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ORCIDJason H. Moore
Person information
- affiliation (since 2015): University of Pennsylvania, Computational Genetics Laboratory, Philadelphia, PA, USA
- affiliation (2004-2015): Dartmouth College, Hanover, NH, USA
- affiliation (1999-2004): Vanderbilt University, Nashville, TN, USA
- affiliation (PhD 1999): University of Michigan, Ann Arbor, MI, USA
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Journal Articles
- 2024
[j170]Sandra Batista, Vered Madar, Philip J. Freda, Priyanka Bhandary, Attri Ghosh, Nicholas Matsumoto, Apurva S. Chitre, Abraham A. Palmer, Jason H. Moore:
Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis. BioData Min. 17(1) (2024)- 2023
- [j169]Abdulrahman Alasiri, Konrad J. Karczewski, Brian S. Cole, Bao-Li Loza, Jason H. Moore, Sander W. Van der Laan, Folkert W. Asselbergs
, Brendan J. Keating, Jessica van Setten:
LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes. BioData Min. 16(1) (2023) - [j168]Philip J. Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S. Chitre, Oksana Polesskaya, Celine L. St. Pierre, Jianjun Gao, Connor D. Martin, Hao Chen, Angel G. Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli, Christopher P. King, Abraham A. Palmer, Ruowang Li, Jason H. Moore:
Automated quantitative trait locus analysis (AutoQTL). BioData Min. 16(1) (2023) - [j167]John T. Gregg, Jason H. Moore:
STAR_outliers: a python package that separates univariate outliers from non-normal distributions. BioData Min. 16(1) (2023) - [j166]Jesse G. Meyer, Ryan J. Urbanowicz, Patrick C. N. Martin, Karen O'Connor, Ruowang Li, Pei-Chen Peng, Tiffani J. Bright, Nicholas P. Tatonetti, Kyoung-Jae Won, Graciela Gonzalez-Hernandez, Jason H. Moore:
ChatGPT and large language models in academia: opportunities and challenges. BioData Min. 16(1) (2023) - [j165]Scott M. Williams, Jason H. Moore:
Genetics and precision health: the ecological fallacy and artificial intelligence solutions. BioData Min. 16(1) (2023) - [j164]Hyunjun Choi, Jay Moran, Nicholas Matsumoto, Miguel E. Hernandez, Jason H. Moore:
Aliro: an automated machine learning tool leveraging large language models. Bioinform. 39(10) (2023) - [j163]Jason H. Moore:
Is the evolution metaphor still necessary or even useful for genetic programming? Genet. Program. Evolvable Mach. 24(2): 21 (2023) - [j162]William G. La Cava, Paul C. Lee, Imran Ajmal, Xiruo Ding, Priyanka Solanki, Jordana B. Cohen, Jason H. Moore, Daniel S. Herman:
A flexible symbolic regression method for constructing interpretable clinical prediction models. npj Digit. Medicine 6 (2023) - [j161]Casey-Tyler Berezin, Luis U. Aguilera, Sonja Billerbeck, Philip E. Bourne, Douglas Densmore, Paul S. Freemont, Thomas E. Gorochowski, Sarah I. Hernandez, Nathan J. Hillson, Connor R. King, Michael Köpke, Shuyi Ma, Katie M. Miller, Tae Seok Moon, Jason H. Moore, Brian Munsky, Chris J. Myers, Dequina A. Nicholas, Samuel J. Peccoud, Wen Zhou, Jean Peccoud:
Ten simple rules for managing laboratory information. PLoS Comput. Biol. 19(12) (2023) - 2022
- [j160]Carlo Combi, Beatrice Amico, Riccardo Bellazzi, Andreas Holzinger, Jason H. Moore, Marinka Zitnik, John H. Holmes:
A manifesto on explainability for artificial intelligence in medicine. Artif. Intell. Medicine 133: 102423 (2022) - [j159]Philip J. Freda, Henry R. Kranzler, Jason H. Moore:
Novel digital approaches to the assessment of problematic opioid use. BioData Min. 15(1) (2022) - [j158]Roland Albert A. Romero, Mariefel Nicole Y. Deypalan, Suchit Mehrotra, John Titus Jungao, Natalie E. Sheils, Elisabetta Manduchi, Jason H. Moore:
Benchmarking AutoML frameworks for disease prediction using medical claims. BioData Min. 15(1) (2022) - [j157]Alexa A. Woodward, Deanne M. Taylor, Elizabeth Goldmuntz, Laura E. Mitchell, A. J. Agopian, Jason H. Moore, Ryan J. Urbanowicz:
Gene-Interaction-Sensitive enrichment analysis in congenital heart disease. BioData Min. 15(1) (2022) - [j156]Joseph D. Romano, Trang T. Le, William G. La Cava, John T. Gregg, Daniel J. Goldberg, Praneel Chakraborty, Natasha L. Ray, Daniel S. Himmelstein, Weixuan Fu, Jason H. Moore:
PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods. Bioinform. 38(3): 878-880 (2022) - [j155]Xuan Wang, Harrison G. Zhang, Xin Xiong, Chuan Hong, Griffin M. Weber, Gabriel A. Brat, Clara-Lea Bonzel, Yuan Luo, Rui Duan, Nathan P. Palmer, Meghan R. Hutch, Alba Gutiérrez-Sacristán, Riccardo Bellazzi, Luca Chiovato, Kelly Cho, Arianna Dagliati, Hossein Estiri, Noelia García-Barrio, Romain Griffier, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Mark S. Keller, Jeffrey G. Klann, Sehi L'Yi, Sara Lozano-Zahonero, Sarah E. Maidlow, Adeline Makoudjou, Alberto Malovini, Bertrand Moal, Jason H. Moore, Michele Morris, Danielle L. Mowery, Shawn N. Murphy, Antoine Neuraz, Kee Yuan Ngiam, Gilbert S. Omenn, Lav P. Patel, Miguel Pedrera-Jiménez, Andrea Prunotto, Malarkodi J. Samayamuthu, Fernando J. Sanz Vidorreta, Emily Schriver, Petra Schubert, Pablo Serrano-Balazote, Andrew M. South, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Patric Tippmann, Shyam Visweswaran, Zongqi Xia, William Yuan, Daniela Zöller, Isaac S. Kohane, Paul Avillach, Zijian Guo, Tianxi Cai:
SurvMaximin: Robust federated approach to transporting survival risk prediction models. J. Biomed. Informatics 134: 104176 (2022) - [j154]Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki, Aleksander Byrski, Leszek Rutkowski, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Applying autonomous hybrid agent-based computing to difficult optimization problems. J. Comput. Sci. 64: 101858 (2022) - [j153]Mansu Kim, Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore, Qi Long, Li Shen:
Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Anal. 76: 102297 (2022) - [j152]Yun Hao, Joseph D. Romano, Jason H. Moore:
Knowledge-guided deep learning models of drug toxicity improve interpretation. Patterns 3(9): 100565 (2022) - [j151]Jason L. Causey, Keyu Li, Xianghao Chen, Wei Dong, Karl Walker, Jake A. Qualls, Jonathan Stubblefield, Jason H. Moore, Yuanfang Guan, Xiuzhen Huang:
Spatial Pyramid Pooling With 3D Convolution Improves Lung Cancer Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 1165-1172 (2022) - [j150]Elisabetta Manduchi, Trang T. Le, Weixuan Fu, Jason H. Moore:
Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1379-1386 (2022) - 2021
- [j149]Jason H. Moore:
Empowering the data science scientist. BioData Min. 14(1): 8 (2021) - [j148]Alena Orlenko, Jason H. Moore:
A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions. BioData Min. 14(1): 9 (2021) - [j147]Jason H. Moore, Van Q. Truong, Ashley B. Robbins, David Nicholson, Clar Lynda Williams-Devane:
Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science. BioData Min. 14(1): 22 (2021) - [j146]William G. La Cava, Heather Williams, Weixuan Fu, Steven Vitale, Durga Srivatsan, Jason H. Moore:
Evaluating recommender systems for AI-driven biomedical informatics. Bioinform. 37(2): 250-256 (2021) - [j145]Trang T. Le, Jason H. Moore:
treeheatr: an R package for interpretable decision tree visualizations. Bioinform. 37(2): 282-284 (2021) - [j144]Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore:
TPOT-NN: augmenting tree-based automated machine learning with neural network estimators. Genet. Program. Evolvable Mach. 22(2): 207-227 (2021) - [j143]Moshe Sipper, Jason H. Moore:
Symbolic-regression boosting. Genet. Program. Evolvable Mach. 22(3): 357-381 (2021) - [j142]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
A semantic genetic programming framework based on dynamic targets. Genet. Program. Evolvable Mach. 22(4): 463-493 (2021) - [j141]Subha Madhavan, Lisa Bastarache, Jeffrey S. Brown, Atul J. Butte, David A. Dorr, Peter J. Embí, Charles P. Friedman, Kevin B. Johnson, Jason H. Moore, Isaac S. Kohane, Philip R. O. Payne, Jessica D. Tenenbaum, Mark G. Weiner, Adam B. Wilcox, Lucila Ohno-Machado:
Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers. J. Am. Medical Informatics Assoc. 28(2): 393-401 (2021) - [j140]Jeffrey G. Klann, Hossein Estiri, Griffin M. Weber, Bertrand Moal, Paul Avillach, Chuan Hong, Amelia L. M. Tan, Brett K. Beaulieu-Jones, Victor M. Castro, Thomas Maulhardt, Alon Geva, Alberto Malovini, Andrew M. South, Shyam Visweswaran, Michele Morris, Malarkodi J. Samayamuthu, Gilbert S. Omenn, Kee Yuan Ngiam, Kenneth D. Mandl, Martin Boeker, Karen L. Olson, Danielle L. Mowery, Robert W. Follett, David A. Hanauer, Riccardo Bellazzi, Jason H. Moore, Ne-Hooi Will Loh, Douglas S. Bell, Kavishwar B. Wagholikar, Luca Chiovato, Valentina Tibollo, Siegbert Rieg, Anthony L. L. J. Li, Vianney Jouhet, Emily Schriver, Zongqi Xia, Meghan Hutch, Yuan Luo, Isaac S. Kohane, Gabriel A. Brat, Shawn N. Murphy:
Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data. J. Am. Medical Informatics Assoc. 28(7): 1411-1420 (2021) - [j139]Yun Hao, Jason H. Moore:
TargetTox: A Feature Selection Pipeline for Identifying Predictive Targets Associated with Drug Toxicity. J. Chem. Inf. Model. 61(11): 5386-5394 (2021) - [j138]John T. Gregg, Trang T. Le, Jason H. Moore:
REGENS: an open source Python package for simulating realistic autosomal genotypes. J. Open Source Softw. 6(59): 2743 (2021) - [j137]Mary Regina Boland, Lena M. Davidson, Silvia P. Canelón, Jessica R. Meeker, Trevor M. Penning, John H. Holmes, Jason H. Moore:
Harnessing electronic health records to study emerging environmental disasters: a proof of concept with perfluoroalkyl substances (PFAS). npj Digit. Medicine 4 (2021) - 2020
- [j136]Jason H. Moore, Randal S. Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi:
How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases. Artif. Life 26(1): 23-37 (2020) - [j135]Jason H. Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S. Herman, Blanca E. Himes, Rebecca A. Hubbard, Dokyoon Kim, Jeffrey S. Morris, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan J. Urbanowicz, John H. Holmes:
