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Applied Bioinformatics|May 26, 2006
Machine learning for detecting gene-gene interactions: a reviewBrett A McKinney, David M Reif, Marylyn D Ritchie, et al.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|January 17, 2015
A screening-testing approach for detecting gene-environment interactions using sequential penalized and unpenalized multiple logistic regressionH Robert Frost, Angeline S Andrew, Margaret R Karagas, et al.Bioinformatics (Oxford, England)|September 22, 2018
STatistical Inference Relief (STIR) feature selectionTrang T Le, Ryan J Urbanowicz, Jason H Moore, et al.Briefings in Bioinformatics|April 2, 2015
Adapting bioinformatics curricula for big dataAnna C Greene, Kristine A Giffin, Casey S Greene, et al.Biodata Mining|July 25, 2014
A classification and characterization of two-locus, pure, strict, epistatic models for simulation and detectionRyan J Urbanowicz, Ambrose Ls Granizo-Mackenzie, Jeff Kiralis, et al.BMC Bioinformatics|October 1, 2020
Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analysesElisabetta Manduchi, Weixuan Fu, Joseph D Romano, et al.Bioinformatics (Oxford, England)|October 5, 2023
Aliro: an automated machine learning tool leveraging large language modelsHyunjun Choi, Jay Moran, Nicholas Matsumoto, et al.Genetic Epidemiology|July 12, 2002
Symbolic discriminant analysis of microarray data in autoimmune diseaseJason H Moore, Joel S Parker, Nancy J Olsen, et al.Journal of the American Board of Family Medicine : JABFM|November 10, 2019
Prevalence and Characterization of Yoga Mentions in the Electronic Health RecordNadia M Penrod, Selah Lynch, Sunil Thomas, et al.Artificial Life|February 7, 2020
How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human DiseasesJason H Moore, Randal S Olson, Peter Schmitt, et al.Pageof 70