World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
104
Citations
49475
World Ranking
1234
National Ranking
730

Research.com Recognitions

  • 2011 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Jason H. Moore is affiliated with the University of Pennsylvania in the United States. Their research encompasses multiple intersecting fields including Computer Science, Biochemistry, Genetics and Molecular Biology, and Medicine.

The scientist's work spans several specialized subfields such as Artificial Intelligence, Genetics, Molecular Biology, Radiology, Nuclear Medicine and Imaging, and Health Information Management. Their research intersects a diverse set of topics with notable coverage in Genetic Associations and Epidemiology, Bioinformatics and Genomic Networks, Evolutionary Algorithms and Applications, Machine Learning and Data Classification, Machine Learning in Healthcare, Metaheuristic Optimization Algorithms Research, and Artificial Intelligence in Healthcare and Education.

Jason H. Moore has published extensively, with a particularly high frequency in certain scientific venues. These include bioRxiv (Cold Spring Harbor Laboratory), BioData Mining, arXiv (Cornell University), Scientific Reports, and Bioinformatics.

The scientist has collaborated frequently with a number of researchers, among them Marylyn D. Ritchie, Ryan J. Urbanowicz, Joseph D. Romano, Li Shen, and John H. Holmes.

Among recent publications are:

  • ChatGPT and large language models in academia: opportunities and challenges (2023, BioData Mining)
  • Multiple Plasma Biomarkers for Risk Stratification in Patients With Heart Failure and Preserved Ejection Fraction (2020, Journal of the American College of Cardiology)
  • Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes (2022, Nature Metabolism)
  • Contemporary Symbolic Regression Methods and their Relative Performance (2021, PubMed)
  • A manifesto on explainability for artificial intelligence in medicine (2022, Artificial Intelligence in Medicine)

The contributions of Jason H. Moore extend into machine learning applications in healthcare, bioinformatics networks, and evolutionary optimization methods. This positions the scientist at the intersection of computational and medical research domains.

Jason H. Moore was recognized as a Fellow of the American Association for the Advancement of Science (AAAS) in 2011.

Best Publications

  • Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

    Marylyn D. Ritchie;Lance W. Hahn;Nady Roodi;L. Renee Bailey

  • Missing heritability and strategies for finding the underlying causes of complex disease

    Evan E. Eichler;Jonathan Flint;Greg Gibson;Augustine Kong

  • The Genetic Structure and History of Africans and African Americans

    Sarah A. Tishkoff;Floyd A. Reed;Françoise R. Friedlaender;Christopher Ehret

  • Chapter 11: Genome-wide association studies.

    William S. Bush;Jason H. Moore

  • Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions.

    Lance W. Hahn;Marylyn D. Ritchie;Jason H. Moore

  • Relief-based feature selection: Introduction and review.

    Ryan J. Urbanowicz;Melissa Meeker;William G. La Cava;Randal S. Olson

  • Characterization of MicroRNA Expression Levels and Their Biological Correlates in Human Cancer Cell Lines

    Arti Gaur;David A. Jewell;Yu Liang;Dana Ridzon

  • The Ubiquitous Nature of Epistasis in Determining Susceptibility to Common Human Diseases

    Jason H. Moore

  • Proteomic patterns of tumour subsets in non-small-cell lung cancer.

    Kiyoshi Yanagisawa;Yu Shyr;Baogang J Xu;Pierre P Massion

  • TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning

    Randal S. Olson;Jason H. Moore

  • A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility

    Jason H. Moore;Joshua C. Gilbert;Chia-Ti Tsai;Fu-Tien Chiang

  • Power of multifactor dimensionality reduction for detecting gene‐gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity

    Marylyn D. Ritchie;Lance W. Hahn;Jason H. Moore

  • Bioinformatics challenges for genome-wide association studies

    Jason H. Moore;Folkert W. Asselbergs;Scott M. Williams

  • Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

    Randal S. Olson;Nathan Bartley;Ryan J. Urbanowicz;Jason H. Moore

  • Renin-Angiotensin System Gene Polymorphisms and Atrial Fibrillation

    Chia Ti Tsai;Ling Ping Lai;Jiunn Lee Lin;Fu Tien Chiang

  • A High-Density Admixture Map for Disease Gene Discovery in African Americans

    Michael W. Smith;Michael W. Smith;Nick Patterson;James A. Lautenberger;Ann L. Truelove;Ann L. Truelove

  • Alzheimer's Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans.

    Andrew J. Saykin;Li Shen;Tatiana M. Foroud;Steven G. Potkin

  • New strategies for identifying gene-gene interactions in hypertension

    Jason H Moore;Scott M Williams

  • A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction

    Digna R. Velez;Bill C. White;Alison A. Motsinger;William S. Bush

  • Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

    Li Shen;Sungeun Kim;Shannon L. Risacher;Kwangsik Nho

Frequent Co-Authors

Scott M. Williams
Scott M. Williams Case Western Reserve University
Marylyn D. Ritchie
Marylyn D. Ritchie University of Pennsylvania
Casey S. Greene
Casey S. Greene University of Colorado Denver
Andrew J. Saykin
Andrew J. Saykin Indiana University
Li Shen
Li Shen University of Pennsylvania
Moshe Sipper
Moshe Sipper Ben-Gurion University of the Negev
Margaret R. Karagas
Margaret R. Karagas Dartmouth College
Shannon L. Risacher
Shannon L. Risacher Indiana University
Kwangsik Nho
Kwangsik Nho Indiana University

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