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| prizes = Fellow of AAAS, ACMI, ASA
| prizes = Fellow of AAAS, ACMI, ASA
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'''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 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 Department of Biostatistics, Epidemiology, and Informatics.
'''Jason H. Moore''' is an [[artificial intelligence]] (AI) scientist, biomedical informatician, and [[Human genetics|human geneticist]], Chair of the Department of Computational Biomedicine, and Director of the Center for AI Research and Education at [[Cedars-Sinai Medical Center]] in [[Los Angeles]]. He holds adjunct faculty appointments at the [[University of Pennsylvania]] and the [[University of California, Los Angeles]].


== Biography ==
== Biography ==
He was a founding Director of the 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.
He was a founding Director of the 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. He was also the founding Director of the Institute for Biomedical Informatics, founding Director of the Division of Informatics, and founding Senior Associate Dean for Informatics at the [[Perelman School of Medicine]] at the [[University of Pennsylvania]] from 2015 until 2021.


He's been the editor-in-chief of the [[BioData Mining]] journal since 2008.
He was editor-in-chief of the open-access [[BioData Mining]] journal from 2008 until 2025.


== Research ==
== Research ==
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 (complex) disorders|complex disease]]. For example, he developed the [[multifactor dimensionality reduction]] (MDR)<ref>{{Cite journal|last1=Ritchie|first1=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|journal=The American Journal of Human Genetics|volume=69|issue=1|pages=138–147|doi=10.1086/321276|pmc=1226028|pmid=11404819}}</ref><ref>{{Cite journal|last1=Hahn|first1=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|journal=Bioinformatics|language=en|volume=19|issue=3|pages=376–382|doi=10.1093/bioinformatics/btf869|pmid=12584123|issn=1367-4803|doi-access=free}}</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 an 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 focuses on computational methods such as the tree-based pipeline optimization tool (TPOT)<ref>{{Cite book|last1=Olson|first1=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.|title=Applications of Evolutionary Computation |chapter=Automating Biomedical Data Science Through Tree-Based Pipeline Optimization |date=2016-03-30|volume=9597|language=en|publisher=Springer, Cham|pages=123–137|doi=10.1007/978-3-319-31204-0_9|series=Lecture Notes in Computer Science|isbn=978-3-319-31203-3|arxiv=1601.07925|s2cid=9709316}}</ref><ref>{{Cite book|last1=Olson|first1=Randal S.|last2=Bartley|first2=Nathan|last3=Urbanowicz|first3=Ryan J.|last4=Moore|first4=Jason H.|title=Proceedings of the Genetic and Evolutionary Computation Conference 2016 |chapter=Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science |date=2016-01-01|series=GECCO '16|location=New York, NY, USA|publisher=ACM|pages=485–492|doi=10.1145/2908812.2908918|isbn=9781450342063|arxiv=1603.06212|s2cid=7142590}}</ref> for [[automated machine learning]] and [[data science]]. Current work also focuses on methods and software for accessible artificial intelligence.<ref>{{cite arXiv|last1=Olson|first1=Randal S.|last2=Sipper|first2=Moshe|last3=La Cava|first3=William|last4=Tartarone|first4=Sharon|last5=Vitale|first5=Steven|last6=Fu|first6=Weixuan|last7=Holmes|first7=John H.|last8=Moore|first8=Jason H.|date=2017-05-01|title=A System for Accessible Artificial Intelligence|eprint=1705.00594|class=cs.AI}}</ref><ref>{{Cite web|url=https://www.vice.com/en/article/researchers-want-people-to-seize-the-means-of-ai-production-penn-ai/|title=These Researchers Want the People to Seize the Means of AI Production|website=Motherboard|language=en-us|access-date=2017-05-06|date=2017-05-03}}</ref>
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 (complex) disorders|complex disease]]. For example, he developed the [[multifactor dimensionality reduction]] (MDR)<ref>{{Cite journal|last1=Ritchie|first1=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|journal=The American Journal of Human Genetics|volume=69|issue=1|pages=138–147|doi=10.1086/321276|pmc=1226028|pmid=11404819}}</ref><ref>{{Cite journal|last1=Hahn|first1=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|journal=Bioinformatics|language=en|volume=19|issue=3|pages=376–382|doi=10.1093/bioinformatics/btf869|pmid=12584123|issn=1367-4803|doi-access=free}}</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 an 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 focuses on computational methods such as the tree-based pipeline optimization tool (TPOT)<ref>{{Cite book|last1=Olson|first1=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.|title=Applications of Evolutionary Computation |chapter=Automating Biomedical Data Science Through Tree-Based Pipeline Optimization |date=2016-03-30|volume=9597|language=en|publisher=Springer, Cham|pages=123–137|doi=10.1007/978-3-319-31204-0_9|series=Lecture Notes in Computer Science|isbn=978-3-319-31203-3|arxiv=1601.07925|s2cid=9709316}}</ref><ref>{{Cite book|last1=Olson|first1=Randal S.|last2=Bartley|first2=Nathan|last3=Urbanowicz|first3=Ryan J.|last4=Moore|first4=Jason H.|title=Proceedings of the Genetic and Evolutionary Computation Conference 2016 |chapter=Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science |date=2016-01-01|series=GECCO '16|location=New York, NY, USA|publisher=ACM|pages=485–492|doi=10.1145/2908812.2908918|isbn=9781450342063|arxiv=1603.06212|s2cid=7142590}}</ref> for [[automated machine learning]] and [[data science]]. Current work also focuses on methods and software for accessible artificial intelligence.<ref>{{cite arXiv|last1=Olson|first1=Randal S.|last2=Sipper|first2=Moshe|last3=La Cava|first3=William|last4=Tartarone|first4=Sharon|last5=Vitale|first5=Steven|last6=Fu|first6=Weixuan|last7=Holmes|first7=John H.|last8=Moore|first8=Jason H.|date=2017-05-01|title=A System for Accessible Artificial Intelligence|eprint=1705.00594|class=cs.AI}}</ref><ref>{{Cite web|url=https://www.vice.com/en/article/researchers-want-people-to-seize-the-means-of-ai-production-penn-ai/|title=These Researchers Want the People to Seize the Means of AI Production|website=Motherboard|language=en-us|access-date=2017-05-06|date=2017-05-03}}</ref>


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 ''BioData Mining.'' He has published more than 500 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 nearly 20 years.
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 ''BioData Mining.'' He has published more than 600 peer-reviewed articles, book chapters and editorials. His health AI research program has been continuously funded by multiple grants from the [[National Institutes of Health]] for more than 25 years.


== Honors ==
== Honors ==
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==External links==
==External links==
* [http://jasonhmoore.org Jason H. Moore's personal web page]
* [http://jasonhmoore.org Jason H. Moore's personal web page]
* [https://web.archive.org/web/20190502091900/http://epistasis.org/ Jason H. Moore's research laboratory at the University of Pennsylvania]
* [https://web.archive.org/web/20190502091900/http://epistasis.org/ Jason H. Moore's research laboratory at Cedars-Sinai]
* [https://github.com/EpistasisLab Jason H. Moore's software on Github]
* [https://github.com/EpistasisLab Jason H. Moore's software on Github]
* [http://automl.info Jason H. Moore's automated machine learning web page]
* [http://atariprojects.org Jason H. Moore's Atari retrocomputing blog]
* [http://atariprojects.org Jason H. Moore's retrocomputing blog]
* [http://retroprojects.org Jason H. Moore's general retrocomputing blog]
* {{Google Scholar id|mE1Te78AAAAJ}}
* {{Google Scholar id|mE1Te78AAAAJ}}


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