Ideas for how informaticians can get involved with COVID-19 research. BioData Min. 13(1): 3 (2020) - [j134]Moshe Sipper, Jason H. Moore:
Conservation machine learning. BioData Min. 13(1): 9 (2020) - [j133]Jason H. Moore:
Ten important roles for academic leaders in data science. BioData Min. 13(1): 18 (2020) - [j132]Owen Wetherbee, Jessica R. Meeker, Caroline Devoto, Trevor M. Penning, Jason H. Moore, Mary Regina Boland:
WellExplorer: an integrative resource linking hydraulic fracturing chemicals with hormonal pathways and geographic location. Database J. Biol. Databases Curation 2020 (2020) - [j131]Trang T. Le, Weixuan Fu, Jason H. Moore:
Scaling tree-based automated machine learning to biomedical big data with a feature set selector. Bioinform. 36(1): 250-256 (2020) - [j130]Alena Orlenko, Daniel Kofink, Leo-Pekka Lyytikäinen, Kjell Nikus, Pashupati P. Mishra, Pekka Kuukasjärvi, Pekka J. Karhunen, Mika Kähönen, Jari O. Laurikka, Terho Lehtimäki, Folkert W. Asselbergs, Jason H. Moore:
Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning. Bioinform. 36(6): 1772-1778 (2020) - [j129]Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Jason H. Moore, Li Shen:
Regional imaging genetic enrichment analysis. Bioinform. 36(8): 2554-2560 (2020) - [j128]Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano, Stefano Ruberto, Jason H. Moore:
Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses. BMC Bioinform. 21(1): 430 (2020) - [j127]Moshe Sipper, Jason H. Moore:
Genetic programming theory and practice: a fifteen-year trajectory. Genet. Program. Evolvable Mach. 21(1-2): 169-179 (2020) - [j126]William G. La Cava, Jason H. Moore:
Learning feature spaces for regression with genetic programming. Genet. Program. Evolvable Mach. 21(3): 433-467 (2020) - [j125]Lingjiao Zhang, Xiruo Ding, Yanyuan Ma, Naveen Muthu, Imran Ajmal, Jason H. Moore, Daniel S. Herman, Jinbo Chen:
A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients. J. Am. Medical Informatics Assoc. 27(1): 119-126 (2020) - [j124]Jiayi Tong, Jing Huang, Jessica Chubak, Xuan Wang, Jason H. Moore, Rebecca A. Hubbard, Yong Chen:
An augmented estimation procedure for EHR-based association studies accounting for differential misclassification. J. Am. Medical Informatics Assoc. 27(2): 244-253 (2020) - [j123]Rui Duan, Mary Regina Boland, Zixuan Liu, Yue Liu, Howard H. Chang, Hua Xu, Haitao Chu, Christopher H. Schmid, Christopher B. Forrest, John H. Holmes, Martijn J. Schuemie, Jesse A. Berlin, Jason H. Moore, Yong Chen:
Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm. J. Am. Medical Informatics Assoc. 27(3): 376-385 (2020) - [j122]Rui Duan, Chongliang Luo, Martijn J. Schuemie, Jiayi Tong, C. Jason Liang, Howard H. Chang, Mary Regina Boland, Jiang Bian, Hua Xu, John H. Holmes, Christopher B. Forrest, Sally C. Morton, Jesse A. Berlin, Jason H. Moore, Kevin B. Mahoney, Yong Chen:
Learning from local to global: An efficient distributed algorithm for modeling time-to-event data. J. Am. Medical Informatics Assoc. 27(7): 1028-1036 (2020) - [j121]Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie G. Kirchoff, Jean B. Craig, Jihad S. Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schriver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Esteve, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane:
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. npj Digit. Medicine 3 (2020) - [j120]Joseph D. Romano, Jason H. Moore:
Ten simple rules for writing a paper about scientific software. PLoS Comput. Biol. 16(11) (2020) - [j119]Moshe Sipper, Jason H. Moore:
Gamorithm. IEEE Trans. Games 12(1): 115-118 (2020) - 2019
- [j118]Elisabetta Manduchi, Patryk Orzechowski, Marylyn D. Ritchie, Jason H. Moore:
Exploration of a diversity of computational and statistical measures of association for genome-wide genetic studies. BioData Min. 12(1): 14:1-14:16 (2019) - [j117]Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore:
Correction to: Investigating the parameter space of evolutionary algorithms. BioData Min. 12(1): 22:1 (2019) - [j116]Trang T. Le, Ryan J. Urbanowicz, Jason H. Moore, Brett A. McKinney:
STatistical Inference Relief (STIR) feature selection. Bioinform. 35(8): 1358-1365 (2019) - [j115]Patryk Orzechowski, Jason H. Moore:
EBIC: an open source software for high-dimensional and big data analyses. Bioinform. 35(17): 3181-3183 (2019) - [j114]William G. La Cava, Thomas Helmuth, Lee Spector, Jason H. Moore:
A Probabilistic and Multi-Objective Analysis of Lexicase Selection and ε-Lexicase Selection. Evol. Comput. 27(3): 377-402 (2019) - [j113]Jason H. Moore, Nalini Raghavachari:
Artificial Intelligence Based Approaches to Identify Molecular Determinants of Exceptional Health and Life Span-An Interdisciplinary Workshop at the National Institute on Aging. Frontiers Artif. Intell. 2: 12 (2019) - [j112]Jason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper:
Automated discovery of test statistics using genetic programming. Genet. Program. Evolvable Mach. 20(1): 127-137 (2019) - [j111]Ruowang Li, Yong Chen, Jason H. Moore:
Integration of genetic and clinical information to improve imputation of data missing from electronic health records. J. Am. Medical Informatics Assoc. 26(10): 1056-1063 (2019) - [j110]Ruowang Li, Rui Duan, Daniel J. Rader, Scott M. Damrauer, Jason H. Moore, Yong Chen:
A regression framework to uncover pleiotropy in large-scale electronic health record data. J. Am. Medical Informatics Assoc. 26(10): 1083-1090 (2019) - [j109]Moshe Sipper, Jason H. Moore:
OMNIREP: originating meaning by coevolving encodings and representations. Memetic Comput. 11(3): 251-261 (2019) - [j108]Jing Huang, Xinyuan Zhang, Jiayi Tong, Jingcheng Du, Rui Duan, Liu Yang, Jason H. Moore, Cui Tao, Yong Chen:
Comparing drug safety of hepatitis C therapies using post-market data. BMC Medical Informatics Decis. Mak. 19-S(4): 147:1-147:12 (2019) - [j107]William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore:
Multidimensional genetic programming for multiclass classification. Swarm Evol. Comput. 44: 260-272 (2019) - 2018
- [j106]Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore:
Investigating the parameter space of evolutionary algorithms. BioData Min. 11(1): 2:1-2:14 (2018) - [j105]Shefali S. Verma, Anastasia Lucas, Xinyuan Zhang, Yogasudha Veturi, Scott M. Dudek, Binglan Li, Ruowang Li, Ryan J. Urbanowicz, Jason H. Moore, Dokyoon Kim, Marylyn D. Ritchie:
Collective feature selection to identify crucial epistatic variants. BioData Min. 11(1): 5:1-5:22 (2018) - [j104]Elizabeth R. Piette, Jason H. Moore:
Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV). BioData Min. 11(1): 6:1-6:11 (2018) - [j103]Moshe Sipper, Ryan J. Urbanowicz, Jason H. Moore:
To know the objective is not (necessarily) to know the objective function. BioData Min. 11(1): 21:1-21:3 (2018) - [j102]Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H. Moore:
EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery. Bioinform. 34(21): 3719-3726 (2018) - [j101]Patryk Orzechowski, Artur Panszczyk, Xiuzhen Huang, Jason H. Moore:
runibic: a Bioconductor package for parallel row-based biclustering of gene expression data. Bioinform. 34(24): 4302-4304 (2018) - [j100]Jing Huang, Rui Duan, Rebecca A. Hubbard, Yonghui Wu, Jason H. Moore, Hua Xu, Yong Chen:
PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data. J. Am. Medical Informatics Assoc. 25(3): 345-352 (2018) - [j99]Ravy K. Vajravelu, Frank I. Scott, Ronac Mamtani, Hongzhe Li, Jason H. Moore, James D. Lewis:
Medication class enrichment analysis: a novel algorithm to analyze multiple pharmacologic exposures simultaneously using electronic health record data. J. Am. Medical Informatics Assoc. 25(7): 780-789 (2018) - [j98]Ryan J. Urbanowicz, Randal S. Olson, Peter Schmitt, Melissa Meeker, Jason H. Moore:
Benchmarking relief-based feature selection methods for bioinformatics data mining. J. Biomed. Informatics 85: 168-188 (2018) - [j97]Ryan J. Urbanowicz, Melissa Meeker, William G. La Cava, Randal S. Olson, Jason H. Moore:
Relief-based feature selection: Introduction and review. J. Biomed. Informatics 85: 189-203 (2018) - [j96]Bob Zigon, Huang Li, Xiaohui Yao, Shiaofen Fang, Mohammad Al Hasan, Jingwen Yan, Jason H. Moore, Andrew J. Saykin, Li Shen:
GPU Accelerated Browser for Neuroimaging Genomics. Neuroinformatics 16(3-4): 393-402 (2018) - [j95]Brian S. Cole, Jason H. Moore:
Eleven quick tips for architecting biomedical informatics workflows with cloud computing. PLoS Comput. Biol. 14(3) (2018) - 2017
- [j94]Musaddeque Ahmed, Richard C. Sallari, Haiyang Guo, Jason H. Moore, Housheng H. He, Mathieu Lupien:
Variant Set Enrichment: an R package to identify disease-associated functional genomic regions. BioData Min. 10(1): 9:1-9:5 (2017) - [j93]Nathaniel Crabtree, Jason H. Moore, John F. Bowyer, Nysia I. George:
Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery. BioData Min. 10(1): 13:1-13:18 (2017) - [j92]Vinicius Tragante, Johannes M. I. H. Gho, Janine F. Felix, Ramachandran S. Vasan, Nicholas L. Smith, Benjamin F. Voight, Colin Palmer, Pim van der Harst, Jason H. Moore, Folkert W. Asselbergs:
Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype. BioData Min. 10(1): 18:1-18:11 (2017) - [j91]Jason H. Moore, Peter C. Andrews, Randal S. Olson, Sarah E. Carlson, Curt Larock, Mario J. Bulhoes, James P. O'Connor, Ellen M. Greytak, Steven Armentrout:
Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases. BioData Min. 10(1): 19:1-19:16 (2017) - [j90]Emily Rose Holzinger, Shefali S. Verma, Carrie Colleen Buchanan Moore, Molly A. Hall, Rishika De, Diane Gilbert-Diamond, Matthew B. Lanktree, Nathan Pankratz, Antoinette Amuzu, Amber Burt, Caroline Dale, Scott M. Dudek, Clement E. Furlong, Tom R. Gaunt, Daniel Seung Kim, Helene Riess, Suthesh Sivapalaratnam, Vinicius Tragante, Erik P. A. van Iperen, Ariel Brautbar, David S. Carrell, David R. Crosslin, Gail P. Jarvik, Helena Kuivaniemi, Iftikhar J. Kullo, Eric B. Larson, Laura J. Rasmussen-Torvik, Gerard Tromp, Jens Baumert, Karen J. Cruickshanks, Martin Farrall, Aroon D. Hingorani, G. K. Hovingh, Marcus E. Kleber, Barbara E. Klein, Ronald Klein, Wolfgang Koenig, Leslie A. Lange, Winfried März, Kari E. North, N. Charlotte Onland-Moret, Alex P. Reiner, Philippa J. Talmud, Yvonne T. van der Schouw, James G. Wilson, Mika Kivimäki, Meena Kumari, Jason H. Moore, Fotios Drenos, Folkert W. Asselbergs, Brendan J. Keating, Marylyn D. Ritchie:
Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min. 10(1): 25:1-25:20 (2017) - [j89]Moshe Sipper, Randal S. Olson, Jason H. Moore:
Evolutionary computation: the next major transition of artificial intelligence? BioData Min. 10(1): 26:1-26:3 (2017) - [j88]Spiros C. Denaxas, Kenan Direk, Arturo Gonzalez-Izquierdo, Maria Pikoula, Sera Aylin Cakiroglu, Jason H. Moore, Harry Hemingway, Liam Smeeth:
Methods for enhancing the reproducibility of biomedical research findings using electronic health records. BioData Min. 10(1): 31:1-31:19 (2017) - [j87]Moshe Sipper, Jason H. Moore:
Artificial intelligence: more human with human. BioData Min. 10(1): 34:1-34:2 (2017) - [j86]Randal S. Olson, William G. La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore:
PMLB: a large benchmark suite for machine learning evaluation and comparison. BioData Min. 10(1): 36:1-36:13 (2017) - [j85]Xiaohui Yao, Jingwen Yan, Kefei Liu, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Casey S. Greene, Jason H. Moore, Andrew J. Saykin, Li Shen:
Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules. Bioinform. 33(20): 3250-3257 (2017) - [j84]Xiaohui Yao, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Two-dimensional enrichment analysis for mining high-level imaging genetic associations. Brain Informatics 4(1): 27-37 (2017) - 2016
- [j83]Anna C. Greene, Kristine A. Giffin, Casey S. Greene, Jason H. Moore:
Adapting bioinformatics curricula for big data. Briefings Bioinform. 17(1): 43-50 (2016) - [j82]Shannon M. Lynch, Jason H. Moore:
A call for biological data mining approaches in epidemiology. BioData Min. 9: 1 (2016) - [j81]Daniel S. Himmelstein, Casey S. Greene, Jason H. Moore:
Erratum to: Evolving hard problems: generating human genetics datasets with a complex etiology. BioData Min. 9: 9 (2016) - [j80]Minjun Huang, Britney E. Graham, Ge Zhang, Reed Harder, Nuri Kodaman, Jason H. Moore, Louis J. Muglia, Scott M. Williams:
Evolutionary triangulation: informing genetic association studies with evolutionary evidence. BioData Min. 9: 12 (2016) - [j79]Jing Li, James D. Malley, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Detecting gene-gene interactions using a permutation-based random forest method. BioData Min. 9: 14 (2016) - [j78]Jason H. Moore, John H. Holmes:
The golden era of biomedical informatics has begun. BioData Min. 9: 15 (2016) - [j77]Spiros C. Denaxas, Folkert W. Asselbergs, Jason H. Moore:
The tip of the iceberg: challenges of accessing hospital electronic health record data for biological data mining. BioData Min. 9: 29 (2016) - [j76]Diego A. Forero, Jason H. Moore:
Considerations for higher efficiency and productivity in research activities. BioData Min. 9: 35:1-35:4 (2016) - [j75]Samantha Cheng, Angeline S. Andrew, Peter C. Andrews, Jason H. Moore:
Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies. BioData Min. 9: 40:1-40:6 (2016) - [j74]Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method. Bioinform. 32(10): 1544-1551 (2016) - [j73]Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Structured sparse CCA for brain imaging genetics via graph OSCAR. BMC Syst. Biol. 10(S-3): 68 (2016) - 2015
- [j72]Xiuzhen Huang, Steven F. Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole L. Cramer, Weihua Guan, Uwe Hilgert, Hongmei Jiang, Zenglu Li, Gail McClure, Donald F. McMullen, Bindu Nanduri, Andy D. Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H. Moore:
Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm. BioData Min. 8: 7 (2015) - [j71]Scott M. Williams, Jason H. Moore:
Lumping versus splitting: the need for biological data mining in precision medicine. BioData Min. 8: 16 (2015) - [j70]Jiang Gui, Casey S. Greene, Con Sullivan, Walter Taylor, Jason H. Moore, Carol Kim:
Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study. BioData Min. 8: 17 (2015) - [j69]Talia Weiss, Amanda L. Zieselman, Douglas P. Hill, Solomon Gilbert Diamond, Li Shen, Andrew J. Saykin, Jason H. Moore:
The role of visualization and 3-D printing in biological data mining. BioData Min. 8: 22 (2015) - [j68]H. Robert Frost, Zhigang Li, Jason H. Moore:
Principal component gene set enrichment (PCGSE). BioData Min. 8: 25 (2015) - [j67]Paul Thompson, Juliette Madan, Jason H. Moore:
Prediction of relevant biomedical documents: a human microbiome case study. BioData Min. 8: 28 (2015) - [j66]François Van Lishout, Francesco Gadaleta, Jason H. Moore, Louis Wehenkel, Kristel Van Steen:
gammaMAXT: a fast multiple-testing correction algorithm. BioData Min. 8: 36 (2015) - [j65]Rishika De, Shefali S. Verma, Fotios Drenos, Emily Rose Holzinger, Michael Holmes, Molly A. Hall, David R. Crosslin, David Carrell, Hakon Hakonarson, Gail P. Jarvik, Eric B. Larson, Jennifer A. Pacheco, Laura Rasmussen-Torvik, Carrie Moore, Folkert W. Asselbergs, Jason H. Moore, Marylyn D. Ritchie, Brendan Keating, Diane Gilbert-Diamond:
Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR). BioData Min. 8: 41 (2015) - [j64]Ting Hu, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks. BioData Min. 8: 43 (2015) - [j63]Rishika De, Ting Hu, Jason H. Moore, Diane Gilbert-Diamond:
Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity. BioData Min. 8: 45 (2015) - [j62]H. Robert Frost, Zhigang Li, Jason H. Moore:
Spectral gene set enrichment (SGSE). BMC Bioinform. 16: 70:1-70:11 (2015) - [j61]Yuanzhu Chen, Xu Liu, Jiafen Liu, Walter Taylor, Jason H. Moore:
Delay-tolerant networks and network coding: Comparative studies on simulated and real-device experiments. Comput. Networks 83: 349-362 (2015) - [j60]Ryan J. Urbanowicz, Jason H. Moore:
ExSTraCS 2.0: description and evaluation of a scalable learning classifier system. Evol. Intell. 8(2-3): 89-116 (2015) - [j59]H. Robert Frost, Zhigang Li, Folkert W. Asselbergs, Jason H. Moore:
An Independent Filter for Gene Set Testing Based on Spectral Enrichment. IEEE ACM Trans. Comput. Biol. Bioinform. 12(5): 1076-1086 (2015) - 2014
- [j58]Joshua L. Payne, Jason H. Moore, Andreas Wagner:
Robustness, Evolvability, and the Logic of Genetic Regulation. Artif. Life 20(1): 111-126 (2014) - [j57]Ting Hu, Wolfgang Banzhaf, Jason H. Moore:
The Effects of Recombination on Phenotypic Exploration and Robustness in Evolution. Artif. Life 20(4): 457-470 (2014) - [j56]Christian Darabos, Marquitta J. White, Britney E. Graham, Derek N. Leung, Scott M. Williams, Jason H. Moore:
The multiscale backbone of the human phenotype network based on biological pathways. BioData Min. 7: 1 (2014) - [j55]Abhijit Dasgupta, Silke Szymczak, Jason H. Moore, Joan E. Bailey-Wilson, James D. Malley:
Risk estimation using probability machines. BioData Min. 7: 2 (2014) - [j54]Ting Hu, Qinxin Pan, Angeline S. Andrew, Jillian M. Langer, Michael D. Cole, Craig R. Tomlinson, Margaret R. Karagas, Jason H. Moore:
Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility. BioData Min. 7: 5 (2014) - [j53]Ryan J. Urbanowicz, Ambrose Granizo-Mackenzie, Jeff Kiralis, Jason H. Moore:
A Classification and Characterization of Two-Locus, Pure, Strict, Epistatic Models for Simulation and Detection. BioData Min. 7: 8 (2014) - [j52]Timothy H. Ciesielski, Sarah A. Pendergrass, Marquitta J. White, Nuri Kodaman, Rafal S. Sobota, Minjun Huang, Jacquelaine Bartlett, Jing Li, Qinxin Pan, Jiang Gui, Scott B. Selleck, Christopher I. Amos, Marylyn D. Ritchie, Jason H. Moore, Scott M. Williams:
Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors. BioData Min. 7: 10 (2014) - [j51]James D. Malley, Jason H. Moore:
Innovation is often unnerving: the door into summer. BioData Min. 7: 12 (2014) - [j50]James D. Malley, Jason H. Moore:
First complex, then simple. BioData Min. 7: 13 (2014) - [j49]Amanda L. Zieselman, Jonathan M. Fisher, Ting Hu, Peter C. Andrews, Casey S. Greene, Li Shen, Andrew J. Saykin, Jason H. Moore:
Computational genetics analysis of grey matter density in Alzheimer's disease. BioData Min. 7: 17 (2014) - [j48]Magnus Lekman, Ola Hössjer, Peter C. Andrews, Henrik Källberg, Daniel Uvehag, Dennis S. Charney, Husseini K. Manji, John A. Rush, Francis J. McMahon, Jason H. Moore, Ingrid Kockum:
The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study. BioData Min. 7: 19 (2014) - [j47]James D. Malley, Karen G. Malley, Jason H. Moore:
O brave new world that has such machines in it. BioData Min. 7: 26 (2014) - [j46]Nima Pouladi, Richard Cowper-Sallari, Jason H. Moore:
Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes. BioData Min. 7: 27 (2014) - [j45]H. Robert Frost, Jason H. Moore:
Optimization of gene set annotations via entropy minimization over variable clusters (EMVC). Bioinform. 30(12): 1698-1706 (2014) - [j44]Jingwen Yan, Lei Du, Sungeun Kim, Shannon L. Risacher, Heng Huang, Jason H. Moore, Andrew J. Saykin, Li Shen:
Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. Bioinform. 30(17): 564-571 (2014) - [j43]Nadia M. Penrod, Jason H. Moore:
Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics. BMC Syst. Biol. 8: 12 (2014) - [j42]Dov A. Pechenick, Joshua L. Payne, Jason H. Moore:
Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks. PLoS Comput. Biol. 10(8) (2014) - 2013
- [j41]Anne Gatewood Hoen, Shea N. Gardner, Jason H. Moore:
Identification of SNPs associated with variola virus virulence. BioData Min. 6: 3 (2013) - [j40]Ryan L. Collins, Ting Hu, Christian Wejse, Giorgio Sirugo, Scott M. Williams, Jason H. Moore:
Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis. BioData Min. 6: 4 (2013) - [j39]James D. Malley, Abhijit Dasgupta, Jason H. Moore:
The limits of p-values for biological data mining. BioData Min. 6: 10 (2013) - [j38]James D. Malley, Jason H. Moore:
The disconnect between classical biostatistics and the biological data mining community. BioData Min. 6: 12 (2013) - [j37]Jason H. Moore, Marylyn D. Ritchie:
The central role of biological data mining in connecting diverse disciplines. BioData Min. 6: 14 (2013) - [j36]Xiuzhen Huang, Barry Bruce, Alison Buchan, Clare Bates Congdon, Carole L. Cramer, Steven F. Jennings, Hongmei Jiang, Zenglu Li, Gail McClure, Rick McMullen, Jason H. Moore, Bindu Nanduri, Joan Peckham, Andy D. Perkins, Shawn W. Polson, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Zhongming Zhao:
No-boundary thinking in bioinformatics research. BioData Min. 6: 19 (2013) - [j35]Scott M. Williams, Jason H. Moore:
Big Data analysis on autopilot? BioData Min. 6: 22 (2013) - [j34]James Rudd, Jason H. Moore, Ryan J. Urbanowicz:
A multi-core parallelization strategy for statistical significance testing in learning classifier systems. Evol. Intell. 6(2): 127-134 (2013) - [j33]Ryan J. Urbanowicz, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Research and applications: Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach. J. Am. Medical Informatics Assoc. 20(4): 603-612 (2013) - [j32]Ting Hu, Yuanzhu Peter Chen, Jeff Kiralis, Ryan L. Collins, Christian Wejse, Giorgio Sirugo, Scott M. Williams, Jason H. Moore:
Research and applications: An information-gain approach to detecting three-way epistatic interactions in genetic association studies. J. Am. Medical Informatics Assoc. 20(4): 630-636 (2013) - [j31]Joshua L. Payne, Mario Giacobini, Jason H. Moore:
Complex and dynamic population structures: synthesis, open questions, and future directions. Soft Comput. 17(7): 1109-1120 (2013) - 2012
- [j30]James A. Foster, John Bunge, Jack A. Gilbert, Jason H. Moore:
Measuring the microbiome: perspectives on advances in DNA-based techniques for exploring microbial life. Briefings Bioinform. 13(4): 420-429 (2012) - [j29]Nora Kim, Peter C. Andrews, Folkert W. Asselbergs, H. Robert Frost, Scott M. Williams, Brent T. Harris, Cynthia Read, Kathleen D. Askland, Jason H. Moore:
Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS. BioData Min. 5: 9 (2012) - [j28]Ryan J. Urbanowicz, Jeff Kiralis, Jonathan M. Fisher, Jason H. Moore:
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection. BioData Min. 5: 15 (2012) - [j27]Ryan J. Urbanowicz, Jeff Kiralis, Nicholas A. Sinnott-Armstrong, Tamra Heberling, Jonathan M. Fisher, Jason H. Moore:
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures. BioData Min. 5: 16 (2012) - [j26]Ryan J. Urbanowicz, Ambrose Granizo-Mackenzie, Jason H. Moore:
An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems. IEEE Comput. Intell. Mag. 7(4): 35-45 (2012) - [j25]Ting Hu, Joshua L. Payne, Wolfgang Banzhaf, Jason H. Moore:
Evolutionary dynamics on multiple scales: a quantitative analysis of the interplay between genotype, phenotype, and fitness in linear genetic programming. Genet. Program. Evolvable Mach. 13(3): 305-337 (2012) - [j24]William S. Bush, Jason H. Moore:
Chapter 11: Genome-Wide Association Studies. PLoS Comput. Biol. 8(12) (2012) - 2011
- [j23]Davnah Urbach, Jason H. Moore:
The spatial dimension in biological data mining. BioData Min. 4: 6 (2011) - [j22]Davnah Urbach, Jason H. Moore:
Data mining and the evolution of biological complexity. BioData Min. 4: 7 (2011) - [j21]Davnah Urbach, Jason H. Moore:
Mining beyond the exome. BioData Min. 4: 14 (2011) - [j20]Daniel S. Himmelstein, Casey S. Greene, Jason H. Moore:
Evolving hard problems: Generating human genetics datasets with a complex etiology. BioData Min. 4: 21 (2011) - [j19]Davnah Urbach, Jason H. Moore:
Mining the diseasome. BioData Min. 4: 25 (2011) - [j18]Ting Hu, Nicholas A. Sinnott-Armstrong, Jeff Kiralis, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Characterizing Genetic Interactions in Human Disease Association Studies Using Statistical Epistasis Networks. BMC Bioinform. 12: 364 (2011) - [j17]Christian Darabos, Marco Tomassini, Ferdinando Di Cunto, Paolo Provero, Jason H. Moore, Mario Giacobini:
Toward robust network based complex systems: from evolutionary cellular automata to biological models. Intelligenza Artificiale 5(1): 37-47 (2011) - 2010
- [j16]Jason H. Moore, Folkert W. Asselbergs, Scott M. Williams:
Bioinformatics challenges for genome-wide association studies. Bioinform. 26(4): 445-455 (2010) - [j15]Casey S. Greene, Nicholas A. Sinnott-Armstrong, Daniel S. Himmelstein, Paul J. Park, Jason H. Moore, Brent T. Harris:
Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS. Bioinform. 26(5): 694-695 (2010) - [j14]Li Shen, Sungeun Kim, Shannon L. Risacher, Kwangsik Nho, Shanker Swaminathan, John D. West, Tatiana Foroud, Nathan Pankratz, Jason H. Moore, Chantel D. Sloan, Matthew J. Huentelman, David W. Craig, Bryan M. DeChairo, Steven G. Potkin, Clifford R. Jack Jr., Michael W. Weiner, Andrew J. Saykin:
Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort. NeuroImage 53(3): 1051-1063 (2010) - 2009
- [j13]Eric Arehart, Scott Gleim, Bill C. White, John Hwa, Jason H. Moore:
Multifactor dimensionality reduction analysis identifies specific nucleotide patterns promoting genetic polymorphisms. BioData Min. 2 (2009) - [j12]Casey S. Greene, Nadia M. Penrod, Jeff Kiralis, Jason H. Moore:
Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions. BioData Min. 2: 5 (2009) - 2008
- [j11]Jesús S. Aguilar-Ruiz, Jason H. Moore, Marylyn D. Ritchie:
Filling the gap between biology and computer science. BioData Min. 1 (2008) - 2007
- [j10]Marylyn D. Ritchie, Alison A. Motsinger, William S. Bush, Christopher S. Coffey, Jason H. Moore:
Genetic programming neural networks: A powerful bioinformatics tool for human genetics. Appl. Soft Comput. 7(1): 471-479 (2007) - [j9]Brett A. McKinney, David M. Reif, Bill C. White, James E. Crowe Jr., Jason H. Moore:
Evaporative cooling feature selection for genotypic data involving interactions. Bioinform. 23(16): 2113-2120 (2007) - [j8]Margaret J. Eppstein, Joshua L. Payne, Bill C. White, Jason H. Moore:
Genomic mining for complex disease traits with "random chemistry". Genet. Program. Evolvable Mach. 8(4): 395-411 (2007) - 2006
- [j7]Tricia A. Thornton-Wells, Jason H. Moore, Jonathan L. Haines:
Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data. BMC Bioinform. 7: 204 (2006) - 2004
- [j6]Jason H. Moore, Lance W. Hahn, Marylyn D. Ritchie, Tricia A. Thornton, Bill C. White:
Routine discovery of complex genetic models using genetic algorithms. Appl. Soft Comput. 4(1): 79-86 (2004) - [j5]Christopher S. Coffey, Patricia R. Hebert, Marylyn D. Ritchie, Harlan M. Krumholz, J. Michael Gaziano, Paul M. Ridker, Nancy J. Brown, Douglas E. Vaughan, Jason H. Moore:
An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation. BMC Bioinform. 5: 49 (2004) - [j4]Lance W. Hahn, Jason H. Moore:
Ideal discrimination of discrete clinical endpoints using multilocus genotypes. Silico Biol. 4(2): 183-194 (2004) - 2003
- [j3]Lance W. Hahn, Marylyn D. Ritchie, Jason H. Moore:
Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinform. 19(3): 376-382 (2003) - [j2]Marylyn D. Ritchie, Bill C. White, Joel S. Parker, Lance W. Hahn, Jason H. Moore:
Optimizationof neural network architecture using genetic programming improvesdetection and modeling of gene-gene interactions in studies of humandiseases. BMC Bioinform. 4: 28 (2003) - 2000
- [j1]Jason H. Moore:
Detection of linear and nonlinear dependencies in time series using the method of surrogate data in S-PLUS. Comput. Methods Programs Biomed. 63(2): 117-121 (2000)
Conference and Workshop Papers
- 2023
- [c173]Nicholas Matsumoto, Anil Kumar Saini, Pedro Henrique Ribeiro, Hyunjun Choi, Alena Orlenko, Leo-Pekka Lyytikäinen, Jari O. Laurikka, Terho Lehtimäki, Sandra Batista, Jason H. Moore:
Faster Convergence with Lexicase Selection in Tree-Based Automated Machine Learning. EuroGP 2023: 165-181 - [c172]Rachit Kumar, Joseph D. Romano, Marylyn D. Ritchie, Jason H. Moore:
Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors. GECCO Companion 2023: 599-602 - [c171]Boning Tong, Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Jason H. Moore, Marylyn D. Ritchie, Li Shen:
Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. MLMI@MICCAI (2) 2023: 144-154 - 2022
- [c170]Jiahang Sha, Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui, Junhao Wen, Christos Davatzikos, Jason H. Moore, Andrew J. Saykin, Qi Long, Li Shen:
Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. BIBM 2022: 541-548 - [c169]Patryk Orzechowski, Pawel Renc, William G. La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Was, Joost Wagenaar:
A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark. GECCO Companion 2022: 276-279 - 2021
- [c168]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
Rapid prototyping of evolution-driven biclustering methods in Julia. GECCO Companion 2021: 61-62 - [c167]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Towards effective GP multi-class classification based on dynamic targets. GECCO 2021: 812-821 - [c166]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
EBIC.JL: an efficient implementation of evolutionary biclustering algorithm in Julia. GECCO Companion 2021: 1540-1548 - [c165]Aleksandra Urbanczyk, Bartosz Nowak, Patryk Orzechowski, Jason H. Moore, Marek Kisiel-Dorohinicki, Aleksander Byrski:
Socio-cognitive Evolution Strategies. ICCS (2) 2021: 329-342 - [c164]William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore:
Contemporary Symbolic Regression Methods and their Relative Performance. NeurIPS Datasets and Benchmarks 2021 - [c163]Carly A. Bobak, Marek Svoboda, Kristine A. Giffin, Dennis P. Wall, Jason H. Moore:
