updated for accuracy and added some citrations

| image =Https://www.amia.org/sites/default/files/Jointsummits2017-Jason-Moore.jpg

| nationality =USA

| workplaces = [[Vanderbilt University]]<BR>[[Dartmouth College]]<BR>[[University of Pennsylvania]]

| alma_mater = [[Florida State University]]<br/>[[University of Michigan]]

| academic_advisors = Charles F. Sing, Ph.D.

| doctoral_students =

| notable_students =[[Marylyn D. Ritchie]]

| known_for = [[Multifactor dimensionality reduction]]

| field = [[Translational bioinformatics]]

| prizes = Fellow of AAAS, ACMI, ASA

'''Jason H. Moore''', is a [[translational bioinformatics]] scientist, biomedical informatician, and [[Human genetics|human geneticist]], the Edward Rose Professor of Informatics and Director of the [http://upibi.org/ Institute for Biomedical Informatics] at the [[Perelman School of Medicine]] at the [[University of Pennsylvania]], where he is also Senior Associate Dean for Informatics and Director of the Division of Informatics in the [http://www.dbei.med.upenn.edu/ Department of Biostatistics, Epidemiology, and Informatics].

He was a founding Director of the [http://www.accre.vanderbilt.edu/ Advanced Computing Center for Research and Education] at [[Vanderbilt University]] from 2000 until 2004 and founding Director of the Institute for Quantitative Biomedical Sciences at [[Geisel School of Medicine]] of [[Dartmouth College]] from 2010 until 2015.

Moore’s research focuses on the development and application of [[artificial intelligence]] and [[machine learning]] methods for modeling complex patterns in biomedical [[big data]]. A central focus is using [[informatics]] methods for identifying combinations of [[DNA]] sequence variations and environmental factors that are predictive of human [[health]] and [[Genetic_disorder#Multifactorial_and_polygenic_.28complex.29_disorders|complex disease]]. For example, he developed the [[multifactor dimensionality reduction]] (MDR)<ref>{{Cite journal|last=Ritchie|first=Marylyn D.|last2=Hahn|first2=Lance W.|last3=Roodi|first3=Nady|last4=Bailey|first4=L. Renee|last5=Dupont|first5=William D.|last6=Parl|first6=Fritz F.|last7=Moore|first7=Jason H.|date=2001-07-01|title=Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer|url=http://www.sciencedirect.com/science/article/pii/S0002929707614530|journal=The American Journal of Human Genetics|volume=69|issue=1|pages=138–147|doi=10.1086/321276|pmc=PMC1226028|pmid=11404819}}</ref><ref>{{Cite journal|last=Hahn|first=L. W.|last2=Ritchie|first2=M. D.|last3=Moore|first3=J. H.|date=2003-02-12|title=Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions|url=https://academic.oup.com/bioinformatics/article/19/3/376/258073/Multifactor-dimensionality-reduction-software-for|journal=Bioinformatics|language=en|volume=19|issue=3|pages=376–382|doi=10.1093/bioinformatics/btf869|issn=1367-4803}}</ref> machine learning method for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. He then applied MDR for improved understanding of the interplay of multiple genetic polymorphisms of [[Quantitative trait locus|complex traits]] in [[Genome-wide association study|genome-wide association studies]]. More recent work has focused on computational methods such as the [https://github.com/EpistasisLab/tpot tree-based pipeline optimization tool] (TPOT)<ref>{{Cite journal|last=Olson|first=Randal S.|last2=Urbanowicz|first2=Ryan J.|last3=Andrews|first3=Peter C.|last4=Lavender|first4=Nicole A.|last5=Kidd|first5=La Creis|last6=Moore|first6=Jason H.|date=2016-03-30|title=Automating Biomedical Data Science Through Tree-Based Pipeline Optimization|url=https://link.springer.com/chapter/10.1007/978-3-319-31204-0_9|journal=Applications of Evolutionary Computation|language=en|publisher=Springer, Cham|pages=123–137|doi=10.1007/978-3-319-31204-0_9}}</ref><ref>{{Cite journal|last=Olson|first=Randal S.|last2=Bartley|first2=Nathan|last3=Urbanowicz|first3=Ryan J.|last4=Moore|first4=Jason H.|date=2016-01-01|title=Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science|url=http://doi.acm.org/10.1145/2908812.2908918|journal=Proceedings of the Genetic and Evolutionary Computation Conference 2016|series=GECCO '16|location=New York, NY, USA|publisher=ACM|pages=485–492|doi=10.1145/2908812.2908918|isbn=9781450342063}}</ref> for automated machine learning and [[data science]].

He is a former member of the [[United States National Library of Medicine|National Library of Medicine]] grant review committee (BLIRC). He is the founding Editor-in-Chief of the journal ''[https://biodatamining.biomedcentral.com/ BioData Mining].'' He has published more than 450 peer reviewed articles, book chapters and editorials. His translational bioinformatics research program has been continuously funded by multiple grants from the [[National Institutes of Health]] for more than 15 years.

In 2011 he was elected as a Fellow of the [[American Association for the Advancement of Science]] (AAAS)<ref>{{Cite news|url=https://www.aaas.org/news/aaas-members-elected-fellows|title=AAAS Members Elected as Fellows|date=2011-12-06|work=AAAS - The World's Largest General Scientific Society|access-date=2017-05-06|language=en}}</ref> and was selected as a Kavli Fellow of the [[National Academy of Sciences]] (NAS)<ref>{{Cite web|url=https://geiselmed.dartmouth.edu/news/2013/07/17_moore/|title=Geisel School of Medicine - Dartmouth's Jason Moore selected as a Kavli Fellow of the National Academy of Sciences|website=geiselmed.dartmouth.edu|language=en|access-date=2017-05-06}}</ref> in 2013. In 2015 he was elected a Fellow of the [[American College of Medical Informatics]] (ACMI)<ref>{{Cite news|url=http://www.prweb.com/releases/2015/11/prweb13066495.htm|title=13 Fellows Inducted into American College of Medical Informatics|work=PRWeb|access-date=2017-05-06}}</ref>. In 2017 we was elected a Fellow of the [[American Statistical Association]] (ASA)<ref>{{Cite web|url=https://www.pennmedicine.org/news/news-releases/2017/april/jason-moore-elected-as-a-fellow-of-the-american-statistical-association|title=Director of the Penn Institute for Biomedical Informatics Jason Moore Elected as a Fellow of the American Statistical Association – PR News|website=www.pennmedicine.org|access-date=2017-05-06}}</ref>.

* [http://www.epistasisblog.org/ Jason H. Moore's blog]

* [https://twitter.com/moorejh Jason H. Moore on twitter]

==References==