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Jason H. Moore: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jason H. Moore, Joel S. Parker, Lance W. Hahn
    Symbolic Discriminant Analysis for Mining Gene Expression Patterns. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:372-381 [Conf]
  2. Jason H. Moore
    Cross Validation Consistency for the Assessment of Genetic Programming Results in Microarray Studies. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2003, pp:99-106 [Conf]
  3. Jason H. Moore, Lance W. Hahn
    An Improved Grammatical Evolution Strategy for Hierarchical Petri Net Modeling of Complex Genetic Systems. [Citation Graph (0, 0)][DBLP]
    EvoWorkshops, 2004, pp:63-72 [Conf]
  4. Jason H. Moore, Lance W. Hahn
    Grammatical Evolution for the Discovery of Petri Net Models of Complex Genetic Systems. [Citation Graph (0, 0)][DBLP]
    GECCO, 2003, pp:2412-2413 [Conf]
  5. Jason H. Moore, Lance W. Hahn
    Systems Biology Modeling in Human Genetics Using Petri Nets and Grammatical Evolution. [Citation Graph (0, 0)][DBLP]
    GECCO (1), 2004, pp:392-401 [Conf]
  6. 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. [Citation Graph (0, 0)][DBLP]
    GECCO, 2002, pp:1150-1155 [Conf]
  7. David M. Reif, Bill C. White, Nancy Olsen, Thomas Aune, Jason H. Moore
    Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data. [Citation Graph (0, 0)][DBLP]
    GECCO, 2003, pp:2277-2287 [Conf]
  8. Marylyn D. Ritchie, Christopher S. Coffey, Jason H. Moore
    Genetic Programming Neural Networks as a Bioinformatics Tool for Human Genetics. [Citation Graph (0, 0)][DBLP]
    GECCO (1), 2004, pp:438-448 [Conf]
  9. Jason H. Moore, Lance W. Hahn
    Cellular Automata and Genetic Algorithms for Parallel Problem Solving in Human Genetics. [Citation Graph (0, 0)][DBLP]
    PPSN, 2002, pp:821-830 [Conf]
  10. Jason H. Moore, Bill C. White
    Exploiting Expert Knowledge in Genetic Programming for Genome-Wide Genetic Analysis. [Citation Graph (0, 0)][DBLP]
    PPSN, 2006, pp:969-977 [Conf]
  11. Jason H. Moore, Lance W. Hahn
    A Cellular Automata Approach to Detecting Interactions Among Single-nucleotide Polymorphisms in Complex Multifactorial Diseases. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2002, pp:53-64 [Conf]
  12. David M. Reif, Scott M. Dudek, Christian M. Shaffer, Janey Wang, Jason H. Moore
    Exploratory Visual Analysis of Pharmacogenomic Results. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2005, pp:- [Conf]
  13. Jason H. Moore, Lance W. Hahn, Marylyn D. Ritchie, Tricia A. Thornton, Bill C. White
    Routine discovery of complex genetic models using genetic algorithms. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2004, v:4, n:1, pp:79-86 [Journal]
  14. 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. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2007, v:7, n:1, pp:471-479 [Journal]
  15. Lance W. Hahn, Marylyn D. Ritchie, Jason H. Moore
    Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2003, v:19, n:3, pp:376-382 [Journal]
  16. 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. [Citation Graph (0, 0)][DBLP]
    BMC Bioinformatics, 2004, v:5, n:, pp:49- [Journal]
  17. 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. [Citation Graph (0, 0)][DBLP]
    BMC Bioinformatics, 2003, v:4, n:, pp:28- [Journal]
  18. Tricia A. Thornton-Wells, Jason H. Moore, Jonathan L. Haines
    Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data. [Citation Graph (0, 0)][DBLP]
    BMC Bioinformatics, 2006, v:7, n:, pp:204- [Journal]
  19. Lance W. Hahn, Jason H. Moore
    Ideal discrimination of discrete clinical endpoints using multilocus genotypes. [Citation Graph (0, 0)][DBLP]
    In Silico Biology, 2004, v:4, n:, pp:- [Journal]
  20. Jason H. Moore
    Detection of linear and nonlinear dependencies in time series using the method of surrogate data in S-PLUS. [Citation Graph (0, 0)][DBLP]
    Computer Methods and Programs in Biomedicine, 2000, v:63, n:2, pp:117-121 [Journal]
  21. Jason H. Moore, Bill C. White
    Tuning ReliefF for Genome-Wide Genetic Analysis. [Citation Graph (0, 0)][DBLP]
    EvoBIO, 2007, pp:166-175 [Conf]
  22. Jason H. Moore, Nate Barney, Bill C. White
    Towards human-human-computer interaction for biologically-inspired problem-solving in human genetics. [Citation Graph (0, 0)][DBLP]
    GECCO, 2007, pp:432-433 [Conf]
  23. Jason H. Moore
    Bioinformatics. [Citation Graph (0, 0)][DBLP]
    GECCO (Companion), 2007, pp:3435-3457 [Conf]
  24. Casey S. Greene, Bill C. White, Jason H. Moore
    An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming. [Citation Graph (0, 0)][DBLP]
    PRIB, 2007, pp:30-40 [Conf]
  25. 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. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:491-497 [Conf]
  26. 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. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:676-682 [Conf]

  27. Ant Colony Optimization for Genome-Wide Genetic Analysis. [Citation Graph (, )][DBLP]


  28. Feature Selection using a Random Forests Classifier for the Integrated Analysis of Multiple Data Types. [Citation Graph (, )][DBLP]


  29. Development and Evaluation of an Open-Ended Computational Evolution System for the Genetic Analysis of Susceptibility to Common Human Diseases. [Citation Graph (, )][DBLP]


  30. Sexual Recombination in Self-Organizing Interaction Networks. [Citation Graph (, )][DBLP]


  31. Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease. [Citation Graph (, )][DBLP]


  32. Artificial Immune Systems for Epistasis Analysis in Human Genetics. [Citation Graph (, )][DBLP]


  33. The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics. [Citation Graph (, )][DBLP]


  34. A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships. [Citation Graph (, )][DBLP]


  35. Mask functions for the symbolic modeling of epistasis using genetic programming. [Citation Graph (, )][DBLP]


  36. Using expert knowledge in initialization for genome-wide analysis of epistasis using genetic programming. [Citation Graph (, )][DBLP]


  37. Environmental noise improves epistasis models of genetic data discovered using a computational evolution system. [Citation Graph (, )][DBLP]


  38. Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units. [Citation Graph (, )][DBLP]


  39. The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies. [Citation Graph (, )][DBLP]


  40. Bioinformatics. [Citation Graph (, )][DBLP]


  41. The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies. [Citation Graph (, )][DBLP]


  42. Employing Publically Available Biological Expert Knowledge from Protein-Protein Interaction Information. [Citation Graph (, )][DBLP]


  43. Sensible initialization using expert knowledge for genome-wide analysis of epistasis using genetic programming. [Citation Graph (, )][DBLP]


  44. Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches. [Citation Graph (, )][DBLP]


  45. Development and evaluation of an open-ended computational evolution system for the creation of digital organisms with complex genetic architecture. [Citation Graph (, )][DBLP]


  46. Evaporative cooling feature selection for genotypic data involving interactions. [Citation Graph (, )][DBLP]


  47. Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS. [Citation Graph (, )][DBLP]


  48. Bioinformatics challenges for genome-wide association studies. [Citation Graph (, )][DBLP]


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