Raising the stakeholders: Improving patient outcomes through interprofessional collaborations in AI for healthcare. PSB 2021 - [c162]Dokyoon Kim, Ju Han Kim, Jason H. Moore:
Translational Bioinformatics: Integrating Electronic Health Record and Omics Data. PSB 2021 - 2020
- [c161]Mary Regina Boland, Lena M. Davidson, Silvia P. Canelón, Jessica R. Meeker, Trevor M. Penning, John H. Holmes, Jason H. Moore:
Harnessing Electronic Health Records to Study Emerging Environmental Disasters: A Proof of Concept with PFAS. AMIA 2020 - [c160]John H. Holmes, Riccardo Bellazzi, Carlo Combi, Jason H. Moore, Niels Peek:
Explainable Artificial Intelligence (XAI): Current Approaches and Paths to the Future. AMIA 2020 - [c159]Nadia M. Penrod, Selah F. Lynch, Jason H. Moore:
Extracting Behavioral Determinants of Health from Electronic Health Records: Classifying Yoga Mentions in the Clinic. HEALTHINF 2020: 77-82 - [c158]Trang T. Le, Hoyt Gong, Patryk Orzechowski, Elisabetta Manduchi, Jason H. Moore:
Expanding Polygenic Risk Scores to Include Automatic Genotype Encodings and Gene-gene Interactions. BIOINFORMATICS 2020: 79-84 - [c157]Ruowang Li, Jiayi Tong, Rui Duan, Yong Chen, Jason H. Moore:
Evaluation of Phenotyping Errors on Polygenic Risk Score Predictions. BIOINFORMATICS 2020: 123-130 - [c156]Patryk Orzechowski, Franciszek Magiera, Jason H. Moore:
Benchmarking Manifold Learning Methods on a Large Collection of Datasets. EuroGP 2020: 135-150 - [c155]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
SGP-DT: Semantic Genetic Programming Based on Dynamic Targets. EuroGP 2020: 167-183 - [c154]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Coevolving Artistic Images Using OMNIREP. EvoMUSART 2020: 165-178 - [c153]Trang T. Le, Weixuan Fu, Jason H. Moore:
Large scale biomedical data analysis with tree-based automated machine learning. GECCO Companion 2020: 21-22 - [c152]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
SGP-DT: towards effective symbolic regression with a semantic GP approach based on dynamic targets. GECCO Companion 2020: 25-26 - [c151]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Image feature learning with a genetic programming autoencoder. GECCO Companion 2020: 245-246 - [c150]William G. La Cava, Jason H. Moore:
Genetic programming approaches to learning fair classifiers. GECCO 2020: 967-975 - [c149]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
Image Feature Learning with Genetic Programming. PPSN (2) 2020: 63-78 - [c148]Jiayi Tong, Rui Duan, Ruowang Li, Martijn J. Scheuemie, Jason H. Moore, Yong Chen:
Robust-ODAL: Learning from Heterogeneous Health Systems Without Sharing Patient-LevelData. PSB 2020: 695-706 - [c147]Marylyn D. Ritchie, Jason H. Moore, Ju Han Kim:
Translational Bioinformatics: Biobanks in the Precision Medicine Era. PSB 2020: 743-747 - 2019
- [c146]William G. La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass:
Interpretation of machine learning predictions for patient outcomes in electronic health records. AMIA 2019 - [c145]Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Jason H. Moore, Li Shen:
Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis. BHI 2019: 1-4 - [c144]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems. CEC 2019: 1868-1874 - [c143]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions. EuroGP 2019: 146-161 - [c142]Jason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper:
Discovering test statistics using genetic programming. GECCO (Companion) 2019: 29-30 - [c141]Patryk Orzechowski, Jason H. Moore:
EBIC: a scalable biclustering method for large scale data analysis. GECCO (Companion) 2019: 31-32 - [c140]Patryk Orzechowski, Jason H. Moore:
Strategies for improving performance of evolutionary biclustering algorithm EBIC. GECCO (Companion) 2019: 185-186 - [c139]Patryk Orzechowski, Jason H. Moore:
Mining a massive RNA-seq dataset with biclustering: are evolutionary approaches ready for big data? GECCO (Companion) 2019: 304-305 - [c138]William G. La Cava, Jason H. Moore:
Semantic variation operators for multidimensional genetic programming. GECCO 2019: 1056-1064 - [c137]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
New Pathways in Coevolutionary Computation. GPTP 2019: 295-305 - [c136]William G. La Cava, Tilak Raj Singh, James Taggart, Srinivas Suri, Jason H. Moore:
Learning concise representations for regression by evolving networks of trees. ICLR (Poster) 2019 - [c135]Yancy Lo, Selah F. Lynch, Ryan J. Urbanowicz, Randal S. Olson, Ashley Z. Ritter, Christina R. Whitehouse, Melissa O'Connor, Susan K. Keim, Margaret V. McDonald, Jason H. Moore, Kathryn H. Bowles:
Using Machine Learning on Home Health Care Assessments to Predict Fall Risk. MedInfo 2019: 684-688 - [c134]Rui Duan, Mary Regina Boland, Jason H. Moore, Yong Chen:
ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. PSB 2019: 30-41 - [c133]Joanne Berghout, Yves A. Lussier, Francesca Vitali, Martha L. Bulyk, Maricel G. Kann, Jason H. Moore:
Reading between the genes: interpreting non-coding DNA in high-throughput. PSB 2019: 444-448 - [c132]Yves A. Lussier, Atul J. Butte, Haiquan Li, Rong Chen, Jason H. Moore:
Translational informatics of population Health: How large biomolecular and clinical datasets unite. PSB 2019: 455 - 2018
- [c131]Jing Huang, Xinyuan Zhang, Jiayi Tong, Jingcheng Du, Rui Duan, Liu Yang, Jason H. Moore, Yong Chen, Cui Tao:
Comparing adverse effects of Hepatitis C drugs using FAERS data. BIBM 2018: 1653-1656 - [c130]William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore:
A multidimensional genetic programming approach for identifying epsistatic gene interactions. GECCO (Companion) 2018: 23-24 - [c129]Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore:
Evolutionary computation: an investigation of parameter space. GECCO (Companion) 2018: 29-30 - [c128]Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H. Moore:
EBIC: a next-generation evolutionary-based parallel biclustering method. GECCO (Companion) 2018: 59-60 - [c127]William G. La Cava, Jason H. Moore:
An analysis of ϵ-lexicase selection for large-scale many-objective optimization. GECCO (Companion) 2018: 185-186 - [c126]Ryan J. Urbanowicz, Christopher Lo, John H. Holmes, Jason H. Moore:
Attribute tracking: strategies towards improved detection and characterization of complex associations. GECCO 2018: 553-560 - [c125]Patryk Orzechowski, William G. La Cava, Jason H. Moore:
Where are we now?: a large benchmark study of recent symbolic regression methods. GECCO 2018: 1183-1190 - [c124]Jason H. Moore, Randal S. Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi:
How computational thought experiments can improve our understanding of the genetic architecture of common human diseases. ALIFE 2018: 23-30 - [c123]William G. La Cava, Jason H. Moore:
Behavioral search drivers and the role of elitism in soft robotics. ALIFE 2018: 206-213 - [c122]Brett K. Beaulieu-Jones, Patryk Orzechowski, Jason H. Moore:
Mapping patient trajectories using longitudinal extraction and deep learning in the MIMIC-III Critical Care Database. PSB 2018: 123-132 - [c121]Randal S. Olson, William G. La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore:
Data-driven advice for applying machine learning to bioinformatics problems. PSB 2018: 192-203 - [c120]Jason H. Moore, Maksim Shestov, Peter Schmitt, Randal S. Olson:
A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods. PSB 2018: 259-267 - [c119]Alena Orlenko, Jason H. Moore, Patryk Orzechowski, Randal S. Olson, Junmei Cairns, Pedro J. Caraballo, Richard M. Weinshilboum, Liewei Wang, Matthew K. Breitenstein:
Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. PSB 2018: 460-471 - [c118]Yves A. Lussier, Joanne Berghout, Francesca Vitali, Kenneth S. Ramos, Maricel G. Kann, Jason H. Moore:
Session Introduction. PSB 2018: 507-511 - [c117]Elisabetta Manduchi, Alessandra Chesi, Molly A. Hall, Struan F. A. Grant, Jason H. Moore:
Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in Type 2 Diabetes GWAS. PSB 2018: 548-558 - [c116]Patryk Orzechowski, Adrian Horzyk, Janusz A. Starzyk, Jason H. Moore:
Retrieving Impressions from Semantic Memory Modeled with Associative Pulsing Neural Networks. SSCI 2018: 2060-2067 - 2017
- [c115]William G. La Cava, Jason H. Moore:
A General Feature Engineering Wrapper for Machine Learning Using \epsilon -Lexicase Survival. EuroGP 2017: 80-95 - [c114]Brian S. Cole, Jason H. Moore:
EVE: Cloud-Based Annotation of Human Genetic Variants. EvoApplications (1) 2017: 83-95 - [c113]Elizabeth R. Piette, Jason H. Moore:
Improving the Reproducibility of Genetic Association Results Using Genotype Resampling Methods. EvoApplications (1) 2017: 96-108 - [c112]William G. La Cava, Sara Silva, Leonardo Vanneschi, Lee Spector, Jason H. Moore:
Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. EvoApplications (1) 2017: 158-173 - [c111]Andrew Sohn, Randal S. Olson, Jason H. Moore:
Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming. GECCO 2017: 489-496 - [c110]William G. La Cava, Jason H. Moore:
Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods. GECCO 2017: 961-968 - [c109]Ryan J. Urbanowicz, Ben Yang, Jason H. Moore:
Problem Driven Machine Learning by Co-evolving Genetic Programming Trees and Rules in a Learning Classifier System. GPTP 2017: 55-71 - [c108]Randal S. Olson, Moshe Sipper, William G. La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, Patryk Orzechowski, Ryan J. Urbanowicz, John H. Holmes, Jason H. Moore:
A System for Accessible Artificial Intelligence. GPTP 2017: 121-134 - [c107]Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Jason H. Moore, Andrew J. Saykin, Li Shen:
Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules. ICASSP 2017: 6170-6174 - [c106]Jing Huang, Xinyuan Zhang, Jingcheng Du, Rui Duan, Liu Yang, Jason H. Moore, Yong Chen, Cui Tao:
