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Jason Moore, PhD

Jason Moore, PhD

faculty photo
Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor
Department: Biostatistics and Epidemiology

Contact information
Institute for Biomedical Informatics
Philadelphia, PA 19104
Education:
B.S. (Biological Sciences)
Florida State University, 1991.
M.S. (Human Genetics)
University of Michigan, 1998.
M.A. (Applied Statistics)
University of Michigan, 1998.
Ph.D. (Human Genetics)
University of Michigan, 1999.
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Description of Research Expertise

Artificial intelligence, bioinformatics, biomedical informatics, complex adaptive systems, data science, epistasis, genetic architecture, genetic epidemiology, genomics, human genetics, machine learning, network science, precision medicine, simulation, systems biology, translational bioinformatics, visualization, visual analytics

Selected Publications

Frost H Robert, Amos Christopher I, Moore Jason H: A global test for gene-gene interactions based on random matrix theory. Genetic epidemiology Jul 2016.

Moore, Jason H, Amos, Ryan, Kiralis, Jeff, Andrews, Peter C: Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions. Genetic epidemiology 39(1): 25-34, 2015.

Frost, H Robert, Moore, Jason H: Optimization of gene set annotations via entropy minimization over variable clusters (EMVC). Bioinformatics 30: 1698-16706, 2014.

Pechenick, Dov A, Payne, Joshua L, Moore, Jason H: Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks. PLoS computational biology 10(8): e1003780, 2014.

Hu, Ting, Chen, Yuanzhu, Kiralis, Jeff W, Moore, Jason H: ViSEN: methodology and software for visualization of statistical epistasis networks. Genetic epidemiology 37(3): 283-285, 2013.

Bush, William S, Moore, Jason H: Genome-wide association studies. PLoS computational biology 8(12): e1002822, 2012.

Hu, Ting, Sinnott-Armstrong, Nicholas A, Kiralis, Jeff W, Andrew, Angeline S, Karagas, Margaret R, Moore, Jason H: Characterizing genetic interactions in human disease association studies using statistical epistasis networks. BMC bioinformatics 12(1): 364, 2011.

Moore, Jason H, Asselbergs, Folkert W, Williams, Scott M: Bioinformatics challenges for genome-wide association studies. Bioinformatics 26(4): 445-455, 2010.

Moore, Jason H, Williams, Scott M: Epistasis and its implications for personal genetics. The American Journal of Human Genetics 85(3): 309-320, 2009.

Moore, Jason H, Gilbert, Joshua C, Tsai, Chia-Ti, Chiang, Fu-Tien, Holden, Todd, Barney, Nate, White, Bill C: A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. Journal of theoretical biology 241(2): 252-261, 2006.

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Last updated: 07/12/2017
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