Experimental design for inference over the A. thaliana circadian clock network

Daniel Trejo-Banos; Andrew J. Millar; Guido Sanguinetti

doi:10.1007/978-3-319-23401-4_4

Experimental design for inference over the A. thaliana circadian clock network

Daniel Trejo-Banos, Andrew J. Millar, Guido Sanguinetti

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Planning experiments is a crucial step in successful investigations, which can greatly benefit from computational modeling approaches. Here we consider the problem of designing informative experiments for elucidating the dynamics of biological networks. Our approach extends previously proposed methodologies to the important case where the structure of the network is also uncertain. We demonstrate our approach on a benchmark scenario in plant biology, the circadian clock network of Arabidopsis thaliana, and discuss the different value of three types of commonly used experiments in terms of aiding the reconstruction of the unknown network

Original language	English
Title of host publication	Computational Methods in Systems Biology
Subtitle of host publication	13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings
Publisher	Springer International Publishing
Pages	28-39
Number of pages	12
ISBN (Electronic)	978-3-319-23401-4
ISBN (Print)	978-3-319-23400-7
DOIs	https://doi.org/10.1007/978-3-319-23401-4_4
Publication status	Published - 2015

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer International Publishing
Volume	9308
ISSN (Print)	0302-9743

Access to Document

10.1007/978-3-319-23401-4_4

cmsb_clocks_16_06_GSAccepted author manuscript, 512 KB

http://link.springer.com/chapter/10.1007%2F978-3-319-23401-4_4

MLCS - Machine learning for computational science statistical and formal modeling of biological systems
Sanguinetti, G.
EU government bodies
1/10/12 → 30/09/17
Project: Research

Cite this

Trejo-Banos, D., Millar, A. J., & Sanguinetti, G. (2015). Experimental design for inference over the A. thaliana circadian clock network. In Computational Methods in Systems Biology: 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings (pp. 28-39). (Lecture Notes in Computer Science; Vol. 9308). Springer International Publishing. https://doi.org/10.1007/978-3-319-23401-4_4

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title = "Experimental design for inference over the A. thaliana circadian clock network",

abstract = "Planning experiments is a crucial step in successful investigations, which can greatly benefit from computational modeling approaches. Here we consider the problem of designing informative experiments for elucidating the dynamics of biological networks. Our approach extends previously proposed methodologies to the important case where the structure of the network is also uncertain. We demonstrate our approach on a benchmark scenario in plant biology, the circadian clock network of Arabidopsis thaliana, and discuss the different value of three types of commonly used experiments in terms of aiding the reconstruction of the unknown network",

author = "Daniel Trejo-Banos and Millar, {Andrew J.} and Guido Sanguinetti",

year = "2015",

doi = "10.1007/978-3-319-23401-4_4",

language = "English",

isbn = "978-3-319-23400-7",

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publisher = "Springer International Publishing",

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Trejo-Banos, D, Millar, AJ & Sanguinetti, G 2015, Experimental design for inference over the A. thaliana circadian clock network. in Computational Methods in Systems Biology: 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings. Lecture Notes in Computer Science, vol. 9308, Springer International Publishing, pp. 28-39. https://doi.org/10.1007/978-3-319-23401-4_4

Experimental design for inference over the A. thaliana circadian clock network. / Trejo-Banos, Daniel; Millar, Andrew J.; Sanguinetti, Guido.
Computational Methods in Systems Biology: 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings. Springer International Publishing, 2015. p. 28-39 (Lecture Notes in Computer Science; Vol. 9308).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Experimental design for inference over the A. thaliana circadian clock network

AU - Trejo-Banos, Daniel

AU - Millar, Andrew J.

AU - Sanguinetti, Guido

PY - 2015

Y1 - 2015

N2 - Planning experiments is a crucial step in successful investigations, which can greatly benefit from computational modeling approaches. Here we consider the problem of designing informative experiments for elucidating the dynamics of biological networks. Our approach extends previously proposed methodologies to the important case where the structure of the network is also uncertain. We demonstrate our approach on a benchmark scenario in plant biology, the circadian clock network of Arabidopsis thaliana, and discuss the different value of three types of commonly used experiments in terms of aiding the reconstruction of the unknown network

AB - Planning experiments is a crucial step in successful investigations, which can greatly benefit from computational modeling approaches. Here we consider the problem of designing informative experiments for elucidating the dynamics of biological networks. Our approach extends previously proposed methodologies to the important case where the structure of the network is also uncertain. We demonstrate our approach on a benchmark scenario in plant biology, the circadian clock network of Arabidopsis thaliana, and discuss the different value of three types of commonly used experiments in terms of aiding the reconstruction of the unknown network

U2 - 10.1007/978-3-319-23401-4_4

DO - 10.1007/978-3-319-23401-4_4

M3 - Conference contribution

SN - 978-3-319-23400-7

T3 - Lecture Notes in Computer Science

SP - 28

EP - 39

BT - Computational Methods in Systems Biology

PB - Springer International Publishing

ER -

Trejo-Banos D, Millar AJ, Sanguinetti G. Experimental design for inference over the A. thaliana circadian clock network. In Computational Methods in Systems Biology: 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings. Springer International Publishing. 2015. p. 28-39. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-23401-4_4

Experimental design for inference over the A. thaliana circadian clock network

Abstract / Description of output

Publication series

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Projects

MLCS - Machine learning for computational science statistical and formal modeling of biological systems

Cite this