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

Title(s):
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

Department(s):
Genetics
Community and Family Medicine

Education:
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)

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

Websites:
http://www.epistasis.org
http://www.iqbs.org
http://compgen.blogspot.com
http://www.twitter.com/moorejh

Contact Information:

DHMC
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

Biography:

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 2012. He serves as Editor-in-Chief of the journal BioData Mining.

Selected Publications:
 

Talukdar T, Moore JH, Diamond SG
Continuous correction of differential path length factor in near-infrared spectroscopy.
J Biomed Opt 2013 May 1; 18(5):56001
PMID: 23640027

Pechenick DA, Moore JH, Payne JL
The influence of assortativity on the robustness and evolvability of gene regulatory networks upon gene birth.
J Theor Biol 2013 Mar 28; 330C:26-36
PMID: 23542384

Hu T, Chen Y, Kiralis JW, Moore JH
ViSEN: methodology and software for visualization of statistical epistasis networks.
Genet Epidemiol 2013 Apr; 37(3):283-5
PMID: 23468157

Urbanowicz RJ, Andrew AS, Karagas MR, Moore JH
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach.
J Am Med Inform Assoc 2013 Feb 26;
PMID: 23444013

Hu T, Andrew AS, Karagas MR, Moore JH
Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models.
Pac Symp Biocomput 2013; :397-408
PMID: 23424144

Collins RL, Hu T, Wejse C, Sirugo G, Williams SM, Moore JH
Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis.
BioData Min 2013 Feb 18; 6(1):4
PMID: 23418869

Hoen AG, Gardner SN, Moore JH
Identification of SNPs associated with variola virus virulence.
BioData Min 2013 Feb 14; 6(1):3
PMID: 23410064

Hu T, Chen Y, Kiralis JW, Collins RL, Wejse C, Sirugo G, Williams SM, Moore JH
An information-gain approach to detecting three-way epistatic interactions in genetic association studies.
J Am Med Inform Assoc 2013 Feb 18;
PMID: 23396514

Andrew AS, Hu T, Gu J, Gui J, Ye Y, Marsit CJ, Kelsey KT, Schned AR, Tanyos SA, Pendleton EM, Mason RA, Morlock EV, Zens MS, Li Z, Moore JH, Wu X, Karagas MR
HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer.
PLoS One 2012; 7(12):e51301
PMID: 23284679

Urbanowicz RJ, Kiralis J, Sinnott-Armstrong NA, Heberling T, Fisher JM, Moore JH
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.
BioData Min 2012 Oct 1; 5(1):16
PMID: 23025260