Essential Guidelines for Computational Method Benchmarking
MCML Authors
Anne-Laure Boulesteix
Prof. Dr.
Principal Investigator
Abstract
Anne-Laure Boulesteix
Prof. Dr.
Principal Investigator
Abstract
In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.
article
Genome Biology
20.125. Jun. 2019.
Authors
L. M. Weber • W. Saelens • R. Cannoodt • C. Soneson • A. Hapfelmeier • P. P. Gardner • A.-L. Boulesteix • Y. Saeys • M. D. RobinsonLinks
DOIResearch Area
BibTeXKey: WSC+19