Detection of linear and nonlinear dependencies in time series using the method of surrogate data in S-PLUS. - Jason H. Moore (Comput. Methods Programs Biomed., 2000)

Symbolic Discriminant Analysis for Mining Gene Expression Patterns. - Jason H. Moore; Joel S. Parker; Lance W. Hahn (ECML, 2001)

Application Of Genetic Algorithms To The Discovery Of Complex Models For Simulation Studies In Human Genetics. - Jason H. Moore; Lance W. Hahn; Marylyn D. Ritchie; Tricia A. Thornton; Bill C. White (GECCO, 2002)

Cellular Automata and Genetic Algorithms for Parallel Problem Solving in Human Genetics. - Jason H. Moore; Lance W. Hahn (PPSN, 2002)

A Cellular Automata Approach to Detecting Interactions Among Single-nucleotide Polymorphisms in Complex Multifactorial Diseases. - Jason H. Moore; Lance W. Hahn (Pacific Symposium on Biocomputing, 2002)

Cross Validation Consistency for the Assessment of Genetic Programming Results in Microarray Studies. - Jason H. Moore (EvoWorkshops, 2003)

Grammatical Evolution for the Discovery of Petri Net Models of Complex Genetic Systems. - Jason H. Moore; Lance W. Hahn (GECCO, 2003)

Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data. - David M. Reif; Bill C. White; Nancy Olsen; Thomas M. Aune; Jason H. Moore (GECCO, 2003)

Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. - Lance W. Hahn; Marylyn D. Ritchie; Jason H. Moore (Bioinform., 2003)

Optimizationof neural network architecture using genetic programming improvesdetection and modeling of gene-gene interactions in studies of humandiseases. - Marylyn D. Ritchie; Bill C. White; Joel S. Parker; Lance W. Hahn; Jason H. Moore (BMC Bioinform., 2003)

An Improved Grammatical Evolution Strategy for Hierarchical Petri Net Modeling of Complex Genetic Systems. - Jason H. Moore; Lance W. Hahn (EvoWorkshops, 2004)

Systems Biology Modeling in Human Genetics Using Petri Nets and Grammatical Evolution. - Jason H. Moore; Lance W. Hahn (GECCO (1), 2004)

Genetic Programming Neural Networks as a Bioinformatics Tool for Human Genetics. - Marylyn D. Ritchie; Christopher S. Coffey; Jason H. Moore (GECCO (1), 2004)

Routine discovery of complex genetic models using genetic algorithms. - Jason H. Moore; Lance W. Hahn; Marylyn D. Ritchie; Tricia A. Thornton; Bill C. White (Appl. Soft Comput., 2004)

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. - 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 (BMC Bioinform., 2004)

Ideal discrimination of discrete clinical endpoints using multilocus genotypes. - Lance W. Hahn; Jason H. Moore (Silico Biol., 2004)

A statistical comparison of grammatical evolution strategies in the domain of human genetics. - Bill C. White; David M. Reif; Joshua C. Gilbert; Jason H. Moore (Congress on Evolutionary Computation, 2005)

Exploratory Visual Analysis of Pharmacogenomic Results. - David M. Reif; Scott M. Dudek; Christian M. Shaffer; Janey Wang; Jason H. Moore (Pacific Symposium on Biocomputing, 2005)

Feature Selection using a Random Forests Classifier for the Integrated Analysis of Multiple Data Types. - David M. Reif; Alison A. Motsinger; Brett A. McKinney; James E. Crowe Jr.; Jason H. Moore (CIBCB, 2006)

Exploiting Expert Knowledge in Genetic Programming for Genome-Wide Genetic Analysis. - Jason H. Moore; Bill C. White (PPSN, 2006)

Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data. - Tricia A. Thornton-Wells; Jason H. Moore; Jonathan L. Haines (BMC Bioinform., 2006)

Tuning ReliefF for Genome-Wide Genetic Analysis. - Jason H. Moore; Bill C. White (EvoBIO, 2007)

Towards human-human-computer interaction for biologically-inspired problem-solving in human genetics. - Jason H. Moore; Nate Barney; Bill C. White (GECCO, 2007)

An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming. - Casey S. Greene; Bill C. White; Jason H. Moore (PRIB, 2007)

Genetic programming neural networks: A powerful bioinformatics tool for human genetics. - Marylyn D. Ritchie; Alison A. Motsinger; William S. Bush; Christopher S. Coffey; Jason H. Moore (Appl. Soft Comput., 2007)

Evaporative cooling feature selection for genotypic data involving interactions. - Brett A. McKinney; David M. Reif; Bill C. White; James E. Crowe Jr.; Jason H. Moore (Bioinform., 2007)

Genomic mining for complex disease traits with "random chemistry". - Margaret J. Eppstein; Joshua L. Payne; Bill C. White; Jason H. Moore (Genet. Program. Evolvable Mach., 2007)

Ant Colony Optimization for Genome-Wide Genetic Analysis. - Casey S. Greene; Bill C. White; Jason H. Moore (ANTS Conference, 2008)

Development and Evaluation of an Open-Ended Computational Evolution System for the Genetic Analysis of Susceptibility to Common Human Diseases. - Jason H. Moore; Peter C. Andrews; Nate Barney; Bill C. White (EvoBIO, 2008)

Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming. - Casey S. Greene; Bill C. White; Jason H. Moore (GECCO, 2008)

Mask functions for the symbolic modeling of epistasis using genetic programming. - Ryan J. Urbanowicz; Nate Barney; Bill C. White; Jason H. Moore (GECCO, 2008)

Filling the gap between biology and computer science. - Jesús S. Aguilar-Ruiz; Jason H. Moore; Marylyn D. Ritchie (BioData Min., 2008)

Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches. - Casey S. Greene; Jeff Kiralis; Jason H. Moore (IEEE Congress on Evolutionary Computation, 2009)

Sensible initialization using expert knowledge for genome-wide analysis of epistasis using genetic programming. - Casey S. Greene; Bill C. White; Jason H. Moore (IEEE Congress on Evolutionary Computation, 2009)

Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture. - Anna L. Tyler; Bill C. White; Casey S. Greene; Paul C. Andrews; Richard Cowper-Sallari; Jason H. Moore (IEEE Congress on Evolutionary Computation, 2009)

An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing. - Jason M. Gilmore; Casey S. Greene; Peter C. Andrews; Jeff Kiralis; Jason H. Moore (ECAL (2), 2009)

An Open-Ended Computational Evolution Strategy for Evolving Parsimonious Solutions to Human Genetics Problems. - Casey S. Greene; Douglas P. Hill; Jason H. Moore (ECAL (1), 2009)

Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease. - Casey S. Greene; Jason M. Gilmore; Jeff Kiralis; Peter C. Andrews; Jason H. Moore (EvoBIO, 2009)

Environmental noise improves epistasis models of genetic data discovered using a computational evolution system. - Casey S. Greene; Douglas P. Hill; Jason H. Moore (GECCO, 2009)

Multifactor dimensionality reduction analysis identifies specific nucleotide patterns promoting genetic polymorphisms. - Eric Arehart; Scott Gleim; Bill C. White; John Hwa; Jason H. Moore (BioData Min., 2009)

Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions. - Casey S. Greene; Nadia M. Penrod; Jeff Kiralis; Jason H. Moore (BioData Min., 2009)

Solving Complex Problems in Human Genetics using Nature-Inspired Algorithms Requires Strategies which Exploit Domain-Specific Knowledge. - Casey S. Greene; Jason H. Moore (Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery, 2010)

The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics. - Casey S. Greene; Daniel S. Himmelstein; Jeff Kiralis; Jason H. Moore (EvoBIO, 2010)

A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships. - Casey S. Greene; Daniel S. Himmelstein; Jason H. Moore (EvoBIO, 2010)

Sexual Recombination in Self-Organizing Interaction Networks. - Joshua L. Payne; Jason H. Moore (EvoApplications (1), 2010)

Artificial Immune Systems for Epistasis Analysis in Human Genetics. - Nadia M. Penrod; Casey S. Greene; Delaney Granizo-MacKenzie; Jason H. Moore (EvoBIO, 2010)

Bioinformatics. - Jason H. Moore (GECCO (Companion), 2010)

Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units. - Nicholas A. Sinnott-Armstrong; Casey S. Greene; Jason H. Moore (GECCO, 2010)

The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies. - Ryan J. Urbanowicz; Jason H. Moore (GECCO, 2010)

The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies. - Ryan J. Urbanowicz; Jason H. Moore (PPSN (1), 2010)

Employing Publically Available Biological Expert Knowledge from Protein-Protein Interaction Information. - Kristine A. Pattin; Jiang Gui; Jason H. Moore (PRIB, 2010)

Enabling Personal Genomics with an Explicit Test of Epistasis. - Casey S. Greene; Daniel S. Himmelstein; Heather H. Nelson; Karl T. Kelsey; Scott M. Williams; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (Pacific Symposium on Biocomputing, 2010)

