Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
暂无分享,去创建一个
Jason H. Moore | Casey S. Greene | Jeff Kiralis | Nadia M. Penrod | N. Penrod | C. Greene | Jeff Kiralis | J. Moore
[1] Jason H. Moore,et al. Genome-Wide Genetic Analysis Using Genetic Programming: The Critical Need for Expert Knowledge , 2007 .
[2] Igor Kononenko,et al. Estimating Attributes: Analysis and Extensions of RELIEF , 1994, ECML.
[3] M. McCarthy,et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges , 2008, Nature Reviews Genetics.
[4] Jason H. Moore,et al. Exploiting Expert Knowledge in Genetic Programming for Genome-Wide Genetic Analysis , 2006, PPSN.
[5] Todd Holden,et al. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. , 2006, Journal of theoretical biology.
[6] F. James Rohlf,et al. Biometry: The Principles and Practice of Statistics in Biological Research , 1969 .
[7] Jason H. Moore,et al. STUDENTJAMA. The challenges of whole-genome approaches to common diseases. , 2004, JAMA.
[8] Casey S Greene,et al. Ability of epistatic interactions of cytokine single-nucleotide polymorphisms to predict susceptibility to disease subsets in systemic sclerosis patients. , 2008, Arthritis and rheumatism.
[9] Sokal Rr,et al. Biometry: the principles and practice of statistics in biological research 2nd edition. , 1981 .
[10] Marko Robnik-Sikonja,et al. An adaptation of Relief for attribute estimation in regression , 1997, ICML.
[11] Daniel E. Weeks,et al. Interpretation of Genetic Association Studies: Markers with Replicated Highly Significant Odds Ratios May Be Poor Classifiers , 2009, PLoS genetics.
[12] Larry A. Rendell,et al. A Practical Approach to Feature Selection , 1992, ML.
[13] J. Hirschhorn,et al. A comprehensive review of genetic association studies , 2002, Genetics in Medicine.
[14] Marylyn D. Ritchie,et al. Linkage Disequilibrium in Genetic Association Studies Improves the Performance of Grammatical Evolution Neural Networks , 2007, 2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.
[15] Jason H. Moore,et al. Tuning ReliefF for Genome-Wide Genetic Analysis , 2007, EvoBIO.
[16] U. Finckh,et al. The future of genetic association studies in Alzheimer disease , 2003, Journal of Neural Transmission.
[17] Peter Kraft,et al. Genetic risk prediction--are we there yet? , 2009, The New England journal of medicine.
[18] A. Singleton,et al. Genomewide association studies and human disease. , 2009, The New England journal of medicine.
[19] Jason H. Moore,et al. An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming , 2007, PRIB.
[20] Jason H. Moore,et al. Evaporative cooling feature selection for genotypic data involving interactions , 2007, Bioinform..
[21] Jason H. Moore,et al. Nature-inspired algorithms for the genetic analysis of epistasis in common human diseases: Theoretical assessment of wrapper vs. filter approaches , 2009, 2009 IEEE Congress on Evolutionary Computation.
[22] Marko Robnik-Sikonja,et al. Theoretical and Empirical Analysis of ReliefF and RReliefF , 2003, Machine Learning.
[23] Jason H. Moore,et al. Ant Colony Optimization for Genome-Wide Genetic Analysis , 2008, ANTS Conference.
[24] B. McKinney,et al. Capturing the Spectrum of Interaction Effects in Genetic Association Studies by Simulated Evaporative Cooling Network Analysis , 2009, PLoS genetics.
[25] Scott M. Williams,et al. Shadows of complexity: what biological networks reveal about epistasis and pleiotropy , 2009, BioEssays : news and reviews in molecular, cellular and developmental biology.
[26] Jason H. Moore,et al. The Ubiquitous Nature of Epistasis in Determining Susceptibility to Common Human Diseases , 2003, Human Heredity.
[27] Mark M Iles,et al. What Can Genome-Wide Association Studies Tell Us about the Genetics of Common Disease , 2008, PLoS genetics.