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Jeff Kiralis
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2010 – 2019
- 2014
- [j6]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) - 2013
- [j5]Ting Hu, Yuanzhu Peter Chen, Jeff Kiralis, Ryan L. Collins
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) - [c6]Arvis Sulovari
Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease. EvoBIO 2013: 129-140 - [c5]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 - 2012
- [j4]Ryan J. Urbanowicz
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection. BioData Min. 5: 15 (2012) - [j3]Ryan J. Urbanowicz
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures. BioData Min. 5: 16 (2012) - 2011
- [j2]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) - 2010
- [c4]Casey S. Greene
The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics. EvoBIO 2010: 182-193
2000 – 2009
- 2009
- [j1]Casey S. Greene
Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions. BioData Min. 2: 5 (2009) - [c3]Casey S. Greene
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 - [c2]Jason M. Gilmore, Casey S. Greene
An Analysis of New Expert Knowledge Scaling Methods for Biologically Inspired Computing. ECAL (2) 2009: 286-293 - [c1]Casey S. Greene
Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease. EvoBIO 2009: 92-103
Coauthor Index
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