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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:


Mackay TF, Moore JH
Why epistasis is important for tackling complex human disease genetics.
Genome Med 2014; 6(6):42
PMID: 25031624

Penrod NM, Greene CS, Moore JH
Predicting targeted drug combinations based on Pareto optimal patterns of coexpression network connectivity.
Genome Med 2014; 6(4):33
PMID: 24944582

White MJ, Tacconelli A, Chen JS, Wejse C, Hill PC, Gomes VF, Velez-Edwards DR, Ostergaard LJ, Hu T, Moore JH, Novelli G, Scott WK, Williams SM, Sirugo G
Epiregulin (EREG) and human V-ATPase (TCIRG1): genetic variation, ethnicity and pulmonary tuberculosis susceptibility in Guinea-Bissau and The Gambia.
Genes Immun 2014 Jun 5;
PMID: 24898387

De R, Bush WS, Moore JH
Bioinformatics challenges in genome-wide association studies (GWAS).
Methods Mol Biol 2014; 1168:63-81
PMID: 24870131

Greene CS, Tan J, Ung M, Moore JH, Cheng C
Big Data Bioinformatics.
J Cell Physiol 2014 May 6;
PMID: 24799088

Ahles TA, Li Y, McDonald BC, Schwartz GN, Kaufman PA, Tsongalis GJ, Moore JH, Saykin AJ
Longitudinal assessment of cognitive changes associated with adjuvant treatment for breast cancer: the impact of APOE and smoking.
Psychooncology 2014 Apr 30;
PMID: 24789331

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 Jun 15; 30(12):1698-706
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