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS. - Casey S. Greene; Nicholas A. Sinnott-Armstrong; Daniel S. Himmelstein; Paul J. Park; Jason H. Moore; Brent T. Harris (Bioinform., 2010)

Bioinformatics challenges for genome-wide association studies. - Jason H. Moore; Folkert W. Asselbergs; Scott M. Williams (Bioinform., 2010)

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 001; 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; et al. (NeuroImage, 2010)

Addressing the Challenges of Detecting Epistasis in Genome-Wide Association Studies of Common Human Diseases Using Biological Expert Knowledge. - Kristine A. Pattin; Jason H. Moore (Handbook of Research on Computational and Systems Biology, 2011)

Distinguishing the effects of epistasis and pleiotropy using a variant of the NK model. - Jonathan M. Fisher; Jason H. Moore (ECAL, 2011)

The influence of whole genome duplication and subsequent diversification on environmental robustness and evolutionary innovation in gene regulatory networks. - Qinxin Pan; Christian Darabos; Anna L. Tyler; Jason H. Moore; Joshua L. Payne (ECAL, 2011)

Robustness, evolvability, and accessibility in the signal-integration space of gene regulatory circuits. - Joshua L. Payne; Jason H. Moore (ECAL, 2011)

Robustness, Evolvability, and Accessibility in Linear Genetic Programming. - Ting Hu 001; Joshua L. Payne; Wolfgang Banzhaf; Jason H. Moore (EuroGP, 2011)

Validating a Threshold-Based Boolean Model of Regulatory Networks on a Biological Organism. - Christian Darabos; Ferdinando Di Cunto; Marco Tomassini; Jason H. Moore; Paolo Provero; Mario Giacobini (EvoBio, 2011)

Random artificial incorporation of noise in a learning classifier system environment. - Ryan J. Urbanowicz; Nicholas A. Sinnott-Armstrong; Jason H. Moore (GECCO (Companion), 2011)

Session Introduction. - James A. Foster; Jason H. Moore (Pacific Symposium on Biocomputing, 2011)

Human Microbiome Visualization Using 3d Technology. - Jason H. Moore; Richard Cowper-Sallari; Douglas P. Hill; Patricia Hibberd; Juliette Madan (Pacific Symposium on Biocomputing, 2011)

Evolving hard problems: Generating human genetics datasets with a complex etiology. - Daniel S. Himmelstein; Casey S. Greene; Jason H. Moore (BioData Min., 2011)

The spatial dimension in biological data mining. - Davnah Urbach; Jason H. Moore (BioData Min., 2011)

Data mining and the evolution of biological complexity. - Davnah Urbach; Jason H. Moore (BioData Min., 2011)

Mining beyond the exome. - Davnah Urbach; Jason H. Moore (BioData Min., 2011)

Mining the diseasome. - Davnah Urbach; Jason H. Moore (BioData Min., 2011)

Characterizing Genetic Interactions in Human Disease Association Studies Using Statistical Epistasis Networks. - Ting Hu 001; Nicholas A. Sinnott-Armstrong; Jeff Kiralis; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (BMC Bioinform., 2011)

Toward robust network based complex systems: from evolutionary cellular automata to biological models. - Christian Darabos; Marco Tomassini; Ferdinando Di Cunto; Paolo Provero; Jason H. Moore; Mario Giacobini (Intelligenza Artificiale, 2011)

Lévy-Flight Genetic Programming: Towards a New Mutation Paradigm. - Christian Darabos; Mario Giacobini; Ting Hu 001; Jason H. Moore (EvoBIO, 2012)

Artificial Immune Systems Perform Valuable Work When Detecting Epistasis in Human Genetic Datasets. - Delaney Granizo-MacKenzie; Jason H. Moore (EvoBIO, 2012)

The Role of Mutations in Whole Genome Duplication. - Qinxin Pan; Christian Darabos; Jason H. Moore (EvoBIO, 2012)

Instance-linked attribute tracking and feedback for michigan-style supervised learning classifier systems. - Ryan J. Urbanowicz; Ambrose Granizo-Mackenzie; Jason H. Moore (GECCO, 2012)

Using Expert Knowledge to Guide Covering and Mutation in a Michigan Style Learning Classifier System to Detect Epistasis and Heterogeneity. - Ryan J. Urbanowicz; Delaney Granizo-MacKenzie; Jason H. Moore (PPSN (1), 2012)

Session introduction. - James A. Foster; Jason H. Moore; Jack A. Gilbert; John Bunge (Pacific Symposium on Biocomputing, 2012)

Measuring the microbiome: perspectives on advances in DNA-based techniques for exploring microbial life. - James A. Foster; John Bunge; Jack A. Gilbert; Jason H. Moore (Briefings Bioinform., 2012)

Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS. - 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 (BioData Min., 2012)

Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection. - Ryan J. Urbanowicz; Jeff Kiralis; Jonathan M. Fisher; Jason H. Moore (BioData Min., 2012)

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures. - Ryan J. Urbanowicz; Jeff Kiralis; Nicholas A. Sinnott-Armstrong; Tamra Heberling; Jonathan M. Fisher; Jason H. Moore (BioData Min., 2012)

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems. - Ryan J. Urbanowicz; Ambrose Granizo-Mackenzie; Jason H. Moore (IEEE Comput. Intell. Mag., 2012)

Evolutionary dynamics on multiple scales: a quantitative analysis of the interplay between genotype, phenotype, and fitness in linear genetic programming. - Ting Hu 001; Joshua L. Payne; Wolfgang Banzhaf; Jason H. Moore (Genet. Program. Evolvable Mach., 2012)

Chapter 11: Genome-Wide Association Studies. - William S. Bush; Jason H. Moore (PLoS Comput. Biol., 2012)

Bipartite Networks Show the Genotype-to-Phenotype Relationship in Biological Systems Models: A Study of the Robustness, Evolvability, and Accessibility in Linear Cellular Automata. - Christian Darabos; Britney E. Graham; Ting Hu 001; Jason H. Moore (ECAL, 2013)

Cellular Automata Coevolution of Update Functions and Topologies: A Tradeoff between Accuracy and Speed. - Christian Darabos; Craig O. Mackenzie; Marco Tomassini; Mario Giacobini; Jason H. Moore (ECAL, 2013)

Bladder cancer specific pathway interaction networks. - Qinxin Pan; Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (ECAL, 2013)

The influence of assortativity on the robustness and evolvability of gene regulatory networks upon gene birth. - Dov A. Pechenick; Jason H. Moore; Joshua L. Payne (ECAL, 2013)

An alternative route to robustness: The relationship between assortativity, in-components, and characteristic path length in gene regulatory networks. - Dov A. Pechenick; Joshua L. Payne; Jason H. Moore (ECAL, 2013)

Rapid Rule Compaction Strategies for Global Knowledge Discovery in a Supervised Learning Classifier System. - Jie Tan; Jason H. Moore; Ryan J. Urbanowicz (ECAL, 2013)

Robustness and Evolvability of Recombination in Linear Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (EuroGP, 2013)

Inferring Human Phenotype Networks from Genome-Wide Genetic Associations. - Christian Darabos; Kinjal Desai; Richard Cowper-Sallari; Mario Giacobini; Britney E. Graham; Mathieu Lupien; Jason H. Moore (EvoBIO, 2013)

Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction. - Jonathan M. Fisher; Peter C. Andrews; Jeff Kiralis; Nicholas A. Sinnott-Armstrong; Jason H. Moore (EvoBIO, 2013)

Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases. - Delaney Granizo-MacKenzie; Jason H. Moore (EvoBIO, 2013)

Supervising Random Forest Using Attribute Interaction Networks. - Qinxin Pan; Ting Hu 001; James D. Malley; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (EvoBIO, 2013)

Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease. - Arvis Sulovari; Jeff Kiralis; Jason H. Moore (EvoBIO, 2013)

Bipartite networks to study the genotype-to-phenotype relationship in cellular automata models. - Christian Darabos; Britney E. Graham; Ting Hu 001; Jason H. Moore (GECCO (Companion), 2013)

Coevolution of rules and topology in cellular automata. - Christian Darabos; Craig O. Mackenzie; Marco Tomassini; Mario Giacobini; Jason H. Moore (GECCO (Companion), 2013)

A simple multi-core parallelization strategy for learning classifier system evaluation. - James Rudd; Jason H. Moore; Ryan J. Urbanowicz (GECCO (Companion), 2013)

Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease. - Jason H. Moore; Douglas P. Hill; Andrew J. Saykin; Li Shen 001 (GPTP, 2013)

Network-Guided Sparse Learning for Predicting Cognitive Outcomes from MRI Measures. - Jingwen Yan; Heng Huang; Shannon L. Risacher; Sungeun Kim; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (MBIA, 2013)

Statistical Epistasis Networks Reduce the Computational Complexity of Searching Three-Locus Genetic Models. - Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (Pacific Symposium on Biocomputing, 2013)

Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis. - Ryan L. Collins; Ting Hu 001; Christian Wejse; Giorgio Sirugo; Scott M. Williams; Jason H. Moore (BioData Min., 2013)

Identification of SNPs associated with variola virus virulence. - Anne Gatewood Hoen; Shea N. Gardner; Jason H. Moore (BioData Min., 2013)

No-boundary thinking in bioinformatics research. - 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; et al. (BioData Min., 2013)

The limits of p-values for biological data mining. - James D. Malley; Abhijit Dasgupta 003; Jason H. Moore (BioData Min., 2013)

The disconnect between classical biostatistics and the biological data mining community. - James D. Malley; Jason H. Moore (BioData Min., 2013)

The central role of biological data mining in connecting diverse disciplines. - Jason H. Moore; Marylyn D. Ritchie (BioData Min., 2013)

Big Data analysis on autopilot? - Scott M. Williams; Jason H. Moore (BioData Min., 2013)

A multi-core parallelization strategy for statistical significance testing in learning classifier systems. - James Rudd; Jason H. Moore; Ryan J. Urbanowicz (Evol. Intell., 2013)

Research and applications: An information-gain approach to detecting three-way epistatic interactions in genetic association studies. - Ting Hu 001; Yuanzhu Peter Chen; Jeff Kiralis; Ryan L. Collins; Christian Wejse; Giorgio Sirugo; Scott M. Williams; Jason H. Moore (J. Am. Medical Informatics Assoc., 2013)

Research and applications: Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach. - Ryan J. Urbanowicz; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (J. Am. Medical Informatics Assoc., 2013)

Complex and dynamic population structures: synthesis, open questions, and future directions. - Joshua L. Payne; Mario Giacobini; Jason H. Moore (Soft Comput., 2013)

Models of Gene Regulation: Integrating Modern Knowledge into the Random Boolean Network Framework. - Christian Darabos; Mario Giacobini; Jason H. Moore; Marco Tomassini (Evolution, Complexity and Artificial Life, 2014)

Identification of Novel Genetic Models of Glaucoma Using the "EMERGENT" Genetic Programming-Based Artificial Intelligence System. - Jason H. Moore; Casey S. Greene; Douglas P. Hill (GPTP, 2014)

Delay-tolerant networks with network coding: How well can we simulate real devices? - Yuanzhu Peter Chen; Xu Liu; Walter Taylor; Jason H. Moore (ICC, 2014)

Message prioritization of epidemic forwarding in delay-tolerant networks. - Xu Liu; Yuanzhu Chen 001; Cheng Li 005; Walter Taylor; Jason H. Moore (ICNC, 2014)

Data synthesis and method evaluation for brain imaging genetics. - Jinhua Sheng; Sungeun Kim; Jingwen Yan; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ISBI, 2014)

Joint identification of imaging and proteomics biomarkers of Alzheimer's disease using network-guided sparse learning. - Jingwen Yan; Heng Huang; Sungeun Kim; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ISBI, 2014)

A Novel Structure-Aware Sparse Learning Algorithm for Brain Imaging Genetics. - Lei Du 001; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Heng Huang; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (MICCAI (3), 2014)

Population Exploration on Genotype Networks in Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (PPSN, 2014)

An Extended Michigan-Style Learning Classifier System for Flexible Supervised Learning, Classification, and Data Mining. - Ryan J. Urbanowicz; Gediminas Bertasius; Jason H. Moore (PPSN, 2014)

Applications of Bioinformatics to Non-Coding RNAs in the Era of Next-Generation Sequencing. - Chao Cheng; Jason H. Moore; Casey S. Greene (Pacific Symposium on Biocomputing, 2014)

Using the Bipartite Human Phenotype Network to Reveal Pleiotropy and Epistasis Beyond the Gene. - Christian Darabos; Samantha H. Harmon; Jason H. Moore (Pacific Symposium on Biocomputing, 2014)

Building the Next Generation of Quantitative Biologists. - Kristine A. Pattin; Anna C. Greene; Russ B. Altman; Lawrence E. Hunter; David A. Ross; James A. Foster; Jason H. Moore (Pacific Symposium on Biocomputing, 2014)

The Effects of Recombination on Phenotypic Exploration and Robustness in Evolution. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (Artif. Life, 2014)

Robustness, Evolvability, and the Logic of Genetic Regulation. - Joshua L. Payne; Jason H. Moore; Andreas Wagner (Artif. Life, 2014)

Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors. - 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; et al. (BioData Min., 2014)

The multiscale backbone of the human phenotype network based on biological pathways. - Christian Darabos; Marquitta J. White; Britney E. Graham; Derek N. Leung; Scott M. Williams; Jason H. Moore (BioData Min., 2014)

Risk estimation using probability machines. - Abhijit Dasgupta 003; Silke Szymczak; Jason H. Moore; Joan E. Bailey-Wilson; James D. Malley (BioData Min., 2014)

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility. - Ting Hu 001; Qinxin Pan; Angeline S. Andrew; Jillian M. Langer; Michael D. Cole; Craig R. Tomlinson; Margaret R. Karagas; Jason H. Moore (BioData Min., 2014)

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study. - 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 (BioData Min., 2014)

Innovation is often unnerving: the door into summer. - James D. Malley; Jason H. Moore (BioData Min., 2014)

First complex, then simple. - James D. Malley; Jason H. Moore (BioData Min., 2014)

O brave new world that has such machines in it. - James D. Malley; Karen G. Malley; Jason H. Moore (BioData Min., 2014)

Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes. - Nima Pouladi; Richard Cowper-Sallari; Jason H. Moore (BioData Min., 2014)

A Classification and Characterization of Two-Locus, Pure, Strict, Epistatic Models for Simulation and Detection. - Ryan J. Urbanowicz; Ambrose Granizo-Mackenzie; Jeff Kiralis; Jason H. Moore (BioData Min., 2014)

Computational genetics analysis of grey matter density in Alzheimer's disease. - Amanda L. Zieselman; Jonathan M. Fisher; Ting Hu 001; Peter C. Andrews; Casey S. Greene; Li Shen 001; Andrew J. Saykin; Jason H. Moore (BioData Min., 2014)

Optimization of gene set annotations via entropy minimization over variable clusters (EMVC). - H. Robert Frost; Jason H. Moore (Bioinform., 2014)

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. - Jingwen Yan; Lei Du 001; Sungeun Kim; Shannon L. Risacher; Heng Huang; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2014)

Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics. - Nadia M. Penrod; Jason H. Moore (BMC Syst. Biol., 2014)

Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks. - Dov A. Pechenick; Joshua L. Payne; Jason H. Moore (PLoS Comput. Biol., 2014)

GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics. - Lei Du 001; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Heng Huang; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (BIH, 2015)

Critical properties of cellular automata with evolving network topologies. - Christian Darabos; Jason H. Moore (CEC, 2015)

Retooling Fitness for Noisy Problems in a Supervised Michigan-style Learning Classifier System. - Ryan J. Urbanowicz; Jason H. Moore (GECCO, 2015)

Continuous Endpoint Data Mining with ExSTraCS: A Supervised Learning Classifier System. - Ryan J. Urbanowicz; Niranjan Ramanand; Jason H. Moore (GECCO (Companion), 2015)

A Bipartite Network Approach to Inferring Interactions Between Environmental Exposures and Human Diseases. - Christian Darabos; Emily D. Grussing; Maria E. Cricco; Kenzie A. Clark; Jason H. Moore (Pacific Symposium on Biocomputing, 2015)

Session Introduction. - 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 (Pacific Symposium on Biocomputing, 2015)

Genome-Wide Genetic Interaction Analysis of Glaucoma Using Expert Knowledge Derived from Human Phenotype Networks. - Ting Hu 001; Christian Darabos; Maria E. Cricco; Emily Kong; Jason H. Moore (Pacific Symposium on Biocomputing, 2015)

Training the Next Generation of Quantitative Biologists in the Era of Big Data. - 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 (Pacific Symposium on Biocomputing, 2015)

Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity. - Rishika De; Ting Hu 001; Jason H. Moore; Diane Gilbert-Diamond (BioData Min., 2015)

Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR). - 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; et al. (BioData Min., 2015)

Principal component gene set enrichment (PCGSE). - H. Robert Frost; Zhigang Li; Jason H. Moore (BioData Min., 2015)

Testing multiple hypotheses through IMP weighted FDR based on a genetic functional network with application to a new zebrafish transcriptome study. - Jiang Gui; Casey S. Greene; Con Sullivan; Walter Taylor; Jason H. Moore; Carol Kim (BioData Min., 2015)

Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks. - Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (BioData Min., 2015)

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm. - 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; et al. (BioData Min., 2015)

gammaMAXT: a fast multiple-testing correction algorithm. - François Van Lishout; Francesco Gadaleta; Jason H. Moore; Louis Wehenkel; Kristel Van Steen (BioData Min., 2015)

