Showing results (161-170 of 648) with videos related to
Sort By:
Pageof 65
Trends in Genetics : TIG|April 7, 2012
Pathway analysis of genomic data: concepts, methods, and prospects for future developmentVijay K Ramanan, Li Shen, Jason H Moore, et al.Biodata Mining|September 24, 2009
Spatially uniform relieff (SURF) for computationally-efficient filtering of gene-gene interactionsCasey S Greene, Nadia M Penrod, Jeff Kiralis, et al.Biodata Mining|December 22, 2016
Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studiesSamantha Cheng, Angeline S Andrew, Peter C Andrews, et al.Genetic Programming and Evolvable Machines|August 7, 2025
TPOT-NN: augmenting tree-based automated machine learning with neural network estimatorsJoseph D Romano, Trang T Le, Weixuan Fu, et al.Patterns (New York, N.Y.)|September 10, 2025
The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learningJose Guadalupe Hernandez, Anil Kumar Saini, Attri Ghosh, et al.Chemical Research in Toxicology|July 12, 2022
Automating Predictive Toxicology Using ComptoxAIJoseph D Romano, Yun Hao, Jason H Moore, et al.Biodata Mining|July 20, 2019
Exploration of a diversity of computational and statistical measures of association for genome-wide genetic studiesElisabetta Manduchi, Patryk R Orzechowski, Marylyn D Ritchie, et al.Cancer Research|February 20, 2004
Association of homozygous wild-type glutathione S-transferase M1 genotype with increased breast cancer riskNady Roodi, William D Dupont, Jason H Moore, et al.Biodata Mining|April 1, 2009
Multifactor dimensionality reduction analysis identifies specific nucleotide patterns promoting genetic polymorphismsEric Arehart, Scott Gleim, Bill White, et al.Biodata Mining|September 28, 2012
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selectionRyan J Urbanowicz, Jeff Kiralis, Jonathan M Fisher, et al.Pageof 65