better prognosis in very early Alzheimer’s disease

Nature Communications(2021)10.1038/s41467-021-24220-7
N/A
1.1DataRank · unranked
36 citations

Tuğba Öztürk, Alexander Kollhoff, Whitney Wharton, J. Christina Howell, Alzheimer’s Disease Neuroimaging Initiative +95 more

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

Communications Biology(2022)10.1038/s42003-022-03795-x
Top 22%
0.924DataRank
Top 22%16 citations

Elizabeth Vance, Matthew Cloward, Ed Ringger, Louisa Dayton, Mark Ebbert +94 more

Correlation between Alzheimer’s disease and type 2 diabetes using non-negative matrix factorization

Scientific Reports(2021)10.1038/s41598-021-94048-0
N/A
0.920DataRank · unranked
32 citations

Hyunju Lee, the Alzheimer’s Disease Neuroimaging Initiative, Michael W. Weiner, Paul Aisen, Ronald Petersen +95 more

Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment

Proceedings of the National Academy of Sciences(2023)10.1073/pnas.2214634120
N/A
0.725DataRank · unranked
125 citations

Phoebe Imms, Mingxi Cheng, Anar Amgalan, Nahian F. Chowdhury, Roy J Massett +83 more

A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer’s disease

Alzheimer s Research & Therapy(2024)10.1186/s13195-024-01425-8
N/A
0.690DataRank · unranked
20 citations

Le Xue, Shuoyan Zhang, Jiacheng Yang, Qi Zhang, Min Wang +95 more

Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

Translational Psychiatry(2021)10.1038/s41398-021-01602-5
N/A
0.637DataRank · unranked
69 citations

Jiaying Lu, Hong‐Qi Li, Yuxiang Yang, Jiehui Jiang, Mei Cui +94 more

A telescope GWAS analysis strategy, based on SNPs-genes-pathways ensamble and on multivariate algorithms, to characterize late onset Alzheimer’s disease

Scientific Reports(2020)10.1038/s41598-020-67699-8
N/A
0.457DataRank · unranked
20 citations

Giulia Abate, Federico Tomasi, Veronica Tozzo, Annalisa Barla, Daniela Uberti +95 more

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

EBioMedicine(2023)10.1016/j.ebiom.2023.104820
N/A
0.406DataRank · unranked
14 citations

Jun Pyo Kim, Paula J. Bice, Kevin Huynh, Tingting Wang, Matthias Arnold +88 more

Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer’s disease

Journal of the Royal Statistical Society Series B (Statistical Methodology)(2024)10.1093/jrsssb/qkae023
N/A
0.104DataRank · unranked
1 citations

Wenbo Zhang, Swati Rane Levendovszky, Alzheimer’s Disease Neuroimaging Initiative, Michael W Weiner, Paul Aisen +86 more

Using latent profile analyses to classify subjects with anhedonia based on reward-related measures obtained in the FAST-MAS study

Journal of Affective Disorders(2023)10.1016/j.jad.2023.07.081
N/A
0DataRank · unranked
10 citations

Diego A. Pizzagalli, Moria J. Smoski, Sanjay J. Mathew, John I. Nürnberger, Sarah H. Lisanby +12 more

Biomarkers and neurobehavioral diagnosis

Biomarkers in Neuropsychiatry(2021)10.1016/j.bionps.2020.100029
N/A
0DataRank · unranked
27 citations

William Z. Potter, John A. Sweeney, Joshua B. Ewen

The GREENBEAN checklist for reporting studies evaluating the effectiveness of EEG-based biomarkers

Clinical Neurophysiology(2025)10.1016/j.clinph.2025.2110777
N/A
0DataRank · unranked
11 citations

Claudio Babiloni, Gary S. Collins, Lauren E. Ethridge, Jean Gotman, Akio Ikeda +6 more