Robustness and accuracy of functional modules in integrated network analysis | Zendy

Daniela Beißer | Zendy; Stefan Brunkhorst | Zendy; Thomas Dandekar | Zendy; Gunnar W. Klau | Zendy; Marcus Dittrich | Zendy; Tobias Müller | Zendy

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Robustness and accuracy of functional modules in integrated network analysis

Author(s) -

Daniela Beißer,

Stefan Brunkhorst,

Thomas Dandekar,

Gunnar W. Klau,

Marcus Dittrich,

Tobias Müller

Publication year - 2012

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/bts265

Subject(s) - jackknife resampling , computer science , robustness (evolution) , resampling , data mining , artificial intelligence , mathematics , gene , biochemistry , statistics , chemistry , estimator

High-throughput molecular data provide a wealth of information that can be integrated into network analysis. Several approaches exist that identify functional modules in the context of integrated biological networks. The objective of this study is 2-fold: first, to assess the accuracy and variability of identified modules and second, to develop an algorithm for deriving highly robust and accurate solutions.

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