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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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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: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1109/TCBB.2018.2812184
Other: pubdata_escidoc:2566695
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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: https://pure.mpg.de/cone/journals/resource/111098975410000