Related references
Note: Only part of the references are listed.The revival of the Gini importance?
Stefano Nembrini et al.
BIOINFORMATICS (2018)
Genome-wide two-locus interaction analysis identifies multiple epistatic SNP pairs that confer risk of prostate cancer: A cross-population study
Jiawei Shen et al.
INTERNATIONAL JOURNAL OF CANCER (2017)
PMLB: a large benchmark suite for machine learning evaluation and comparison
Randal S. Olson et al.
BIODATA MINING (2017)
Do little interactions get lost in dark random forests?
Marvin N. Wright et al.
BMC BIOINFORMATICS (2016)
Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium
Timothy J. Hohman et al.
NEUROBIOLOGY OF AGING (2016)
Detecting gene-gene interactions using a permutation-based random forest method
Jing Li et al.
BIODATA MINING (2016)
Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
Alex Goldstein et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2015)
A random forest approach to capture genetic effects in the presence of population structure
Johannes Stephan et al.
NATURE COMMUNICATIONS (2015)
A survey about methods dedicated to epistasis detection
Clément Niel et al.
Frontiers in Genetics (2015)
Identification of Novel Genetic Models of Glaucoma Using the EMERGENT Genetic Programming-Based Artificial Intelligence System
Jason H. Moore et al.
GENETIC PROGRAMMING THEORY AND PRACTICE XII (2015)
A genome-wide gene-gene interaction analysis identifies an epistatic gene pair for lung cancer susceptibility in Han Chinese
Minjie Chu et al.
CARCINOGENESIS (2014)
Why epistasis is important for tackling complex human disease genetics
Trudy F. C. Mackay et al.
GENOME MEDICINE (2014)
ViSEN: Methodology and Software for Visualization of Statistical Epistasis Networks
Ting Hu et al.
GENETIC EPIDEMIOLOGY (2013)
An information-gain approach to detecting three-way epistatic interactions in genetic association studies
Ting Hu et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2013)
An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data
Christoph Lippert et al.
SCIENTIFIC REPORTS (2013)
A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology
Ching Lee Koo et al.
BIOMED RESEARCH INTERNATIONAL (2013)
Genome-Wide Association Scan Allowing for Epistasis in Type 2 Diabetes
Jordana T. Bell et al.
ANNALS OF HUMAN GENETICS (2011)
Random Forests for Genetic Association Studies
Benjamin A. Goldstein et al.
STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY (2011)
Bioinformatics challenges for genome-wide association studies
Jason H. Moore et al.
BIOINFORMATICS (2010)
Permutation importance: a corrected feature importance measure
Andre Altmann et al.
BIOINFORMATICS (2010)
Feasible and Successful: Genome-Wide Interaction Analysis Involving All 1.9 x 10(11) Pair-Wise Interaction Tests
Michael Steffens et al.
HUMAN HEREDITY (2010)
A random forest approach to the detection of epistatic interactions in case-control studies
Rui Jiang et al.
BMC BIOINFORMATICS (2009)
Genome-wide association reveals three SNPs associated with sporadic amyotrophic lateral sclerosis through a two-locus analysis
Qiuying Sha et al.
BMC MEDICAL GENETICS (2009)
Epistasis - the essential role of gene interactions in the structure and evolution of genetic systems
Patrick C. Phillips
NATURE REVIEWS GENETICS (2008)
Bias in random forest variable importance measures: Illustrations, sources and a solution
Carolin Strobl et al.
BMC BIOINFORMATICS (2007)
A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility
Jason H. Moore et al.
JOURNAL OF THEORETICAL BIOLOGY (2006)
Traversing the conceptual divide between biological and statistical epistasis: Systems biology and a more modern synthesis
JH Moore et al.
BIOESSAYS (2005)
Epistasis:: too often neglected in complex trait studies?
Ö Carlborg et al.
NATURE REVIEWS GENETICS (2004)
The ubiquitous nature of epistasis in determining susceptibility to common human diseases
JH Moore
HUMAN HEREDITY (2003)
Share Paper
