Parallel biocomputing. - Kenneth S. Kompass; Thomas J. Hoffmann; John S. Witte (Source Code Biol. Medicine, 2011)

Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations. - Clinton L. Cario; John S. Witte (Bioinform., 2018)

Efficient Estimation and Applications of Cross-Validated Genetic Predictions. - Joel Mefford; Danny S. Park; Zhili Zheng; Arthur Ko; Mika Ala-Korpela; Markku Laakso; Paivi Pajukanta; Jian Yang 005; John S. Witte; Noah Zaitlen (RECOMB, 2019)

Efficient Estimation and Applications of Cross-Validated Genetic Predictions to Polygenic Risk Scores and Linear Mixed Models. - Joel Mefford; Danny S. Park; Zhili Zheng; Arthur Ko; Mika Ala-Korpela; Markku Laakso; Päivi Pajukanta; Jian Yang 005; John S. Witte; Noah Zaitlen (J. Comput. Biol., 2020)

Detecting methylation quantitative trait loci using a methylation random field method. - Chen Lyu 005; Manyan Huang; Nianjun Liu; Zhongxue Chen; Philip J. Lupo; Benjamin Tycko; John S. Witte; Charlotte A. Hobbs; Ming Li (Briefings Bioinform., 2021)

A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes. - Arunabha Majumdar; Kathryn S. Burch; Tanushree Haldar; Sriram Sankararaman; Bogdan Pasaniuc; W. James Gauderman; John S. Witte (Bioinform., 2021)

Random field modeling of multi-trait multi-locus association for detecting methylation quantitative trait loci. - Chen Lyu 005; Manyan Huang; Nianjun Liu; Zhongxue Chen; Philip J. Lupo; Benjamin Tycko; John S. Witte; Charlotte A. Hobbs; Ming Li (Bioinform., 2022)