Adaptive und Mutual-Information-basierte Verfahren für eQTL-Studien. - Silke Szymczak (2011)

Risk estimation using probability machines. - Abhijit Dasgupta 003; Silke Szymczak; Jason H. Moore; Joan E. Bailey-Wilson; James D. Malley (BioData Min., 2014)

Variable Selection Method for the Identification of Epistatic Models. - Emily Rose Holzinger; Silke Szymczak; Abhijit Dasgupta 003; James D. Malley; Qing Li; Joan E. Bailey-Wilson (Pacific Symposium on Biocomputing, 2015)

r2VIM: A new variable selection method for random forests in genome-wide association studies. - Silke Szymczak; Emily Rose Holzinger; Abhijit Dasgupta 003; James D. Malley; Anne M. Molloy; James L. Mills; Lawrence C. Brody; Dwight Stambolian; Joan E. Bailey-Wilson (BioData Min., 2016)

Evaluation of variable selection methods for random forests and omics data sets. - Frauke Degenhardt; Stephan Seifert; Silke Szymczak (Briefings Bioinform., 2019)

Surrogate minimal depth as an importance measure for variables in random forests. - Stephan Seifert; Sven Gundlach; Silke Szymczak (Bioinform., 2019)

Integrating biological knowledge and gene expression data using pathway-guided random forests: a benchmarking study. - Stephan Seifert; Sven Gundlach; Olaf Junge; Silke Szymczak; Luigi Martelli (Bioinform., 2020)

A review on longitudinal data analysis with random forest in precision medicine. - Jianchang Hu; Silke Szymczak (CoRR, 2022)

Effect of hyperparameters on variable selection in random forests. - Césaire J. K. Fouodo; Lea L. Kronziel; Inke R. König; Silke Szymczak (CoRR, 2023)

A review on longitudinal data analysis with random forest. - Jianchang Hu; Silke Szymczak (Briefings Bioinform., 2023)

Construction of Artificial Most Representative Trees by Minimizing Tree-Based Distance Measures. - Björn-Hergen Laabs; Lea L. Kronziel; Inke R. König; Silke Szymczak (xAI (2), 2024)

Evaluation of network-guided random forest for disease gene discovery. - Jianchang Hu; Silke Szymczak (BioData Min., 2024)