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

Frank P. MacMaster

Dalhousie University

ORCID: 0000-0002-7159-7583
Health ProfessionsPsychology

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
4.5Author 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.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Molecular Psychiatry(2020)10.1038/s41380-020-0754-0
Top 5%
4.4DataRank
Top 5%308 citations

Richard Dinga, Tim Hahn, Christopher R. K. Ching, Lisa T. Eyler, Lyubomir I. Aftanas +95 more

Papers

Driven by 13 papers — median percentile 59. Top paper: “Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group”.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Molecular Psychiatry(2020)10.1038/s41380-020-0754-0
Top 5%
4.4DataRank
Top 5%308 citations

Richard Dinga, Tim Hahn, Christopher R. K. Ching, Lisa T. Eyler, Lyubomir I. Aftanas +95 more

Regional brain morphology and current antidepressant use: findings from 32 international cohorts from the ENIGMA major depressive disorder working group

Molecular Psychiatry(2025)10.1038/s41380-025-03310-8
Top 78%
0.104DataRank
Top 78%1 citations

Yara J. Toenders, Elena Pozzi, André Alemán, Nina Alexander, Zeynep Başgöze +95 more

Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data

Journal of Alzheimer s Disease(2020)10.3233/jad-191169
N/A
0DataRank · unranked
126 citations

for the Alzheimer’s Disease Neuroimaging Initiative, Pauline Mouchès, Sophie Hu, Deepthi Rajashekar, Frank P. MacMaster +4 more

Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD Working Group

Translational Psychiatry(2020)10.1038/s41398-020-01109-5
N/A
0DataRank · unranked
65 citations

Tessa F. Blanken, Elena Pozzi, Neda Jahanshad, Lyubomir I. Aftanas, Ole A. Andreassen +48 more

Brain correlates of suicide attempt in 18,925 participants across 18 international cohorts

medRxiv(2020)10.1101/2020.05.06.20090191
N/A
0DataRank · unranked
9 citations

Paul M. Thompson, Dick J. Veltman, Elena Pozzi, Laura S. van Veltzen, Neda Jahanshad +59 more

Neural correlates of the impulse dyscontrol domain of mild behavioral impairment

International Journal of Geriatric Psychiatry(2021)10.1002/gps.5540
N/A
0DataRank · unranked
84 citations

Meng Wang, Pauline Mouchès, Deepthi Rajashekar, Tolulope T. Sajobi, Frank P. MacMaster +5 more

Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts

Biological Psychiatry(2021)10.1016/j.biopsych.2021.03.015
N/A
0DataRank · unranked
64 citations

Paul M. Thompson, Dick J. Veltman, Elena Pozzi, Laura S. van Veltzen, Neda Jahanshad +58 more

Classification of Major Depressive Disorder Using Vertex-Wise Brain Sulcal Depth, Curvature, and Thickness with a Deep and a Shallow Learning Model

arXiv (Cornell University)(2023)10.48550/arxiv.2311.11046
N/A
0DataRank · unranked
2 citations

Tracy Erwin-Grabner, Ling‐Li Zeng, Christopher R. K. Ching, André Alemán, Alyssa R. Amod +82 more

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Scientific Reports(2024)10.1038/s41598-023-47934-8
N/A
0DataRank · unranked
35 citations

Tracy Erwin-Grabner, Moji Aghajani, André Alemán, Alyssa R. Amod, Zeynep Başgöze +61 more

Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model

Molecular Psychiatry(2025)10.1038/s41380-025-03273-w
N/A
0DataRank · unranked
3 citations

Tracy Erwin-Grabner, Ling‐Li Zeng, Christopher R. K. Ching, André Alemán, Alyssa R. Amod +82 more

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

Molecular Psychiatry(2020)10.1038/s41380-020-0774-9
N/A
0DataRank · unranked
159 citations

Anbupalam Thalamuthu, Yuri Milaneschi, Dominik Grotegerd, Claas Flint, Ramona Leenings +59 more

Association of Brain Structural Measurements and Polygenic Risk Scores with Obsessive-Compulsive Symptoms in Adolescents Diagnosed with Obsessive-Compulsive Disorder, Attention-Deficit/Hyperactivity Disorder, Anxiety, Depression, Autism and Tic Disorders

medRxiv(2025)10.64898/2025.12.17.25342484
N/A
0DataRank · unranked
0 citations

S-M Shaheen, Christie L. Burton, Gregory Baldwin, Rebecca Neill, Phillip Easter +5 more

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

Translational Psychiatry(2020)10.1038/s41398-020-0842-6
N/A
0DataRank · unranked
240 citations

Elena Pozzi, Tiffany C. Ho, Laura S. van Velzen, Ilya M. Veer, Nils Opel +73 more