Prediction of relevant biomedical documents: a human microbiome case study. - Paul Thompson 001; Juliette Madan; Jason H. Moore (BioData Min., 2015)

The role of visualization and 3-D printing in biological data mining. - Talia Weiss; Amanda L. Zieselman; Douglas P. Hill; Solomon Gilbert Diamond; Li Shen 001; Andrew J. Saykin; Jason H. Moore (BioData Min., 2015)

Lumping versus splitting: the need for biological data mining in precision medicine. - Scott M. Williams; Jason H. Moore (BioData Min., 2015)

Spectral gene set enrichment (SGSE). - H. Robert Frost; Zhigang Li; Jason H. Moore (BMC Bioinform., 2015)

Delay-tolerant networks and network coding: Comparative studies on simulated and real-device experiments. - Yuanzhu Chen 001; Xu Liu; Jiafen Liu; Walter Taylor; Jason H. Moore (Comput. Networks, 2015)

ExSTraCS 2.0: description and evaluation of a scalable learning classifier system. - Ryan J. Urbanowicz; Jason H. Moore (Evol. Intell., 2015)

An Independent Filter for Gene Set Testing Based on Spectral Enrichment. - H. Robert Frost; Zhigang Li; Folkert W. Asselbergs; Jason H. Moore (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

Exploring the coevolution of predator and prey morphology and behavior. - Christoph Adami; Jason H. Moore; Fred C. Dyer; Arend Hintze; Randal S. Olson (ALIFE, 2016)

Bicliques in Graphs with Correlated Edges: From Artificial to Biological Networks. - Aaron Kershenbaum; Alicia Cutillo; Christian Darabos; Keitha A. Murray; Robert Schiaffino; Jason H. Moore (EvoApplications (1), 2016)

Automating Biomedical Data Science Through Tree-Based Pipeline Optimization. - Randal S. Olson; Ryan J. Urbanowicz; Peter C. Andrews; Nicole A. Lavender; La Creis Kidd; Jason H. Moore (EvoApplications (1), 2016)

Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. - Randal S. Olson; Nathan Bartley; Ryan J. Urbanowicz; Jason H. Moore (GECCO, 2016)

Pareto Inspired Multi-objective Rule Fitness for Adaptive Rule-based Machine Learning. - Ryan J. Urbanowicz; Randal S. Olson; Jason H. Moore (GECCO (Companion), 2016)

Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. - Randal S. Olson; Jason H. Moore (GPTP, 2016)

TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning. - Randal S. Olson; Jason H. Moore (AutoML@ICML, 2016)

Evolution of Active Categorical Image Classification via Saccadic Eye Movement. - Randal S. Olson; Jason H. Moore; Christoph Adami (PPSN, 2016)

Pareto Inspired Multi-objective Rule Fitness for Noise-Adaptive Rule-Based Machine Learning. - Ryan J. Urbanowicz; Randal S. Olson; Jason H. Moore (PPSN, 2016)

An Integrated Network Approach to Identifying Biological Pathways and Environmental Exposure Interactions in Complex Diseases. - Christian Darabos; Jingya Qiu; Jason H. Moore (PSB, 2016)

Adapting bioinformatics curricula for big data. - Anna C. Greene; Kristine A. Giffin; Casey S. Greene; Jason H. Moore (Briefings Bioinform., 2016)

Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies. - Samantha Cheng; Angeline S. Andrew; Peter C. Andrews; Jason H. Moore (BioData Min., 2016)

The tip of the iceberg: challenges of accessing hospital electronic health record data for biological data mining. - Spiros C. Denaxas; Folkert W. Asselbergs; Jason H. Moore (BioData Min., 2016)

Considerations for higher efficiency and productivity in research activities. - Diego A. Forero; Jason H. Moore (BioData Min., 2016)

Erratum to: Evolving hard problems: generating human genetics datasets with a complex etiology. - Daniel S. Himmelstein; Casey S. Greene; Jason H. Moore (BioData Min., 2016)

Evolutionary triangulation: informing genetic association studies with evolutionary evidence. - Minjun Huang; Britney E. Graham; Ge Zhang; Reed Harder; Nuri Kodaman; Jason H. Moore; Louis J. Muglia; Scott M. Williams (BioData Min., 2016)

Detecting gene-gene interactions using a permutation-based random forest method. - Jing Li; James D. Malley; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (BioData Min., 2016)

A call for biological data mining approaches in epidemiology. - Shannon M. Lynch; Jason H. Moore (BioData Min., 2016)

The golden era of biomedical informatics has begun. - Jason H. Moore; John H. Holmes (BioData Min., 2016)

Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method. - Lei Du 001; Heng Huang; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2016)

Structured sparse CCA for brain imaging genetics via graph OSCAR. - Lei Du 001; Heng Huang; Jingwen Yan; Sungeun Kim; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (BMC Syst. Biol., 2016)

A General Feature Engineering Wrapper for Machine Learning Using epsilon -Lexicase Survival. - William G. La Cava; Jason H. Moore (EuroGP, 2017)

Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. - William G. La Cava; Sara Silva; Leonardo Vanneschi; Lee Spector; Jason H. Moore (EvoApplications (1), 2017)

EVE: Cloud-Based Annotation of Human Genetic Variants. - Brian S. Cole; Jason H. Moore (EvoApplications (1), 2017)

Improving the Reproducibility of Genetic Association Results Using Genotype Resampling Methods. - Elizabeth R. Piette; Jason H. Moore (EvoApplications (1), 2017)

Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods. - William G. La Cava; Jason H. Moore (GECCO, 2017)

Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming. - Andrew Sohn; Randal S. Olson; Jason H. Moore (GECCO, 2017)

A System for Accessible Artificial Intelligence. - 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 (GPTP, 2017)

Problem Driven Machine Learning by Co-evolving Genetic Programming Trees and Rules in a Learning Classifier System. - Ryan J. Urbanowicz; Ben Yang; Jason H. Moore (GPTP, 2017)

Network-based genome wide study of hippocampal imaging phenotype in Alzheimer's Disease to identify functional interaction modules. - Xiaohui Yao; Jingwen Yan; Shannon L. Risacher; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (ICASSP, 2017)

Comparing Different Adverse Effects Among Multiple Drugs Using FAERS Data. - Jing Huang 021; Xinyuan Zhang 003; Jingcheng Du; Rui Duan 004; Liu Yang; Jason H. Moore; Yong Chen 016; Cui Tao (MedInfo, 2017)

Missing Data Imputation in the Electronic Health Record Using Deeply Learned Autoencoders. - Brett K. Beaulieu-Jones; Jason H. Moore; et al. (PSB, 2017)

The Training of Next Generation Data Scientists in Biomedicine. - 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 (PSB, 2017)

No-Boundary Thinking in Bioinformatics. - 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 (PSB, 2017)

Variant Set Enrichment: an R package to identify disease-associated functional genomic regions. - Musaddeque Ahmed; Richard C. Sallari; Haiyang Guo; Jason H. Moore; Housheng H. He; Mathieu Lupien (BioData Min., 2017)

Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery. - Nathaniel Crabtree; Jason H. Moore; John F. Bowyer; Nysia I. George (BioData Min., 2017)

Methods for enhancing the reproducibility of biomedical research findings using electronic health records. - Spiros C. Denaxas; Kenan Direk; Arturo Gonzalez-Izquierdo; Maria Pikoula; Sera Aylin Cakiroglu; Jason H. Moore; Harry Hemingway; Liam Smeeth (BioData Min., 2017)

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. - 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; et al. (BioData Min., 2017)

Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases. - 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 (BioData Min., 2017)

PMLB: a large benchmark suite for machine learning evaluation and comparison. - Randal S. Olson; William G. La Cava; Patryk Orzechowski; Ryan J. Urbanowicz; Jason H. Moore (BioData Min., 2017)

Artificial intelligence: more human with human. - Moshe Sipper; Jason H. Moore (BioData Min., 2017)

Evolutionary computation: the next major transition of artificial intelligence? - Moshe Sipper; Randal S. Olson; Jason H. Moore (BioData Min., 2017)

Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype. - 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 (BioData Min., 2017)

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules. - Xiaohui Yao; Jingwen Yan; Kefei Liu 001; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Casey S. Greene; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Bioinform., 2017)

Two-dimensional enrichment analysis for mining high-level imaging genetic associations. - Xiaohui Yao; Jingwen Yan; Sungeun Kim; Kwangsik Nho; Shannon L. Risacher; Mark Inlow; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Brain Informatics, 2017)

A System for Accessible Artificial Intelligence. - Randal S. Olson; Moshe Sipper; William G. La Cava; Sharon Tartarone; Steven Vitale; Weixuan Fu; John H. Holmes; Jason H. Moore (CoRR, 2017)

From MEGATON to RASCAL: Surfing the Parameter Space of Evolutionary Algorithms. - Moshe Sipper; Weixuan Fu; Karuna Ahuja; Jason H. Moore (CoRR, 2017)

