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SN Computer Science
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November 1, 2021
Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests
Roman Hornung
Plos One
|
August 7, 2018
On the overestimation of random forest's out-of-bag error
Silke Janitza, Roman Hornung
BMC Bioinformatics
|
June 29, 2019
Block Forests: random forests for blocks of clinical and omics covariate data
Roman Hornung, Marvin N Wright
BMC Bioinformatics
|
January 13, 2016
Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment
Roman Hornung, Anne-Laure Boulesteix, David Causeur
BMC Bioinformatics
|
May 4, 2026
ShadowVIMP: permutation-based multiple testing-controlled variable selection
Tim Müller, Roman Hornung, Silke Szymczak, et al.
Genes
|
December 24, 2021
Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study
Yingxia Li, Ulrich Mansmann, Shangming Du, et al.
BMC Medical Informatics and Decision Making
|
September 2, 2024
Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study
Yingxia Li, Tobias Herold, Ulrich Mansmann, et al.
BMC Bioinformatics
|
October 5, 2022
Benchmark study of feature selection strategies for multi-omics data
Yingxia Li, Ulrich Mansmann, Shangming Du, et al.
Bioinformatics (Oxford, England)
|
November 1, 2016
Improving cross-study prediction through addon batch effect adjustment or addon normalization
Roman Hornung, David Causeur, Christoph Bernau, et al.
Briefings in Bioinformatics
|
August 22, 2020
Large-scale benchmark study of survival prediction methods using multi-omics data
Moritz Herrmann, Philipp Probst, Roman Hornung, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 26) with videos related to
Sort By:
Page
of 3
SN Computer Science
|
November 1, 2021
Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests
Roman Hornung
Plos One
|
August 7, 2018
On the overestimation of random forest's out-of-bag error
Silke Janitza, Roman Hornung
BMC Bioinformatics
|
June 29, 2019
Block Forests: random forests for blocks of clinical and omics covariate data
Roman Hornung, Marvin N Wright
BMC Bioinformatics
|
January 13, 2016
Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment
Roman Hornung, Anne-Laure Boulesteix, David Causeur
BMC Bioinformatics
|
May 4, 2026
ShadowVIMP: permutation-based multiple testing-controlled variable selection
Tim Müller, Roman Hornung, Silke Szymczak, et al.
Genes
|
December 24, 2021
Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study
Yingxia Li, Ulrich Mansmann, Shangming Du, et al.
BMC Medical Informatics and Decision Making
|
September 2, 2024
Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study
Yingxia Li, Tobias Herold, Ulrich Mansmann, et al.
BMC Bioinformatics
|
October 5, 2022
Benchmark study of feature selection strategies for multi-omics data
Yingxia Li, Ulrich Mansmann, Shangming Du, et al.
Bioinformatics (Oxford, England)
|
November 1, 2016
Improving cross-study prediction through addon batch effect adjustment or addon normalization
Roman Hornung, David Causeur, Christoph Bernau, et al.
Briefings in Bioinformatics
|
August 22, 2020
Large-scale benchmark study of survival prediction methods using multi-omics data
Moritz Herrmann, Philipp Probst, Roman Hornung, et al.
Page
of 3