Comparing Different Adverse Effects Among Multiple Drugs Using FAERS Data. MedInfo 2017: 1268 - [c105]Brett K. Beaulieu-Jones, Jason H. Moore, et al.:
Missing Data Imputation in the Electronic Health Record Using Deeply Learned Autoencoders. PSB 2017: 207-218 - [c104]Lana X. Garmire, Stephen V. Gliske, Quynh C. Nguyen, Jonathan H. Chen, Shamim Nemati, John D. Van Horn, Jason H. Moore, Carol Shreffler, Michelle Dunn:
The Training of Next Generation Data Scientists in Biomedicine. PSB 2017: 640-645 - [c103]Jason H. Moore, Steven F. Jennings, Casey S. Greene, Lawrence E. Hunter, Andy D. Perkins, ClarLynda R. Williams-DeVane, Donald C. Wunsch, Zhongming Zhao, Xiuzhen Huang:
No-Boundary Thinking in Bioinformatics. PSB 2017: 646-648 - 2016
- [c102]Christoph Adami, Jason H. Moore, Fred C. Dyer, Arend Hintze, Randal S. Olson:
Exploring the coevolution of predator and prey morphology and behavior. ALIFE 2016: 250-257 - [c101]Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, Jason H. Moore:
Automating Biomedical Data Science Through Tree-Based Pipeline Optimization. EvoApplications (1) 2016: 123-137 - [c100]Aaron Kershenbaum, Alicia Cutillo, Christian Darabos, Keitha A. Murray, Robert Schiaffino, Jason H. Moore:
Bicliques in Graphs with Correlated Edges: From Artificial to Biological Networks. EvoApplications (1) 2016: 138-155 - [c99]Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz, Jason H. Moore:
Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. GECCO 2016: 485-492 - [c98]Ryan J. Urbanowicz, Randal S. Olson, Jason H. Moore:
Pareto Inspired Multi-objective Rule Fitness for Adaptive Rule-based Machine Learning. GECCO (Companion) 2016: 1403 - [c97]Randal S. Olson, Jason H. Moore:
Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. GPTP 2016: 211-223 - [c96]Randal S. Olson, Jason H. Moore:
TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning. AutoML@ICML 2016: 66-74 - [c95]Ryan J. Urbanowicz, Randal S. Olson, Jason H. Moore:
Pareto Inspired Multi-objective Rule Fitness for Noise-Adaptive Rule-Based Machine Learning. PPSN 2016: 514-524 - [c94]Randal S. Olson, Jason H. Moore, Christoph Adami:
Evolution of Active Categorical Image Classification via Saccadic Eye Movement. PPSN 2016: 581-590 - [c93]Christian Darabos, Jingya Qiu, Jason H. Moore:
An Integrated Network Approach to Identifying Biological Pathways and Environmental Exposure Interactions in Complex Diseases. PSB 2016: 9-20 - 2015
- [c92]Xiaohui Yao, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Two-Dimensional Enrichment Analysis for Mining High-Level Imaging Genetic Associations. BIH 2015: 115-124 - [c91]Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics. BIH 2015: 275-284 - [c90]Christian Darabos, Jason H. Moore:
Critical properties of cellular automata with evolving network topologies. CEC 2015: 2105-2112 - [c89]Ryan J. Urbanowicz, Jason H. Moore:
Retooling Fitness for Noisy Problems in a Supervised Michigan-style Learning Classifier System. GECCO 2015: 591-598 - [c88]Ryan J. Urbanowicz, Niranjan Ramanand, Jason H. Moore:
Continuous Endpoint Data Mining with ExSTraCS: A Supervised Learning Classifier System. GECCO (Companion) 2015: 1029-1036 - [c87]Molly A. Hall, Shefali S. Verma, Dennis P. Wall, Jason H. Moore, Brendan Keating, Daniel B. Campbell, Gregory Gibson, Folkert W. Asselbergs, Sarah A. Pendergrass:
Session Introduction. Pacific Symposium on Biocomputing 2015: 156-160 - [c86]Christian Darabos, Emily D. Grussing, Maria E. Cricco, Kenzie A. Clark, Jason H. Moore:
A Bipartite Network Approach to Inferring Interactions Between Environmental Exposures and Human Diseases. Pacific Symposium on Biocomputing 2015: 171-182 - [c85]Ting Hu, Christian Darabos, Maria E. Cricco, Emily Kong, Jason H. Moore:
Genome-Wide Genetic Interaction Analysis of Glaucoma Using Expert Knowledge Derived from Human Phenotype Networks. Pacific Symposium on Biocomputing 2015: 207-218 - [c84]Kristine A. Pattin, Anna C. Greene, Russ B. Altman, Kevin Bretonnel Cohen, Elizabeth Wethington, Carsten Görg, Lawrence E. Hunter, Spencer V. Muse, Predrag Radivojac, Jason H. Moore:
Training the Next Generation of Quantitative Biologists in the Era of Big Data. Pacific Symposium on Biocomputing 2015: 488-492 - 2014
- [c83]Jason H. Moore, Casey S. Greene, Douglas P. Hill:
Identification of Novel Genetic Models of Glaucoma Using the "EMERGENT" Genetic Programming-Based Artificial Intelligence System. GPTP 2014: 17-35 - [c82]Yuanzhu Peter Chen, Xu Liu, Walter Taylor, Jason H. Moore:
Delay-tolerant networks with network coding: How well can we simulate real devices? ICC 2014: 5808-5813 - [c81]Xu Liu, Yuanzhu Chen, Cheng Li, Walter Taylor, Jason H. Moore:
Message prioritization of epidemic forwarding in delay-tolerant networks. ICNC 2014: 573-577 - [c80]Jingwen Yan, Heng Huang, Sungeun Kim, Jason H. Moore, Andrew J. Saykin, Li Shen:
Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning. ISBI 2014: 665-668 - [c79]Jinhua Sheng, Sungeun Kim, Jingwen Yan, Jason H. Moore, Andrew J. Saykin, Li Shen:
Data synthesis and method evaluation for brain imaging genetics. ISBI 2014: 1202-1205 - [c78]Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics. MICCAI (3) 2014: 329-336 - [c77]Ryan J. Urbanowicz, Gediminas Bertasius, Jason H. Moore:
An Extended Michigan-Style Learning Classifier System for Flexible Supervised Learning, Classification, and Data Mining. PPSN 2014: 211-221 - [c76]Ting Hu, Wolfgang Banzhaf, Jason H. Moore:
Population Exploration on Genotype Networks in Genetic Programming. PPSN 2014: 424-433 - [c75]Christian Darabos, Samantha H. Harmon, Jason H. Moore:
Using the Bipartite Human Phenotype Network to Reveal Pleiotropy and Epistasis Beyond the Gene. Pacific Symposium on Biocomputing 2014: 188-199 - [c74]Chao Cheng, Jason H. Moore, Casey S. Greene:
Applications of Bioinformatics to Non-Coding RNAs in the Era of Next-Generation Sequencing. Pacific Symposium on Biocomputing 2014: 412-416 - [c73]Kristine A. Pattin, Anna C. Greene, Russ B. Altman, Lawrence E. Hunter, David A. Ross, James A. Foster, Jason H. Moore:
Building the Next Generation of Quantitative Biologists. Pacific Symposium on Biocomputing 2014: 417-421 - 2013
- [c72]Dov A. Pechenick, Jason H. Moore, Joshua L. Payne:
The influence of assortativity on the robustness and evolvability of gene regulatory networks upon gene birth. ECAL 2013: 59-60 - [c71]Qinxin Pan, Ting Hu, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Bladder cancer specific pathway interaction networks. ECAL 2013: 94-101 - [c70]Jie Tan, Jason H. Moore, Ryan J. Urbanowicz:
Rapid Rule Compaction Strategies for Global Knowledge Discovery in a Supervised Learning Classifier System. ECAL 2013: 110-117 - [c69]Christian Darabos, Craig O. Mackenzie, Marco Tomassini, Mario Giacobini, Jason H. Moore:
Cellular Automata Coevolution of Update Functions and Topologies: A Tradeoff between Accuracy and Speed. ECAL 2013: 340-347 - [c68]Christian Darabos, Britney E. Graham, Ting Hu, Jason H. Moore:
Bipartite Networks Show the Genotype-to-Phenotype Relationship in Biological Systems Models: A Study of the Robustness, Evolvability, and Accessibility in Linear Cellular Automata. ECAL 2013: 348-355 - [c67]Dov A. Pechenick, Joshua L. Payne, Jason H. Moore:
An alternative route to robustness: The relationship between assortativity, in-components, and characteristic path length in gene regulatory networks. ECAL 2013: 364-371 - [c66]Ting Hu, Wolfgang Banzhaf, Jason H. Moore:
Robustness and Evolvability of Recombination in Linear Genetic Programming. EuroGP 2013: 97-108 - [c65]Delaney Granizo-MacKenzie, Jason H. Moore:
Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases. EvoBIO 2013: 1-10 - [c64]Christian Darabos, Kinjal Desai, Richard Cowper-Sallari, Mario Giacobini, Britney E. Graham, Mathieu Lupien, Jason H. Moore:
Inferring Human Phenotype Networks from Genome-Wide Genetic Associations. EvoBIO 2013: 23-34 - [c63]Qinxin Pan, Ting Hu, James D. Malley, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Supervising Random Forest Using Attribute Interaction Networks. EvoBIO 2013: 104-116 - [c62]Arvis Sulovari, Jeff Kiralis, Jason H. Moore:
Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease. EvoBIO 2013: 129-140 - [c61]Jonathan M. Fisher, Peter C. Andrews, Jeff Kiralis, Nicholas A. Sinnott-Armstrong, Jason H. Moore:
Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction. EvoBIO 2013: 200-211 - [c60]Christian Darabos, Craig O. Mackenzie, Marco Tomassini, Mario Giacobini, Jason H. Moore:
Coevolution of rules and topology in cellular automata. GECCO (Companion) 2013: 117-118 - [c59]James Rudd, Jason H. Moore, Ryan J. Urbanowicz:
A simple multi-core parallelization strategy for learning classifier system evaluation. GECCO (Companion) 2013: 1259-1266 - [c58]Christian Darabos, Britney E. Graham, Ting Hu, Jason H. Moore:
Bipartite networks to study the genotype-to-phenotype relationship in cellular automata models. GECCO (Companion) 2013: 1725-1726 - [c57]Jason H. Moore, Douglas P. Hill, Andrew J. Saykin, Li Shen:
Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease. GPTP 2013: 31-45 - [c56]Jingwen Yan, Heng Huang, Shannon L. Risacher, Sungeun Kim, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen:
Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures. MBIA 2013: 202-210 - [c55]Ting Hu, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Statistical Epistasis Networks Reduce the Computational Complexity of Searching Three-Locus Genetic Models. Pacific Symposium on Biocomputing 2013: 397-408 - 2012
- [c54]Christian Darabos, Mario Giacobini, Ting Hu, Jason H. Moore:
Lévy-Flight Genetic Programming: Towards a New Mutation Paradigm. EvoBIO 2012: 38-49 - [c53]Qinxin Pan, Christian Darabos, Jason H. Moore:
The Role of Mutations in Whole Genome Duplication. EvoBIO 2012: 122-133 - [c52]Delaney Granizo-MacKenzie, Jason H. Moore:
