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Jason H Moore

Showing results (161-170 of 531) with videos related to

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IEEE/ACM Transactions on Computational Biology and Bioinformatics|October 10, 2015
An Independent Filter for Gene Set Testing Based on Spectral EnrichmentH Robert Frost, Zhigang Li, Folkert W Asselbergs, et al.
Briefings in Bioinformatics|February 7, 2012
Measuring the microbiome: perspectives on advances in DNA-based techniques for exploring microbial lifeJames A Foster, John Bunge, Jack A Gilbert, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 21, 2013
Statistical epistasis networks reduce the computational complexity of searching three-locus genetic modelsTing Hu, Angeline S Andrew, Margaret R Karagas, et al.
Biology of Sex Differences|January 24, 2026
Integrative microRNA and transcriptome analysis reveals sex-specific molecular divergence in human bladder cancerYizhou Wang, Priyanka Bhandary, Jason H Moore, et al.
Current Pharmaceutical Design|July 23, 2003
Gene expression profiles in human autoimmune diseaseThomas M Aune, Kevin Maas, Jason H Moore, 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.
Genetic Epidemiology|May 4, 2021
The Translational Machine: A novel machine-learning approach to illuminate complex genetic architecturesKathleen D Askland, David Strong, Marvin N Wright, et al.
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.
Pageof 54

Showing results (161-170 of 531) with videos related to

Sort By:
Pageof 54
IEEE/ACM Transactions on Computational Biology and Bioinformatics|October 10, 2015
An Independent Filter for Gene Set Testing Based on Spectral EnrichmentH Robert Frost, Zhigang Li, Folkert W Asselbergs, et al.
Briefings in Bioinformatics|February 7, 2012
Measuring the microbiome: perspectives on advances in DNA-based techniques for exploring microbial lifeJames A Foster, John Bunge, Jack A Gilbert, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 21, 2013
Statistical epistasis networks reduce the computational complexity of searching three-locus genetic modelsTing Hu, Angeline S Andrew, Margaret R Karagas, et al.
Biology of Sex Differences|January 24, 2026
Integrative microRNA and transcriptome analysis reveals sex-specific molecular divergence in human bladder cancerYizhou Wang, Priyanka Bhandary, Jason H Moore, et al.
Current Pharmaceutical Design|July 23, 2003
Gene expression profiles in human autoimmune diseaseThomas M Aune, Kevin Maas, Jason H Moore, 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.
Genetic Epidemiology|May 4, 2021
The Translational Machine: A novel machine-learning approach to illuminate complex genetic architecturesKathleen D Askland, David Strong, Marvin N Wright, et al.
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.
Pageof 54