GeneNetWeaver:in silicobenchmark generation and performance profiling of network inference methods | Zendy

Thomas Schaffter | Zendy; Daniel Marbach | Zendy; Dario Floreano | Zendy

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GeneNetWeaver:in silicobenchmark generation and performance profiling of network inference methods

Author(s) -

Thomas Schaffter,

Daniel Marbach,

Dario Floreano

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr373

Subject(s) - inference , computer science , benchmark (surveying) , data mining , source code , java , profiling (computer programming) , software , machine learning , artificial intelligence , programming language , geodesy , geography

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks.

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