Artificial Immune Systems Perform Valuable Work When Detecting Epistasis in Human Genetic Datasets. EvoBIO 2012: 189-200 - [c51]Ryan J. Urbanowicz, Ambrose Granizo-Mackenzie, Jason H. Moore:
Instance-linked attribute tracking and feedback for michigan-style supervised learning classifier systems. GECCO 2012: 927-934 - [c50]Ryan J. Urbanowicz, Delaney Granizo-MacKenzie, Jason H. Moore:
Using Expert Knowledge to Guide Covering and Mutation in a Michigan Style Learning Classifier System to Detect Epistasis and Heterogeneity. PPSN (1) 2012: 266-275 - [c49]James A. Foster, Jason H. Moore, Jack A. Gilbert, John Bunge:
Session introduction. Pacific Symposium on Biocomputing 2012: 200-202 - 2011
- [c48]Jonathan M. Fisher, Jason H. Moore:
Distinguishing the effects of epistasis and pleiotropy using a variant of the NK model. ECAL 2011: 234-241 - [c47]Qinxin Pan, Christian Darabos, Anna L. Tyler, Jason H. Moore, Joshua L. Payne:
The influence of whole genome duplication and subsequent diversification on environmental robustness and evolutionary innovation in gene regulatory networks. ECAL 2011: 614-621 - [c46]Joshua L. Payne, Jason H. Moore:
Robustness, evolvability, and accessibility in the signal-integration space of gene regulatory circuits. ECAL 2011: 638-645 - [c45]Ting Hu, Joshua L. Payne, Wolfgang Banzhaf, Jason H. Moore:
Robustness, Evolvability, and Accessibility in Linear Genetic Programming. EuroGP 2011: 13-24 - [c44]Christian Darabos, Ferdinando Di Cunto, Marco Tomassini, Jason H. Moore, Paolo Provero, Mario Giacobini:
Validating a Threshold-Based Boolean Model of Regulatory Networks on a Biological Organism. EvoBio 2011: 59-68 - [c43]Ryan J. Urbanowicz, Nicholas A. Sinnott-Armstrong, Jason H. Moore:
Random artificial incorporation of noise in a learning classifier system environment. GECCO (Companion) 2011: 369-374 - [c42]James A. Foster, Jason H. Moore:
Session Introduction. Pacific Symposium on Biocomputing 2011: 118-120 - [c41]Jason H. Moore, Richard Cowper-Sallari, Douglas P. Hill, Patricia Hibberd, Juliette Madan:
Human Microbiome Visualization Using 3d Technology. Pacific Symposium on Biocomputing 2011: 154-164 - 2010
- [c40]Joshua L. Payne, Jason H. Moore:
Sexual Recombination in Self-Organizing Interaction Networks. EvoApplications (1) 2010: 41-50 - [c39]Casey S. Greene, Daniel S. Himmelstein, Jason H. Moore:
A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships. EvoBIO 2010: 74-85 - [c38]Casey S. Greene, Daniel S. Himmelstein, Jeff Kiralis, Jason H. Moore:
The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics. EvoBIO 2010: 182-193 - [c37]Nadia M. Penrod, Casey S. Greene, Delaney Granizo-MacKenzie, Jason H. Moore:
Artificial Immune Systems for Epistasis Analysis in Human Genetics. EvoBIO 2010: 194-204 - [c36]Ryan J. Urbanowicz, Jason H. Moore:
The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies. GECCO 2010: 195-202 - [c35]Nicholas A. Sinnott-Armstrong, Casey S. Greene, Jason H. Moore:
Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units. GECCO 2010: 215-216 - [c34]Jason H. Moore:
Bioinformatics. GECCO (Companion) 2010: 2503-2534 - [c33]Ryan J. Urbanowicz, Jason H. Moore:
The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies. PPSN (1) 2010: 404-413 - [c32]Kristine A. Pattin, Jiang Gui, Jason H. Moore:
Employing Publically Available Biological Expert Knowledge from Protein-Protein Interaction Information. PRIB 2010: 395-406 - [c31]Casey S. Greene, Daniel S. Himmelstein, Heather H. Nelson, Karl T. Kelsey, Scott M. Williams, Angeline S. Andrew, Margaret R. Karagas, Jason H. Moore:
Enabling Personal Genomics with an Explicit Test of Epistasis. Pacific Symposium on Biocomputing 2010: 327-336 - 2009
- [c30]Casey S. Greene, Jeff Kiralis, Jason H. Moore:
Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches. IEEE Congress on Evolutionary Computation 2009: 800-807 - [c29]Casey S. Greene, Bill C. White, Jason H. Moore:
Sensible initialization using expert knowledge for genome-wide analysis of epistasis using genetic programming. IEEE Congress on Evolutionary Computation 2009: 1289-1296 - [c28]Anna L. Tyler, Bill C. White, Casey S. Greene, Paul C. Andrews, Richard Cowper-Sallari, Jason H. Moore:
Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture. IEEE Congress on Evolutionary Computation 2009: 2907-2912 - [c27]Jason M. Gilmore, Casey S. Greene, Peter C. Andrews, Jeff Kiralis, Jason H. Moore:
An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing. ECAL (2) 2009: 286-293 - [c26]Casey S. Greene, Douglas P. Hill, Jason H. Moore:
An Open-Ended Computational Evolution Strategy for Evolving Parsimonious Solutions to Human Genetics Problems. ECAL (1) 2009: 313-320 - [c25]Casey S. Greene, Jason M. Gilmore, Jeff Kiralis, Peter C. Andrews, Jason H. Moore:
Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease. EvoBIO 2009: 92-103 - [c24]Casey S. Greene, Douglas P. Hill, Jason H. Moore:
Environmental noise improves epistasis models of genetic data discovered using a computational evolution system. GECCO 2009: 1785-1786 - 2008
- [c23]Casey S. Greene, Bill C. White, Jason H. Moore:
Ant Colony Optimization for Genome-Wide Genetic Analysis. ANTS Conference 2008: 37-47 - [c22]Jason H. Moore, Peter C. Andrews, Nate Barney, Bill C. White:
Development and Evaluation of an Open-Ended Computational Evolution System for the Genetic Analysis of Susceptibility to Common Human Diseases. EvoBIO 2008: 129-140 - [c21]Ryan J. Urbanowicz, Nate Barney, Bill C. White, Jason H. Moore:
Mask functions for the symbolic modeling of epistasis using genetic programming. GECCO 2008: 339-346 - [c20]Casey S. Greene, Bill C. White, Jason H. Moore:
Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming. GECCO 2008: 351-352 - 2007
- [c19]Jason H. Moore, Bill C. White:
Tuning ReliefF for Genome-Wide Genetic Analysis. EvoBIO 2007: 166-175 - [c18]Jason H. Moore, Nate Barney, Bill C. White:
Towards human-human-computer interaction for biologically-inspired problem-solving in human genetics. GECCO 2007: 432-433 - [c17]Jason H. Moore:
Bioinformatics. GECCO (Companion) 2007: 3435-3457 - [c16]Casey S. Greene, Bill C. White, Jason H. Moore:
An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming. PRIB 2007: 30-40 - 2006
- [c15]David M. Reif, Alison A. Motsinger, Brett A. McKinney, James E. Crowe Jr., Jason H. Moore:
Feature Selection using a Random Forests Classifier for the Integrated Analysis of Multiple Data Types. CIBCB 2006: 1-8 - [c14]Jason H. Moore, Bill C. White:
Exploiting Expert Knowledge in Genetic Programming for Genome-Wide Genetic Analysis. PPSN 2006: 969-977 - 2005
- [c13]Bill C. White, David M. Reif, Joshua C. Gilbert, Jason H. Moore:
A statistical comparison of grammatical evolution strategies in the domain of human genetics. Congress on Evolutionary Computation 2005: 491-497 - [c12]Bill C. White, David M. Reif, Joshua C. Gilbert, Jason H. Moore:
A statistical comparison of grammatical evolution strategies in the domain of human genetics. Congress on Evolutionary Computation 2005: 676-682 - [c11]David M. Reif, Scott M. Dudek, Christian M. Shaffer, Janey Wang, Jason H. Moore:
Exploratory Visual Analysis of Pharmacogenomic Results. Pacific Symposium on Biocomputing 2005 - 2004
- [c10]Jason H. Moore, Lance W. Hahn:
An Improved Grammatical Evolution Strategy for Hierarchical Petri Net Modeling of Complex Genetic Systems. EvoWorkshops 2004: 63-72 - [c9]Jason H. Moore, Lance W. Hahn:
Systems Biology Modeling in Human Genetics Using Petri Nets and Grammatical Evolution. GECCO (1) 2004: 392-401 - [c8]Marylyn D. Ritchie, Christopher S. Coffey, Jason H. Moore:
Genetic Programming Neural Networks as a Bioinformatics Tool for Human Genetics. GECCO (1) 2004: 438-448 - 2003
- [c7]Jason H. Moore:
Cross Validation Consistency for the Assessment of Genetic Programming Results in Microarray Studies. EvoWorkshops 2003: 99-106 - [c6]David M. Reif, Bill C. White, Nancy Olsen, Thomas M. Aune, Jason H. Moore:
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data. GECCO 2003: 2277-2287 - [c5]Jason H. Moore, Lance W. Hahn:
Grammatical Evolution for the Discovery of Petri Net Models of Complex Genetic Systems. GECCO 2003: 2412-2413 - 2002
- [c4]Jason H. Moore, Lance W. Hahn, Marylyn D. Ritchie, Tricia A. Thornton, Bill C. White:
Application Of Genetic Algorithms To The Discovery Of Complex Models For Simulation Studies In Human Genetics. GECCO 2002: 1150-1155 - [c3]Jason H. Moore, Lance W. Hahn:
Cellular Automata and Genetic Algorithms for Parallel Problem Solving in Human Genetics. PPSN 2002: 821-830 - [c2]Jason H. Moore, Lance W. Hahn:
A Cellular Automata Approach to Detecting Interactions Among Single-nucleotide Polymorphisms in Complex Multifactorial Diseases. Pacific Symposium on Biocomputing 2002: 53-64 - 2001
- [c1]Jason H. Moore, Joel S. Parker, Lance W. Hahn:
Symbolic Discriminant Analysis for Mining Gene Expression Patterns. ECML 2001: 372-381
Parts in Books or Collections
- 2019
- [p5]Randal S. Olson, Jason H. Moore:
TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning. Automated Machine Learning 2019: 151-160 - 2018
- [p4]Jason H. Moore, Moshe Sipper:
Grammatical Evolution Strategies for Bioinformatics and Systems Genomics. Handbook of Grammatical Evolution 2018: 395-405 - 2014
- [p3]Christian Darabos, Mario Giacobini, Jason H. Moore, Marco Tomassini:
Models of Gene Regulation: Integrating Modern Knowledge into the Random Boolean Network Framework. Evolution, Complexity and Artificial Life 2014: 43-57 - 2011
- [p2]Kristine A. Pattin, Jason H. Moore:
Addressing the Challenges of Detecting Epistasis in Genome-Wide Association Studies of Common Human Diseases Using Biological Expert Knowledge. Handbook of Research on Computational and Systems Biology 2011: 128-147 - 2010
- [p1]Casey S. Greene, Jason H. Moore:
Solving Complex Problems in Human Genetics using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific Knowledge. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery 2010: 166-180