$ε$-Lexicase selection: a probabilistic and multi-objective analysis of lexicase selection in continuous domains. - William G. La Cava; Thomas Helmuth; Lee Spector; Jason H. Moore (CoRR, 2017)

Benchmarking Relief-Based Feature Selection Methods. - Ryan J. Urbanowicz; Randal S. Olson; Peter Schmitt; Melissa Meeker; Jason H. Moore (CoRR, 2017)

Grammatical Evolution Strategies for Bioinformatics and Systems Genomics. - Jason H. Moore; Moshe Sipper (Handbook of Grammatical Evolution, 2018)

Comparing adverse effects of Hepatitis C drugs using FAERS data. - Jing Huang 021; Xinyuan Zhang 003; Jiayi Tong; Jingcheng Du; Rui Duan 004; Liu Yang; Jason H. Moore; Yong Chen 016; Cui Tao (BIBM, 2018)

An analysis of ϵ-lexicase selection for large-scale many-objective optimization. - William G. La Cava; Jason H. Moore (GECCO (Companion), 2018)

A multidimensional genetic programming approach for identifying epsistatic gene interactions. - William G. La Cava; Sara Silva; Kourosh Danai; Lee Spector; Leonardo Vanneschi; Jason H. Moore (GECCO (Companion), 2018)

Where are we now?: a large benchmark study of recent symbolic regression methods. - Patryk Orzechowski; William G. La Cava; Jason H. Moore (GECCO, 2018)

EBIC: a next-generation evolutionary-based parallel biclustering method. - Patryk Orzechowski; Moshe Sipper; Xiuzhen Huang; Jason H. Moore (GECCO (Companion), 2018)

Evolutionary computation: an investigation of parameter space. - Moshe Sipper; Weixuan Fu; Karuna Ahuja; Jason H. Moore (GECCO (Companion), 2018)

Attribute tracking: strategies towards improved detection and characterization of complex associations. - Ryan J. Urbanowicz; Christopher Lo; John H. Holmes; Jason H. Moore (GECCO, 2018)

Behavioral search drivers and the role of elitism in soft robotics. - William G. La Cava; Jason H. Moore (ALIFE, 2018)

How computational thought experiments can improve our understanding of the genetic architecture of common human diseases. - Jason H. Moore; Randal S. Olson; Peter Schmitt; Yong Chen 016; Elisabetta Manduchi (ALIFE, 2018)

Mapping patient trajectories using longitudinal extraction and deep learning in the MIMIC-III Critical Care Database. - Brett K. Beaulieu-Jones; Patryk Orzechowski; Jason H. Moore (PSB, 2018)

Session Introduction. - Yves A. Lussier; Joanne Berghout; Francesca Vitali; Kenneth S. Ramos; Maricel G. Kann; Jason H. Moore (PSB, 2018)

Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in Type 2 Diabetes GWAS. - Elisabetta Manduchi; Alessandra Chesi; Molly A. Hall; Struan F. A. Grant; Jason H. Moore (PSB, 2018)

A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods. - Jason H. Moore; Maksim Shestov; Peter Schmitt; Randal S. Olson (PSB, 2018)

Data-driven advice for applying machine learning to bioinformatics problems. - Randal S. Olson; William G. La Cava; Zairah Mustahsan; Akshay Varik; Jason H. Moore (PSB, 2018)

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. - Alena Orlenko; Jason H. Moore; Patryk Orzechowski; Randal S. Olson; Junmei Cairns; Pedro J. Caraballo; Richard M. Weinshilboum; Liewei Wang; Matthew K. Breitenstein (PSB, 2018)

Retrieving Impressions from Semantic Memory Modeled with Associative Pulsing Neural Networks. - Patryk Orzechowski; Adrian Horzyk; Janusz A. Starzyk; Jason H. Moore (SSCI, 2018)

Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV). - Elizabeth R. Piette; Jason H. Moore (BioData Min., 2018)

Investigating the parameter space of evolutionary algorithms. - Moshe Sipper; Weixuan Fu; Karuna Ahuja; Jason H. Moore (BioData Min., 2018)

To know the objective is not (necessarily) to know the objective function. - Moshe Sipper; Ryan J. Urbanowicz; Jason H. Moore (BioData Min., 2018)

Collective feature selection to identify crucial epistatic variants. - Shefali S. Verma; Anastasia Lucas; Xinyuan Zhang 003; Yogasudha Veturi; Scott M. Dudek; Binglan Li; Ruowang Li; Ryan J. Urbanowicz; Jason H. Moore; Dokyoon Kim; Marylyn D. Ritchie (BioData Min., 2018)

runibic: a Bioconductor package for parallel row-based biclustering of gene expression data. - Patryk Orzechowski; Artur Panszczyk; Xiuzhen Huang; Jason H. Moore (Bioinform., 2018)

EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery. - Patryk Orzechowski; Moshe Sipper; Xiuzhen Huang; Jason H. Moore (Bioinform., 2018)

EBIC: an artificial intelligence-based parallel biclustering algorithm for pattern discovery. - Patryk Orzechowski; Moshe Sipper; Xiuzhen Huang; Jason H. Moore (CoRR, 2018)

Stochastic optimization approaches to learning concise representations. - William G. La Cava; Tilak Raj Singh; James Taggart; Srinivas Suri; Jason H. Moore (CoRR, 2018)

EBIC: an open source software for high-dimensional and big data biclustering analyses. - Patryk Orzechowski; Jason H. Moore (CoRR, 2018)

PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data. - Jing Huang 021; Rui Duan 004; Rebecca A. Hubbard; Yonghui Wu; Jason H. Moore; Hua Xu 001; Yong Chen 016 (J. Am. Medical Informatics Assoc., 2018)

Medication class enrichment analysis: a novel algorithm to analyze multiple pharmacologic exposures simultaneously using electronic health record data. - Ravy K. Vajravelu; Frank I. Scott; Ronac Mamtani; Hongzhe Li; Jason H. Moore; James D. Lewis (J. Am. Medical Informatics Assoc., 2018)

Relief-based feature selection: Introduction and review. - Ryan J. Urbanowicz; Melissa Meeker; William G. La Cava; Randal S. Olson; Jason H. Moore (J. Biomed. Informatics, 2018)

Benchmarking relief-based feature selection methods for bioinformatics data mining. - Ryan J. Urbanowicz; Randal S. Olson; Peter Schmitt; Melissa Meeker; Jason H. Moore (J. Biomed. Informatics, 2018)

GPU Accelerated Browser for Neuroimaging Genomics. - Bob Zigon; Huang Li; Xiaohui Yao; Shiaofen Fang; Mohammad Al Hasan; Jingwen Yan; Jason H. Moore; Andrew J. Saykin; Li Shen 001 (Neuroinformatics, 2018)

Eleven quick tips for architecting biomedical informatics workflows with cloud computing. - Brian S. Cole; Jason H. Moore (PLoS Comput. Biol., 2018)

TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning. - Randal S. Olson; Jason H. Moore (Automated Machine Learning, 2019)

Interpretation of machine learning predictions for patient outcomes in electronic health records. - William G. La Cava; Christopher R. Bauer; Jason H. Moore; Sarah A. Pendergrass (AMIA, 2019)

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis. - Xiaohui Yao; Shan Cong; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Jason H. Moore; Li Shen 001 (BHI, 2019)

Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems. - Moshe Sipper; Jason H. Moore; Ryan J. Urbanowicz (CEC, 2019)

Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions. - Moshe Sipper; Jason H. Moore; Ryan J. Urbanowicz (EuroGP, 2019)

Semantic variation operators for multidimensional genetic programming. - William G. La Cava; Jason H. Moore (GECCO, 2019)

Discovering test statistics using genetic programming. - Jason H. Moore; Randal S. Olson; Yong Chen 016; Moshe Sipper (GECCO (Companion), 2019)

EBIC: a scalable biclustering method for large scale data analysis. - Patryk Orzechowski; Jason H. Moore (GECCO (Companion), 2019)

Strategies for improving performance of evolutionary biclustering algorithm EBIC. - Patryk Orzechowski; Jason H. Moore (GECCO (Companion), 2019)

Mining a massive RNA-seq dataset with biclustering: are evolutionary approaches ready for big data? - Patryk Orzechowski; Jason H. Moore (GECCO (Companion), 2019)

New Pathways in Coevolutionary Computation. - Moshe Sipper; Jason H. Moore; Ryan J. Urbanowicz (GPTP, 2019)

Learning concise representations for regression by evolving networks of trees. - William G. La Cava; Tilak Raj Singh; James Taggart; Srinivas Suri; Jason H. Moore (ICLR (Poster), 2019)

Using Machine Learning on Home Health Care Assessments to Predict Fall Risk. - 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 (MedInfo, 2019)

Reading between the genes: interpreting non-coding DNA in high-throughput. - Joanne Berghout; Yves A. Lussier; Francesca Vitali; Martha L. Bulyk; Maricel G. Kann; Jason H. Moore (PSB, 2019)

ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. - Rui Duan 004; Mary Regina Boland; Jason H. Moore; Yong Chen 016 (PSB, 2019)

Translational informatics of population Health: How large biomolecular and clinical datasets unite. - Yves A. Lussier; Atul J. Butte; Haiquan Li; Rong Chen; Jason H. Moore (PSB, 2019)

Exploration of a diversity of computational and statistical measures of association for genome-wide genetic studies. - Elisabetta Manduchi; Patryk Orzechowski; Marylyn D. Ritchie; Jason H. Moore (BioData Min., 2019)

Correction to: Investigating the parameter space of evolutionary algorithms. - Moshe Sipper; Weixuan Fu; Karuna Ahuja; Jason H. Moore (BioData Min., 2019)

STatistical Inference Relief (STIR) feature selection. - Trang T. Le; Ryan J. Urbanowicz; Jason H. Moore; Brett A. McKinney (Bioinform., 2019)

EBIC: an open source software for high-dimensional and big data analyses. - Patryk Orzechowski; Jason H. Moore (Bioinform., 2019)

Evaluating recommender systems for AI-driven data science. - William G. La Cava; Heather Williams; Weixuan Fu; Jason H. Moore (CoRR, 2019)

A Probabilistic and Multi-Objective Analysis of Lexicase Selection and ε-Lexicase Selection. - William G. La Cava; Thomas Helmuth; Lee Spector; Jason H. Moore (Evol. Comput., 2019)

Artificial Intelligence Based Approaches to Identify Molecular Determinants of Exceptional Health and Life Span-An Interdisciplinary Workshop at the National Institute on Aging. - Jason H. Moore; Nalini Raghavachari (Frontiers Artif. Intell., 2019)

Automated discovery of test statistics using genetic programming. - Jason H. Moore; Randal S. Olson; Yong Chen 016; Moshe Sipper (Genet. Program. Evolvable Mach., 2019)

Integration of genetic and clinical information to improve imputation of data missing from electronic health records. - Ruowang Li; Yong Chen 016; Jason H. Moore (J. Am. Medical Informatics Assoc., 2019)

A regression framework to uncover pleiotropy in large-scale electronic health record data. - Ruowang Li; Rui Duan 004; Daniel J. Rader; Scott M. Damrauer; Jason H. Moore; Yong Chen 016 (J. Am. Medical Informatics Assoc., 2019)

OMNIREP: originating meaning by coevolving encodings and representations. - Moshe Sipper; Jason H. Moore (Memetic Comput., 2019)

Comparing drug safety of hepatitis C therapies using post-market data. - Jing Huang 021; Xinyuan Zhang 003; Jiayi Tong; Jingcheng Du; Rui Duan 004; Liu Yang; Jason H. Moore; Cui Tao; Yong Chen 016 (BMC Medical Informatics Decis. Mak., 2019)

Multidimensional genetic programming for multiclass classification. - William G. La Cava; Sara Silva; Kourosh Danai; Lee Spector; Leonardo Vanneschi; Jason H. Moore (Swarm Evol. Comput., 2019)

Gene-Gene Interactions: An Essential Component to Modeling Complexity for Precision Medicine. - Molly A. Hall; Brian S. Cole; Jason H. Moore (Encyclopedia of Bioinformatics and Computational Biology (2), 2019)

Harnessing Electronic Health Records to Study Emerging Environmental Disasters: A Proof of Concept with PFAS. - Mary Regina Boland; Lena M. Davidson; Silvia P. Canelón; Jessica R. Meeker; Trevor M. Penning; John H. Holmes; Jason H. Moore (AMIA, 2020)

Explainable Artificial Intelligence (XAI): Current Approaches and Paths to the Future. - John H. Holmes; Riccardo Bellazzi; Carlo Combi; Jason H. Moore; Niels Peek (AMIA, 2020)

Expanding Polygenic Risk Scores to Include Automatic Genotype Encodings and Gene-gene Interactions. - Trang T. Le; Hoyt Gong; Patryk Orzechowski; Elisabetta Manduchi; Jason H. Moore (BIOINFORMATICS, 2020)

Evaluation of Phenotyping Errors on Polygenic Risk Score Predictions. - Ruowang Li; Jiayi Tong; Rui Duan 004; Yong Chen 016; Jason H. Moore (BIOINFORMATICS, 2020)

Extracting Behavioral Determinants of Health from Electronic Health Records: Classifying Yoga Mentions in the Clinic. - Nadia M. Penrod; Selah F. Lynch; Jason H. Moore (HEALTHINF, 2020)

Benchmarking Manifold Learning Methods on a Large Collection of Datasets. - Patryk Orzechowski; Franciszek Magiera; Jason H. Moore (EuroGP, 2020)

SGP-DT: Semantic Genetic Programming Based on Dynamic Targets. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (EuroGP, 2020)

Coevolving Artistic Images Using OMNIREP. - Moshe Sipper; Jason H. Moore; Ryan J. Urbanowicz (EvoMUSART, 2020)

Genetic programming approaches to learning fair classifiers. - William G. La Cava; Jason H. Moore (GECCO, 2020)

Large scale biomedical data analysis with tree-based automated machine learning. - Trang T. Le; Weixuan Fu; Jason H. Moore (GECCO Companion, 2020)

SGP-DT: towards effective symbolic regression with a semantic GP approach based on dynamic targets. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (GECCO Companion, 2020)

Image feature learning with a genetic programming autoencoder. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (GECCO Companion, 2020)

Image Feature Learning with Genetic Programming. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (PPSN (2), 2020)

Translational Bioinformatics: Biobanks in the Precision Medicine Era. - Marylyn D. Ritchie; Jason H. Moore; Ju Han Kim (PSB, 2020)

Robust-ODAL: Learning from Heterogeneous Health Systems Without Sharing Patient-LevelData. - Jiayi Tong; Rui Duan 004; Ruowang Li; Martijn J. Scheuemie; Jason H. Moore; Yong Chen 016 (PSB, 2020)

How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases. - Jason H. Moore; Randal S. Olson; Peter Schmitt; Yong Chen 016; Elisabetta Manduchi (Artif. Life, 2020)

Ten important roles for academic leaders in data science. - Jason H. Moore (BioData Min., 2020)

Ideas for how informaticians can get involved with COVID-19 research. - Jason H. Moore; Ian Barnett; Mary Regina Boland; Yong Chen 016; George Demiris; Graciela Gonzalez-Hernandez; Daniel S. Herman; Blanca E. Himes; Rebecca A. Hubbard; Dokyoon Kim; Jeffrey S. Morris; Danielle L. Mowery; et al. (BioData Min., 2020)

Conservation machine learning. - Moshe Sipper; Jason H. Moore (BioData Min., 2020)

WellExplorer: an integrative resource linking hydraulic fracturing chemicals with hormonal pathways and geographic location. - Owen Wetherbee; Jessica R. Meeker; Caroline Devoto; Trevor M. Penning; Jason H. Moore; Mary Regina Boland (Database J. Biol. Databases Curation, 2020)

Scaling tree-based automated machine learning to biomedical big data with a feature set selector. - Trang T. Le; Weixuan Fu; Jason H. Moore (Bioinform., 2020)

Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning. - 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 (Bioinform., 2020)

Regional imaging genetic enrichment analysis. - Xiaohui Yao; Shan Cong; Jingwen Yan; Shannon L. Risacher; Andrew J. Saykin; Jason H. Moore; Li Shen 001 (Bioinform., 2020)

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses. - Elisabetta Manduchi; Weixuan Fu; Joseph D. Romano; Stefano Ruberto; Jason H. Moore (BMC Bioinform., 2020)

Is deep learning necessary for simple classification tasks? - Joseph D. Romano; Trang T. Le; Weixuan Fu; Jason H. Moore (CoRR, 2020)

Benchmarking in Optimization: Best Practice and Open Issues. - Thomas Bartz-Beielstein; Carola Doerr; Jakob Bossek; Sowmya Chandrasekaran; Tome Eftimov; Andreas Fischbach; Pascal Kerschke; Manuel López-Ibáñez 001; Katherine M. Malan; Jason H. Moore; Boris Naujoks; Patryk Orzechowski; et al. (CoRR, 2020)

A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments. - Ryan J. Urbanowicz; Pranshu Suri; Yuhan Cui; Jason H. Moore; Karen Ruth; Rachael Stolzenberg-Solomon; Shannon M. Lynch (CoRR, 2020)

Learning feature spaces for regression with genetic programming. - William G. La Cava; Jason H. Moore (Genet. Program. Evolvable Mach., 2020)

Genetic programming theory and practice: a fifteen-year trajectory. - Moshe Sipper; Jason H. Moore (Genet. Program. Evolvable Mach., 2020)

Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm. - Rui Duan 004; Mary Regina Boland; Zixuan Liu; Yue Liu; Howard H. Chang; Hua Xu 001; Haitao Chu; Christopher H. Schmid; Christopher B. Forrest; John H. Holmes; Martijn J. Schuemie; Jesse A. Berlin; et al. (J. Am. Medical Informatics Assoc., 2020)

Learning from local to global: An efficient distributed algorithm for modeling time-to-event data. - Rui Duan 004; Chongliang Luo; Martijn J. Schuemie; Jiayi Tong; C. Jason Liang; Howard H. Chang; Mary Regina Boland; Jiang Bian 001; Hua Xu 001; John H. Holmes; Christopher B. Forrest; Sally C. Morton; et al. (J. Am. Medical Informatics Assoc., 2020)

An augmented estimation procedure for EHR-based association studies accounting for differential misclassification. - Jiayi Tong; Jing Huang 021; Jessica Chubak; Xuan Wang; Jason H. Moore; Rebecca A. Hubbard; Yong Chen 016 (J. Am. Medical Informatics Assoc., 2020)

A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients. - Lingjiao Zhang; Xiruo Ding; Yanyuan Ma; Naveen Muthu; Imran Ajmal; Jason H. Moore; Daniel S. Herman; Jinbo Chen (J. Am. Medical Informatics Assoc., 2020)

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium. - 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; et al. (npj Digit. Medicine, 2020)

Ten simple rules for writing a paper about scientific software. - Joseph D. Romano; Jason H. Moore (PLoS Comput. Biol., 2020)

Gamorithm. - Moshe Sipper; Jason H. Moore (IEEE Trans. Games, 2020)

Dataset to replicate experiments in "Image Feature Learning with Genetic Programming" paper. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (Zenodo, 2020)

Rapid prototyping of evolution-driven biclustering methods in Julia. - Pawel Renc; Patryk Orzechowski; Aleksander Byrski; Jaroslaw Was; Jason H. Moore (GECCO Companion, 2021)

EBIC.JL: an efficient implementation of evolutionary biclustering algorithm in Julia. - Pawel Renc; Patryk Orzechowski; Aleksander Byrski; Jaroslaw Was; Jason H. Moore (GECCO Companion, 2021)

Towards effective GP multi-class classification based on dynamic targets. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (GECCO, 2021)

Socio-cognitive Evolution Strategies. - Aleksandra Urbanczyk; Bartosz Nowak; Patryk Orzechowski; Jason H. Moore; Marek Kisiel-Dorohinicki; Aleksander Byrski (ICCS (2), 2021)

Contemporary Symbolic Regression Methods and their Relative Performance. - William G. La Cava; Patryk Orzechowski; Bogdan Burlacu; Fabrício Olivetti de França; Marco Virgolin; Ying Jin; Michael Kommenda; Jason H. Moore (NeurIPS Datasets and Benchmarks, 2021)

Raising the stakeholders: Improving patient outcomes through interprofessional collaborations in AI for healthcare. - Carly A. Bobak; Marek Svoboda; Kristine A. Giffin; Dennis P. Wall; Jason H. Moore (PSB, 2021)

Translational Bioinformatics: Integrating Electronic Health Record and Omics Data. - Dokyoon Kim; Ju Han Kim; Jason H. Moore (PSB, 2021)

Empowering the data science scientist. - Jason H. Moore (BioData Min., 2021)

Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science. - Jason H. Moore; Van Q. Truong; Ashley B. Robbins; David Nicholson; Clar Lynda Williams-Devane (BioData Min., 2021)

A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions. - Alena Orlenko; Jason H. Moore (BioData Min., 2021)

Evaluating recommender systems for AI-driven biomedical informatics. - William G. La Cava; Heather Williams; Weixuan Fu; Steven Vitale; Durga Srivatsan; Jason H. Moore (Bioinform., 2021)

treeheatr: an R package for interpretable decision tree visualizations. - Trang T. Le; Jason H. Moore (Bioinform., 2021)

Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers. - Patryk Orzechowski; Jason H. Moore (CoRR, 2021)

TPOT-NN: augmenting tree-based automated machine learning with neural network estimators. - Joseph D. Romano; Trang T. Le; Weixuan Fu; Jason H. Moore (Genet. Program. Evolvable Mach., 2021)

A semantic genetic programming framework based on dynamic targets. - Stefano Ruberto; Valerio Terragni; Jason H. Moore (Genet. Program. Evolvable Mach., 2021)

Symbolic-regression boosting. - Moshe Sipper; Jason H. Moore (Genet. Program. Evolvable Mach., 2021)

Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data. - 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; et al. (J. Am. Medical Informatics Assoc., 2021)

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. - 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; et al. (J. Am. Medical Informatics Assoc., 2021)

TargetTox: A Feature Selection Pipeline for Identifying Predictive Targets Associated with Drug Toxicity. - Yun Hao; Jason H. Moore (J. Chem. Inf. Model., 2021)

REGENS: an open source Python package for simulating realistic autosomal genotypes. - John T. Gregg; Trang T. Le; Jason H. Moore (J. Open Source Softw., 2021)

Harnessing electronic health records to study emerging environmental disasters: a proof of concept with perfluoroalkyl substances (PFAS). - Mary Regina Boland; Lena M. Davidson; Silvia P. Canelón; Jessica R. Meeker; Trevor M. Penning; John H. Holmes; Jason H. Moore (npj Digit. Medicine, 2021)

Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer's Disease. - Jiahang Sha; Jingxuan Bao; Kefei Liu 001; Shu Yang 009; Zixuan Wen; Yuhan Cui; Junhao Wen 002; Christos Davatzikos; Jason H. Moore; Andrew J. Saykin; Qi Long; Li Shen 001 (BIBM, 2022)

A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark. - Patryk Orzechowski; Pawel Renc; William G. La Cava; Jason H. Moore; Arkadiusz Sitek; Jaroslaw Was; Joost B. Wagenaar (GECCO Companion, 2022)

A manifesto on explainability for artificial intelligence in medicine. - Carlo Combi; Beatrice Amico; Riccardo Bellazzi; Andreas Holzinger; Jason H. Moore; Marinka Zitnik; John H. Holmes (Artif. Intell. Medicine, 2022)

Novel digital approaches to the assessment of problematic opioid use. - Philip J. Freda; Henry R. Kranzler; Jason H. Moore (BioData Min., 2022)

Benchmarking AutoML frameworks for disease prediction using medical claims. - Roland Albert A. Romero; Mariefel Nicole Y. Deypalan; Suchit Mehrotra; John Titus Jungao; Natalie E. Sheils; Elisabetta Manduchi; Jason H. Moore (BioData Min., 2022)

Gene-Interaction-Sensitive enrichment analysis in congenital heart disease. - Alexa A. Woodward; Deanne M. Taylor; Elizabeth Goldmuntz; Laura E. Mitchell; A. J. Agopian; Jason H. Moore; Ryan J. Urbanowicz (BioData Min., 2022)

PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods. - 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 (Bioinform., 2022)

Automatically Balancing Model Accuracy and Complexity using Solution and Fitness Evolution (SAFE). - Moshe Sipper; Jason H. Moore; Ryan J. Urbanowicz (CoRR, 2022)

Benchmarking AutoML algorithms on a collection of synthetic classification problems. - Pedro Henrique Ribeiro; Patryk Orzechowski; Joost B. Wagenaar; Jason H. Moore (CoRR, 2022)

SurvMaximin: Robust federated approach to transporting survival risk prediction models. - Xuan Wang; Harrison G. Zhang; Xin Xiong; Chuan Hong; Griffin M. Weber; Gabriel A. Brat; Clara-Lea Bonzel; Yuan Luo 001; Rui Duan 004; Nathan P. Palmer; Meghan R. Hutch; Alba Gutiérrez-Sacristán; et al. (J. Biomed. Informatics, 2022)

Applying autonomous hybrid agent-based computing to difficult optimization problems. - Mateusz Godzik; Jacek Dajda; Marek Kisiel-Dorohinicki; Aleksander Byrski; Leszek Rutkowski; Patryk Orzechowski; Joost B. Wagenaar; Jason H. Moore (J. Comput. Sci., 2022)

Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics. - Mansu Kim; Eun Jeong Min; Kefei Liu 001; Jingwen Yan; Andrew J. Saykin; Jason H. Moore; Qi Long; Li Shen 001 (Medical Image Anal., 2022)

Knowledge-guided deep learning models of drug toxicity improve interpretation. - Yun Hao; Joseph D. Romano; Jason H. Moore (Patterns, 2022)

Spatial Pyramid Pooling With 3D Convolution Improves Lung Cancer Detection. - Jason L. Causey; Keyu Li; Xianghao Chen; Wei Dong 003; Karl Walker; Jake A. Qualls; Jonathan W. Stubblefield; Jason H. Moore; Yuanfang Guan; Xiuzhen Huang (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection. - Elisabetta Manduchi; Trang T. Le; Weixuan Fu; Jason H. Moore (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Faster Convergence with Lexicase Selection in Tree-Based Automated Machine Learning. - 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 (EuroGP, 2023)

