Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach
Open Access
- 1 July 2013
- journal article
- Published by Oxford University Press (OUP) in Journal of the American Medical Informatics Association
- Vol. 20 (4) , 603-612
Abstract
Background and objective Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an importKeywords
This publication has 50 references indexed in Scilit:
- GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architecturesBioData Mining, 2012
- Missing heritability and strategies for finding the underlying causes of complex diseaseNature Reviews Genetics, 2010
- Bioinformatics challenges for genome-wide association studiesBioinformatics, 2010
- Finding the missing heritability of complex diseasesNature, 2009
- Exploring the Performance of Multifactor Dimensionality Reduction in Large Scale SNP Studies and in the Presence of Genetic Heterogeneity among Epistatic Disease ModelsHuman Heredity, 2008
- Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysisBMC Genomic Data, 2008
- Confronting complexity in late‐onset Alzheimer disease: application of two‐stage analysis approach addressing heterogeneity and epistasisGenetic Epidemiology, 2007
- A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reductionGenetic Epidemiology, 2007
- Power of multifactor dimensionality reduction for detecting gene‐gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneityGenetic Epidemiology, 2003
- A Combinatorial Partitioning Method to Identify Multilocus Genotypic Partitions That Predict Quantitative Trait VariationGenome Research, 2001