Editorship
- 2014
- [e6]Rick L. Riolo, Jason H. Moore, Mark E. Kotanchek:
Genetic Programming Theory and Practice XI [GPTP 2013, University of Michigan, Ann Arbor, USA, May 9-11, 2013]. Springer 2014, ISBN 978-1-4939-0374-0 [contents] - 2012
- [e5]Terence Soule, Jason H. Moore:
Genetic and Evolutionary Computation Conference, GECCO '12, Philadelphia, PA, USA, July 7-11, 2012. ACM 2012, ISBN 978-1-4503-1177-9 [contents] - [e4]Terence Soule, Jason H. Moore:
Genetic and Evolutionary Computation Conference, GECCO '12, Philadelphia, PA, USA, July 7-11, 2012, Companion Material Proceedings. ACM 2012, ISBN 978-1-4503-1178-6 [contents] - 2008
- [e3]Elena Marchiori, Jason H. Moore:
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, 6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008. Proceedings. Lecture Notes in Computer Science 4973, Springer 2008, ISBN 978-3-540-78756-3 [contents] - 2007
- [e2]Elena Marchiori, Jason H. Moore, Jagath C. Rajapakse:
Evolutionary Computation,Machine Learning and Data Mining in Bioinformatics, 5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007, Proceedings. Lecture Notes in Computer Science 4447, Springer 2007, ISBN 978-3-540-71782-9 [contents] - 2006
- [e1]Franz Rothlauf, Jürgen Branke, Stefano Cagnoni, Ernesto Costa, Carlos Cotta, Rolf Drechsler, Evelyne Lutton, Penousal Machado, Jason H. Moore, Juan Romero, George D. Smith, Giovanni Squillero, Hideyuki Takagi:
Applications of Evolutionary Computing, EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Budapest, Hungary, April 10-12, 2006, Proceedings. Lecture Notes in Computer Science 3907, Springer 2006, ISBN 3-540-33237-5 [contents]
Reference Works
- 2019
- [r1]Molly A. Hall, Brian S. Cole, Jason H. Moore:
Gene-Gene Interactions: An Essential Component to Modeling Complexity for Precision Medicine. Encyclopedia of Bioinformatics and Computational Biology (2) 2019: 171-177
Informal and Other Publications
- 2024
- [i43]Yu-Ning Huang, Michael I. Love, Cynthia Flaire Ronkowski, Dhrithi Deshpande, Lynn M. Schriml, Annie Wong-Beringer, Barend Mons, Russell Corbett-Detig, Christopher I Hunter, Jason H. Moore, Lana X. Garmire, T. B. K. Reddy, Winston A. Hide, Atul J. Butte, Mark D. Robinson, Serghei Mangul:
Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies. CoRR abs/2401.02965 (2024) - [i42]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
New Pathways in Coevolutionary Computation. CoRR abs/2401.10515 (2024) - [i41]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Coevolving Artistic Images Using OMNIREP. CoRR abs/2401.11167 (2024) - [i40]Moshe Sipper, Jason H. Moore:
Genetic Programming Theory and Practice: A Fifteen-Year Trajectory. CoRR abs/2402.00425 (2024) - 2023
- [i39]Nicholas Matsumoto, Anil Kumar Saini, Pedro Henrique Ribeiro, Hyunjun Choi, Alena Orlenko, Leo-Pekka Lyytikäinen, Jari O. Laurikka, Terho Lehtimäki, Sandra Batista, Jason H. Moore:
Faster Convergence with Lexicase Selection in Tree-based Automated Machine Learning. CoRR abs/2302.00731 (2023) - 2022
- [i38]Moshe Sipper, Jason H. Moore:
Symbolic-Regression Boosting. CoRR abs/2206.12082 (2022) - [i37]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions. CoRR abs/2206.12707 (2022) - [i36]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems. CoRR abs/2206.13509 (2022) - [i35]Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Automatically Balancing Model Accuracy and Complexity using Solution and Fitness Evolution (SAFE). CoRR abs/2206.15409 (2022) - [i34]Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki, Aleksander Byrski, Leszek Rutkowski, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems. CoRR abs/2210.13205 (2022) - [i33]Pedro Henrique Ribeiro, Patryk Orzechowski, Joost Wagenaar, Jason H. Moore:
Benchmarking AutoML algorithms on a collection of synthetic classification problems. CoRR abs/2212.02704 (2022) - 2021
- [i32]Pawel Renc, Patryk Orzechowski, Aleksander Byrski, Jaroslaw Was, Jason H. Moore:
EBIC.JL - an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia. CoRR abs/2105.01196 (2021) - [i31]Patryk Orzechowski, Jason H. Moore:
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers. CoRR abs/2107.06475 (2021) - [i30]Roland Albert A. Romero, Mariefel Nicole Y. Deypalan, Suchit Mehrotra, John Titus Jungao, Natalie E. Sheils, Elisabetta Manduchi, Jason H. Moore:
Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims. CoRR abs/2107.10495 (2021) - [i29]William G. La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabrício Olivetti de França, Marco Virgolin, Ying Jin, Michael Kommenda, Jason H. Moore:
Contemporary Symbolic Regression Methods and their Relative Performance. CoRR abs/2107.14351 (2021) - 2020
- [i28]Stefano Ruberto, Valerio Terragni, Jason H. Moore:
SGP-DT: Semantic Genetic Programming Based on Dynamic Targets. CoRR abs/2001.11535 (2020) - [i27]William G. La Cava, Jason H. Moore:
Genetic programming approaches to learning fair classifiers. CoRR abs/2004.13282 (2020) - [i26]Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore:
Is deep learning necessary for simple classification tasks? CoRR abs/2006.06730 (2020) - [i25]Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise:
Benchmarking in Optimization: Best Practice and Open Issues. CoRR abs/2007.03488 (2020) - [i24]Ryan J. Urbanowicz, Pranshu Suri, Yuhan Cui, Jason H. Moore, Karen Ruth, Rachael Stolzenberg-Solomon, Shannon M. Lynch:
A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments. CoRR abs/2008.12829 (2020) - [i23]Trang T. Le, William G. La Cava, Joseph D. Romano, John T. Gregg, Daniel J. Goldberg, Praneel Chakraborty, Natasha L. Ray, Daniel S. Himmelstein, Weixuan Fu, Jason H. Moore:
PMLB v1.0: an open source dataset collection for benchmarking machine learning methods. CoRR abs/2012.00058 (2020) - 2019
- [i22]William G. La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass:
Interpretation of machine learning predictions for patient outcomes in electronic health records. CoRR abs/1903.12074 (2019) - [i21]William G. La Cava, Jason H. Moore:
Semantic variation operators for multidimensional genetic programming. CoRR abs/1904.08577 (2019) - [i20]William G. La Cava, Heather Williams, Weixuan Fu, Jason H. Moore:
Evaluating recommender systems for AI-driven data science. CoRR abs/1905.09205 (2019) - 2018
- [i19]Patryk Orzechowski, Moshe Sipper, Xiuzhen Huang, Jason H. Moore:
EBIC: an artificial intelligence-based parallel biclustering algorithm for pattern discovery. CoRR abs/1801.03039 (2018) - [i18]Patryk Orzechowski, William G. La Cava, Jason H. Moore:
Where are we now? A large benchmark study of recent symbolic regression methods. CoRR abs/1804.09331 (2018) - [i17]Moshe Sipper, Jason H. Moore:
Gamorithm. CoRR abs/1806.02717 (2018) - [i16]William G. La Cava, Tilak Raj Singh, James Taggart, Srinivas Suri, Jason H. Moore:
Stochastic optimization approaches to learning concise representations. CoRR abs/1807.00981 (2018) - [i15]Patryk Orzechowski, Jason H. Moore:
EBIC: an open source software for high-dimensional and big data biclustering analyses. CoRR abs/1807.09932 (2018) - 2017
- [i14]Andrew Sohn, Randal S. Olson, Jason H. Moore:
Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming. CoRR abs/1702.01780 (2017) - [i13]Randal S. Olson, William G. La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore:
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison. CoRR abs/1703.00512 (2017) - [i12]William G. La Cava, Jason H. Moore:
Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods. CoRR abs/1703.06934 (2017) - [i11]Randal S. Olson, Moshe Sipper, William G. La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, John H. Holmes, Jason H. Moore:
A System for Accessible Artificial Intelligence. CoRR abs/1705.00594 (2017) - [i10]Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H. Moore:
From MEGATON to RASCAL: Surfing the Parameter Space of Evolutionary Algorithms. CoRR abs/1706.04119 (2017) - [i9]Randal S. Olson, William G. La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore:
Data-driven Advice for Applying Machine Learning to Bioinformatics Problems. CoRR abs/1708.05070 (2017) - [i8]William G. La Cava, Thomas Helmuth, Lee Spector, Jason H. Moore:
$ε$-Lexicase selection: a probabilistic and multi-objective analysis of lexicase selection in continuous domains. CoRR abs/1709.05394 (2017) - [i7]Ryan J. Urbanowicz, Melissa Meeker, William G. La Cava, Randal S. Olson, Jason H. Moore:
Relief-Based Feature Selection: Introduction and Review. CoRR abs/1711.08421 (2017) - [i6]Ryan J. Urbanowicz, Randal S. Olson, Peter Schmitt, Melissa Meeker, Jason H. Moore:
Benchmarking Relief-Based Feature Selection Methods. CoRR abs/1711.08477 (2017) - 2016
- [i5]Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, Jason H. Moore:
Automating biomedical data science through tree-based pipeline optimization. CoRR abs/1601.07925 (2016) - [i4]Randal S. Olson, Arend Hintze, Fred C. Dyer, Jason H. Moore, Christoph Adami:
Exploring the coevolution of predator and prey morphology and behavior. CoRR abs/1602.08802 (2016) - [i3]Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz, Jason H. Moore:
Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. CoRR abs/1603.06212 (2016) - [i2]Randal S. Olson, Jason H. Moore, Christoph Adami:
Evolution of active categorical image classification via saccadic eye movement. CoRR abs/1603.08233 (2016) - [i1]Randal S. Olson, Jason H. Moore:
Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. CoRR abs/1607.08878 (2016)
Coauthor Index
[j166] [j157] [j135] [j116] [j105] [j103] [j98] [j97] [j86] [j60] [j53] [j34] [j33] [j28] [j27] [j26] [c154] [c144] [c143] [c137] [c135] [c126] [c109] [c108] [c101] [c99] [c98] [c95] [c89] [c88] [c77] [c70] [c59] [c51] [c50] [c43] [c36] [c33] [c21] [i42] [i41] [i37] [i36] [i35] [i24] [i13] [i7] [i6] [i5] [i3]
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