A computationally fast variable importance test for random forests for high-dimensional data

An experimental study of the intrinsic stability of random forest variable importance measures

(2016) Huazhen Wang et al.   BMC BIOINFORMATICS

Random forest for ordinal responses: Prediction and variable selection

(2016) Silke Janitza et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

r2VIM: A new variable selection method for random forests in genome-wide association studies

(2016) Silke Szymczak et al.   BioData Mining

Cell-of-origin chromatin organization shapes the mutational landscape of cancer

(2015) Paz Polak et al.   NATURE

Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research

(2015) Anne-Laure Boulesteix   PLoS Computational Biology

Predicting phenotypes of asthma and eczema with machine learning

(2014) Mattia CF Prosperi et al.   BMC Medical Genomics

An AUC-based permutation variable importance measure for random forests

(2013) Silke Janitza et al.   BMC BIOINFORMATICS

Statistical interpretation of machine learning-based feature importance scores for biomarker discovery

(2012) Vân Anh Huynh-Thu et al.   BIOINFORMATICS

A new variable selection approach using Random Forests

(2012) A. Hapfelmeier et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Novel biomarkers for pre-diabetes identified by metabolomics

(2012) Rui Wang-Sattler et al.   Molecular Systems Biology

Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations

(2011) A.-L. Boulesteix et al.   BRIEFINGS IN BIOINFORMATICS

Letter to the Editor: On the stability and ranking of predictors from random forest variable importance measures

(2011) K. K. Nicodemus   BRIEFINGS IN BIOINFORMATICS

Power of Data Mining Methods to Detect Genetic Associations and Interactions

(2011) Annette M. Molinaro et al.   HUMAN HEREDITY

On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data

(2010) Daniel F. Schwarz et al.   BIOINFORMATICS

Permutation importance: a corrected feature importance measure

(2010) André Altmann et al.   BIOINFORMATICS

Permutation P-values Should Never Be Zero: Calculating Exact P-values When Permutations Are Randomly Drawn

(2010) Belinda Phipson et al.   Statistical Applications in Genetics and Molecular Biology

Predictor correlation impacts machine learning algorithms: implications for genomic studies

(2009) K. K. Nicodemus et al.   BIOINFORMATICS

Random survival forests

(2008) Hemant Ishwaran et al.   Annals of Applied Statistics

Conditional Variable Importance for Random Forests

(2008) Carolin Strobl et al.   BMC BIOINFORMATICS

Integrated analysis of genetic and proteomic data identifies biomarkers associated with adverse events following smallpox vaccination

(2008) D M Reif et al.   GENES AND IMMUNITY