Positive and negative forms of replicability in gene network analysis | Zendy

Wim Verleyen | Zendy; Sara Ballouz | Zendy; Jesse Gillis | Zendy

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Positive and negative forms of replicability in gene network analysis

Author(s) -

Wim Verleyen,

Sara Ballouz,

Jesse Gillis

Publication year - 2015

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/btv734

Subject(s) - overfitting , computer science , correctness , data mining , replication (statistics) , sampling (signal processing) , source code , machine learning , function (biology) , field (mathematics) , artificial intelligence , algorithm , statistics , biology , mathematics , genetics , filter (signal processing) , artificial neural network , pure mathematics , computer vision , operating system

Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility that this may lead to overfitting in the field as a whole.

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