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  Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models

Steinke, F., Seeger, M., & Tsuda, K. (2007). Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models. BMC Systems Biology, 1: 51, pp. 1-15. doi:10.1186/1752-0509-1-51.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CB09-A Version Permalink: http://hdl.handle.net/21.11116/0000-0003-BB14-4
Genre: Journal Article

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 Creators:
Steinke, F1, 2, Author              
Seeger, M1, 2, Author              
Tsuda, K1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Dates: 2007-11
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1186/1752-0509-1-51
BibTex Citekey: 4810
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Title: BMC Systems Biology
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 1 Sequence Number: 51 Start / End Page: 1 - 15 Identifier: ISSN: 1752-0509
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000225260