Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data. - Vipul Satone; Rachneet Kaur; Faraz Faghri; Mike A. Nalls; Andrew B. Singleton; Roy H. Campbell (CoRR, 2018)

GenoML: Automated Machine Learning for Genomics. - Mary B. Makarious; Hampton L. Leonard; Dan Vitale; Hirotaka Iwaki; David Saffo; Lana Sargent; Anant Dadu; Eduardo Salmerón Castaño; John F. Carter; Melina Maleknia; Juan A. Botía; Cornelis Blauwendraat; et al. (CoRR, 2021)

Application of Aligned-UMAP to longitudinal biomedical studies. - Anant Dadu; Vipul Satone; Rachneet Kaur; Mathew J. Koretsky; Hirotaka Iwaki; Yue A. Qi; Daniel M. Ramos; Brian B. Avants; Jacob Hesterman; Roger Gunn; Mark R. Cookson; Michael E. Ward; et al. (Patterns, 2023)

Federated learning for multi-omics: A performance evaluation in Parkinson's disease. - Benjamin P. Danek; Mary B. Makarious; Anant Dadu; Dan Vitale; Paul Suhwan Lee; Andrew B. Singleton; Mike A. Nalls; Jimeng Sun 001; Faraz Faghri (Patterns, 2024)

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics. - Ziyi Li 005; Cory A. Weller; Syed Shah; Nicholas L. Johnson; Ying Hao; Paige B. Jarreau; Jessica Roberts; Deyaan Guha; Colleen Bereda; Sydney Klaisner; Pedro Machado; Matteo Zanovello; et al. (Genom. Proteom. Bioinform., 2025)