Revealing differences in gene network inference algorithms on the network level by ensemble methods | Zendy

Gökmen Altay | Zendy; Frank EmmertStreib | Zendy

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Revealing differences in gene network inference algorithms on the network level by ensemble methods

Author(s) -

Gökmen Altay,

Frank EmmertStreib

Publication year - 2010

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/btq259

Subject(s) - inference , computer science , context (archaeology) , causal inference , gene regulatory network , interpretation (philosophy) , statistical inference , machine learning , data mining , artificial intelligence , algorithm , econometrics , mathematics , statistics , gene , gene expression , biology , paleontology , biochemistry , programming language

The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

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