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Jason H Moore

BioData mining

Showing results (41-50 of 87) with videos related to

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Biodata Mining|September 30, 2008
Filling the gap between biology and computer scienceJesús S Aguilar-Ruiz, Jason H Moore, Marylyn D Ritchie
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.
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.
Biodata Mining|December 24, 2015
Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networksTing Hu, Angeline S Andrew, Margaret R Karagas, 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.
Biodata Mining|April 29, 2017
Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discoveryNathaniel M Crabtree, Jason H Moore, John F Bowyer, 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.
Biodata Mining|April 15, 2025
Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modelingXi Li, Jui-Hsuan Chang, Mythreye Venkatesan, et al.
Pageof 9

Showing results (41-50 of 87) with videos related to

Sort By:
Pageof 9
Biodata Mining|September 30, 2008
Filling the gap between biology and computer scienceJesús S Aguilar-Ruiz, Jason H Moore, Marylyn D Ritchie
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.
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.
Biodata Mining|December 24, 2015
Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networksTing Hu, Angeline S Andrew, Margaret R Karagas, 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.
Biodata Mining|April 29, 2017
Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discoveryNathaniel M Crabtree, Jason H Moore, John F Bowyer, 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.
Biodata Mining|April 15, 2025
Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modelingXi Li, Jui-Hsuan Chang, Mythreye Venkatesan, et al.
Pageof 9