Showing results (151-160 of 489) with videos related to
Sort By:
Pageof 49
Nature Biotechnology|February 24, 2026
Agentic AI and the rise of in silico team science in biomedical researchBinglan Li, Anil Kumar Saini, Jose Guadalupe Hernandez, et al.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.Plos One|June 9, 2009
Failure to replicate a genetic association may provide important clues about genetic architectureCasey S Greene, Nadia M Penrod, Scott M Williams, et al.Journal of the American Medical Informatics Association : JAMIA|February 28, 2013
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approachRyan John Urbanowicz, Angeline S Andrew, Margaret Rita Karagas, et al.Pageof 49