Extending Tree-Based Automated Machine Learning to Biomedical Image and Text Data Using Custom Feature Extractors. - Rachit Kumar; Joseph D. Romano; Marylyn D. Ritchie; Jason H. Moore (GECCO Companion, 2023)

TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning. - Pedro Henrique Ribeiro; Anil Kumar Saini; Jay Moran; Nicholas Matsumoto; Hyunjun Choi; Miguel E. Hernandez; Jason H. Moore (GPTP, 2023)

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. - Boning Tong; Zhuoping Zhou; Davoud Ataee Tarzanagh; Bojian Hou; Andrew J. Saykin; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (MLMI@MICCAI (2), 2023)

A flexible symbolic regression method for constructing interpretable clinical prediction models. - William G. La Cava; Paul C. Lee; Imran Ajmal; Xiruo Ding; Priyanka Solanki; Jordana B. Cohen; Jason H. Moore; Daniel S. Herman (npj Digit. Medicine, 2023)

LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes. - 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 (BioData Min., 2023)

Automated quantitative trait locus analysis (AutoQTL). - Philip J. Freda; Attri Ghosh; Elizabeth Zhang; Tianhao Luo; Apurva S. Chitre; Oksana Polesskaya; Celine L. St. Pierre; Jianjun Gao 004; Connor D. Martin; Hao Chen; Angel G. Garcia-Martinez; Tengfei Wang; et al. (BioData Min., 2023)

STAR_outliers: a python package that separates univariate outliers from non-normal distributions. - John T. Gregg; Jason H. Moore (BioData Min., 2023)

ChatGPT and large language models in academia: opportunities and challenges. - 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 (BioData Min., 2023)

Genetics and precision health: the ecological fallacy and artificial intelligence solutions. - Scott M. Williams; Jason H. Moore (BioData Min., 2023)

Aliro: an automated machine learning tool leveraging large language models. - Hyunjun Choi; Jay Moran; Nicholas Matsumoto; Miguel E. Hernandez; Jason H. Moore (Bioinform., 2023)

Is the evolution metaphor still necessary or even useful for genetic programming? - Jason H. Moore (Genet. Program. Evolvable Mach., 2023)

Ten simple rules for managing laboratory information. - 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; et al. (PLoS Comput. Biol., 2023)

Lexidate: Model Evaluation and Selection with Lexicase. - Jose Guadalupe Hernandez; Anil Kumar Saini; Jason H. Moore (GECCO Companion, 2024)

Survival-LCS: A Rule-Based Machine Learning Approach to Survival Analysis. - Alexa A. Woodward; Harsh Bandhey; Jason H. Moore; Ryan J. Urbanowicz (GECCO, 2024)

A review of feature selection strategies utilizing graph data structures and Knowledge Graphs. - Sisi Shao; Pedro Henrique Ribeiro; Christina M. Ramirez; Jason H. Moore (Briefings Bioinform., 2024)

Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis. - Sandra Batista; Vered Madar; Philip J. Freda; Priyanka Bhandary; Attri Ghosh; Nicholas Matsumoto; Apurva S. Chitre; Abraham A. Palmer; Jason H. Moore (BioData Min., 2024)

PAGER: A novel genotype encoding strategy for modeling deviations from additivity in complex trait association studies. - Philip J. Freda; Attri Ghosh; Priyanka Bhandary; Nicholas Matsumoto; Apurva S. Chitre; Jiayan Zhou; Molly A. Hall; Abraham A. Palmer; Tayo Obafemi-Ajayi; Jason H. Moore (BioData Min., 2024)

Assessing the limitations of relief-based algorithms in detecting higher-order interactions. - Philip J. Freda; Suyu Ye; Robert Zhang 004; Jason H. Moore; Ryan J. Urbanowicz (BioData Min., 2024)

Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis. - Zhendong Sha; Philip J. Freda; Priyanka Bhandary; Attri Ghosh; Nicholas Matsumoto; Jason H. Moore; Ting Hu 001 (BioData Min., 2024)

Using GPT-4 to write a scientific review article: a pilot evaluation study. - Zhiping Paul Wang; Priyanka Bhandary; Yizhou Wang; Jason H. Moore (BioData Min., 2024)

Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies. - 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; et al. (CoRR, 2024)

Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras. - Jun Yu; Yutong Dai 002; Xiaokang Liu; Jin Huang; Yishan Shen; Ke Zhang; Rong Zhou; Eashan Adhikarla; Wenxuan Ye; Yixin Liu 002; Zhaoming Kong; Kai Zhang 039; et al. (CoRR, 2024)

Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics. - Jose Guadalupe Hernandez; Anil Kumar Saini; Jason H. Moore (CoRR, 2024)

Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs. - Tianqi Shang; Shu Yang 009; Weiqing He; Tianhua Zhai; Dawei Li 008; Bojian Hou; Tianlong Chen 001; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (CoRR, 2024)

Interpretable deep clustering survival machines for Alzheimer's disease subtype discovery. - Bojian Hou; Zixuan Wen; Jingxuan Bao; Richard Zhang; Boning Tong; Shu Yang 009; Junhao Wen 002; Yuhan Cui; Jason H. Moore; Andrew J. Saykin; Heng Huang; Paul M. Thompson; et al. (Medical Image Anal., 2024)

Advancing LGBTQ+ inclusion in STEM education and AI research. - Emily Wong; Ryan J. Urbanowicz; Tiffani J. Bright; Nicholas P. Tatonetti; Yi-Wen Hsiao; Xiuzhen Huang; Jason H. Moore; Pei-Chen Peng (Patterns, 2024)

A latent transfer learning method for estimating hospital-specific post-acute healthcare demands following SARS-CoV-2 infection. - Qiong Wu; Nathan M. Pajor; Yiwen Lu; Charles J. Wolock; Jiayi Tong; Vitaly Lorman; Kevin B. Johnson; Jason H. Moore; Christopher B. Forrest; David A. Asch; Yong Chen 016 (Patterns, 2024)

Enhancing clinical outcome predictions through effective sample size evaluation in graph-based digital twin modeling. - Xi Li; Jui-Hsuan Chang; Mythreye Venkatesan; Zhiping Paul Wang; Jason H. Moore (BioData Min., 2025)

Vibe coding: a new paradigm for biomedical software development. - Jason H. Moore; Nicholas P. Tatonetti (BioData Min., 2025)

AI as an accelerator for defining new problems that transcends boundaries. - Tayo Obafemi-Ajayi; Steven F. Jennings; Yu Zhang; Kara Li Liu; Joan Peckham; Jason H. Moore (BioData Min., 2025)

Drug repurposing for Alzheimer's disease using a graph-of-thoughts based large language model to infer drug-disease relationships in a comprehensive knowledge graph. - Zhiping Paul Wang; Xi Li; Nicholas Matsumoto; Mythreye Venkatesan; Jui-Hsuan Chang; Jay Moran; Hyunjun Choi; Binglan Li; Yufei Meng; Miguel E. Hernandez; Jason H. Moore (BioData Min., 2025)

Mapping GLAMs: creating a national dataset of GLAMs to develop a categorical climate-change risk assessment scale. - Edward Benoit III; Jill Trepanier; Jennifer Vanos; Emily Fisher; Kaitlyn Bailey; Annie Waddell; Jason H. Moore; Mandy Hatman; Mary Sidwell; Symonne Russell; Virginia Seger; Paige Boutte; et al. (Inf. Res., 2025)

A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics. - Huixin Zhan; Jason H. Moore; Zijun Zhang (Nat. Mac. Intell., 2025)

The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning. - Jose Guadalupe Hernandez; Anil Kumar Saini; Attri Ghosh; Jason H. Moore (Patterns, 2025)

StarBASE-GP: Biologically-Guided Automated Machine Learning for Genotype-to-Phenotype Association Analysis. - Jose Guadalupe Hernandez; Attri Ghosh; Philip J. Freda; Yufei Meng; Nicholas Matsumoto; Jason H. Moore (CoRR, 2025)

SafeGenes: Evaluating the Adversarial Robustness of Genomic Foundation Models. - Huixin Zhan; Jason H. Moore (CoRR, 2025)

Agentic Surgical AI: Surgeon Style Fingerprinting and Privacy Risk Quantification via Discrete Diffusion in a Vision-Language-Action Framework. - Huixin Zhan; Jason H. Moore (CoRR, 2025)

Enabling Few-Shot Alzheimer's Disease Diagnosis on Tabular Biomarker Data with LLMs. - Sophie Kearney; Shu Yang 009; Zixuan Wen; Bojian Hou; Duy Duong-Tran; Tianlong Chen 001; Jason H. Moore; Marylyn D. Ritchie; Li Shen 001 (CoRR, 2025)

GP and LLMs for Program Synthesis: No Clear Winners. - Jose Guadalupe Hernandez; Anil Kumar Saini; Gabriel Ketron; Jason H. Moore (CoRR, 2025)