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Jason H. Moore, B.S., M.A., M.S., Ph.D.

Professor of Genetics
Professor of Community and Family Medicine
Third Century Professor
Director of the Institute for Quantitative Biomedical Sciences (iQBS)
Director of the Graduate Program in Quantitative Biomedical Sciences (QBS)
Associate Director, Norris-Cotton Cancer Center (NCCC)
Associate Director, SYNERGY
Editor-in-Chief, BioData Mining

Community and Family Medicine

University of Michigan - PhD 1999 (Human Genetics)
University of Michigan - MA 1998 (Applied Statistics)
University of Michigan - MS 1994 (Human Genetics)
Florida State University - BS 1991 (Biological Sciences)

Molecular and Cellular Biology Graduate Programs
Molecular Pathogenesis Program
Neuroscience Center at Dartmouth
Norris Cotton Cancer Center
Quantitative Biomedical Sciences


Contact Information:

One Medical Center Dr.
HB 7937
Lebanon NH 03756

Office: 706 Rubin
Phone: 603-653-9939
Fax: 603-653-9952
Email: Jason.H.Moore@Dartmouth.edu

Assistant: Kim Becker
Asst. Phone: 603-653-3634
Asst. Email: Kimberly.S.Becker@Dartmouth.EDU

Professional Interests:

Artificial Intelligence, Artificial Life, Biodefense, Bioinformatics, Biomedical Informatics, Biostatistics, Canalization, Cancer, Cardiovascular Disease, Clinical Informatics, Complex Adaptive Systems, Computational Biology, Computational Genetics, Computational Intelligence, Data Mining, Digital Genetics, Environmental Health Sciences, Epidemiology, Epistasis, Evolutionary Computing, Functional Genomics, Gene-Environment Interaction, Genetic Architecture, Genetic Epidemiology, Genetic Heterogeneity, Genome-Wide Association Studies, Genomics, Human-Computer Interaction, Human Genetics, Information Visualization, Machine Learning, Metagenomics, Network Science, Neuropsychiatric Disease, Personal Genetics, Personalized Medicine, Pharmacogenetics, Pleiotropy, Reaction Norms, Software, Statistical Genetics, Systems Biology, Video Games, Visual Analytics

Rotations and Thesis Projects:

Rotation students are always welcome. Research projects range from applied analysis of complex biomedical data to theoretical aspects of computer science, complex adaptive systems and bioinformatics.

Grant Information:

NIH R01 AI59694 (PI - Moore) "Bioinformatics Strategies for Biodefense Vaccine Research"

NIH R01 LM009012 (PI - Moore) "Machine Learning Prediction of Cancer Susceptibility"

NIH R01 LM010098 (PI - Moore) "Bioinformatics Strategies for Genome-Wide Association Analysis"

NIH R01 EY022300 (PI - Moore) "Bioinformatics Approaches for Visual Disease Genetics"

NIH R01 LM011360 (PI - Moore) "Bioinformatics Strategies for Multidimensional Brain Imaging"

NIH P20 RR024475 (PI - Moore) "Quantitative Biology Research Institute"

NIH R25 CA134286 (PI - Moore) "Training Program for Quantitative Population Sciences"

NIH R41 GM097765 (PI - Moore) “CG-GRID: Computational Genetics Grid Resource for Interaction Discovery”

Courses Taught:

GEN/QBS 146: Molecular and Computational Genomics


Dr. Moore was an Ingram Associate Professor of Cancer Research and a member of the Center for Human Genetics Research at Vanderbilt University before joining the faculty at The Geisel School of Medicine at Dartmouth in 2004. He was elected a Fellow of the American Association for the Advancement of Science (AAAS) in 2011. He was selected as a Kavli Fellow of the National Academy of Sciences in 2013. He serves as Editor-in-Chief of the journal BioData Mining.

Selected Publications:


Hu T, Pan Q, Andrew AS, Langer JM, Cole MD, Tomlinson CR, Karagas MR, Moore JH
Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.
BioData Min 2014 Apr 11; 7(1):5
PMID: 24725556

Frost HR, Moore JH
Optimization of gene set annotations via entropy minimization over variable clusters (EMVC).
Bioinformatics 2014 Mar 13;
PMID: 24574114

Pan Q, Hu T, Malley JD, Andrew AS, Karagas MR, Moore JH
A system-level pathway-phenotype association analysis using synthetic feature random forest.
Genet Epidemiol 2014 Apr; 38(3):209-19
PMID: 24535726

Penrod NM, Moore JH
Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics.
BMC Syst Biol 2014 Feb 5; 8:12
PMID: 24495353

Darabos C, White MJ, Graham BE, Leung DN, Williams SM, Moore JH
The multiscale backbone of the human phenotype network based on biological pathways.
BioData Min 2014 Jan 25; 7(1):1
PMID: 24460644

Rudd J, Moore JH, Urbanowicz RJ
A Multi-Core Parallelization Strategy for Statistical Significance Testing in Learning Classifier Systems.
Evol Intell 2013 Nov; 6(2)
PMID: 24358057

Williams SM, Moore JH
Big Data analysis on autopilot?
BioData Min 2013 Dec 6; 6(1):22
PMID: 24314297

Pattin KA, Greene AC, Altman RB, Hunter LE, Ross DA, Foster JA, Moore JH
Building the next generation of quantitative biologists.
Pac Symp Biocomput 2014; :417-21
PMID: 24297567

Darabos C, Harmon SH, Moore JH
Using the bipartite human phenotype network to reveal pleiotropy and epistasis beyond the gene.
Pac Symp Biocomput 2014; :188-99
PMID: 24297546

Moore JH, Ritchie MD
The central role of biological data mining in connecting diverse disciplines.
BioData Min 2013 Aug 12; 6(1):14
PMID: 23937773