TY  - JOUR
A1  - Perscheid, Cindy
T1  - Comprior
BT  - Facilitating the implementation and automated benchmarking of prior knowledge-based feature selection approaches on gene expression data sets
JF  - BMC Bioinformatics
N2  - Background
Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness.

Results
We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance.

Conclusion
Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness
KW  - Feature selection
KW  - Prior knowledge
KW  - Gene expression
KW  - Reproducible benchmarking
Y1  - 2021
U6  - https://doi.org/10.1186/s12859-021-04308-z
SN  - 1471-2105
VL  - 22
SP  - 1
EP  - 15
PB  - Springer Nature
CY  - London
ER  -