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  Designing optimal experiments to discriminate interaction graph models

Thiele, S., Heise, S., Hessenkemper, W., Bongartz, H., Fensky, M., Schaper, F., et al. (2019). Designing optimal experiments to discriminate interaction graph models. IEEE ACM Transactions on Computational Biology and Bioinformatics, 16(3), 925-935. doi:10.1109/TCBB.2018.2812184.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-F89E-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-E095-7
Genre: Journal Article

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This work is licensed under a Creative Commons Attribution 3.0 License.

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 Creators:
Thiele, Sven1, Author              
Heise, Sandra1, Author              
Hessenkemper, Wiebke2, Author
Bongartz, Hannes2, Author
Fensky, Melissa3, Author
Schaper, Fred2, Author
Klamt, Steffen1, Author              
Affiliations:
1Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              
2Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              
3IDT Biologika, Dessau-Roßlau, Germany, ou_persistent22              

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Language(s): eng - English
 Dates: 2019
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1109/TCBB.2018.2812184
Other: data_escidoc:2566695
 Degree: -

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Title: IEEE ACM Transactions on Computational Biology and Bioinformatics
Source Genre: Journal
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Publ. Info: New York, NY : IEEE Computer Society
Pages: - Volume / Issue: 16 (3) Sequence Number: - Start / End Page: 925 - 935 Identifier: ISSN: 1545-5963
CoNE: /journals/resource/111098975410000