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  Inferring cellular networks – a review.

Markowetz, F., & Spang, R. (2007). Inferring cellular networks – a review. BMC Bioinformatics, 8(Suppl 6), S5-S5. doi:10.1186/1471-2105-8-S6-S5.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8167-C Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8168-A
Genre: Journal Article
Alternative Title : BMC Bioinformatics

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1471-2105-8-S6-S5.pdf (Any fulltext), 503KB
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 Creators:
Markowetz, Florian1, Author
Spang, Rainer2, Author              
Affiliations:
1Max Planck Society, ou_persistent13              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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 Abstract: In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations.

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Language(s): eng - English
 Dates: 2007-09-27
 Publication Status: Published in print
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Title: BMC Bioinformatics
  Alternative Title : BMC Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 8 (Suppl 6) Sequence Number: - Start / End Page: S5 - S5 Identifier: ISSN: 1471-2105