Abstract

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.
Original languageUndefined
Title of host publicationProceedings 1st International Workshop on Synthesis of Continuous Parameters
EditorsÉtienne André, Goran Frehse
PublisherOpen Publishing Association
Pages35-47
Number of pages13
DOIs
StatePublished - 8 Apr 2014

Publication series

NameElectronic Proceedings in Theoretical Computer Science
PublisherOpen Publishing Association
Volume145
ISSN (Print)2075-2180
ISSN (Electronic)2075-2180

Fingerprint

Topology
Genes

Keywords

  • signal transduction
  • EWI-24659
  • Experimental data
  • Computational modeling
  • IR-91060
  • METIS-304060
  • FMT-TOOLS
  • parameter synthesis
  • biological networks

Cite this

Schivo, S., Scholma, J., Karperien, H. B. J., Post, J. N., van de Pol, J. C., & Langerak, R. (2014). Setting Parameters for Biological Models With ANIMO. In É. André, & G. Frehse (Eds.), Proceedings 1st International Workshop on Synthesis of Continuous Parameters (pp. 35-47). (Electronic Proceedings in Theoretical Computer Science; Vol. 145). Open Publishing Association. DOI: 10.4204/EPTCS.145.5

Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus / Setting Parameters for Biological Models With ANIMO.

Proceedings 1st International Workshop on Synthesis of Continuous Parameters. ed. / Étienne André; Goran Frehse. Open Publishing Association, 2014. p. 35-47 (Electronic Proceedings in Theoretical Computer Science; Vol. 145).

Research output: Scientific - peer-reviewConference contribution

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keywords = "signal transduction, EWI-24659, Experimental data, Computational modeling, IR-91060, METIS-304060, FMT-TOOLS, parameter synthesis, biological networks",
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Schivo, S, Scholma, J, Karperien, HBJ, Post, JN, van de Pol, JC & Langerak, R 2014, Setting Parameters for Biological Models With ANIMO. in É André & G Frehse (eds), Proceedings 1st International Workshop on Synthesis of Continuous Parameters. Electronic Proceedings in Theoretical Computer Science, vol. 145, Open Publishing Association, pp. 35-47. DOI: 10.4204/EPTCS.145.5

Setting Parameters for Biological Models With ANIMO. / Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus.

Proceedings 1st International Workshop on Synthesis of Continuous Parameters. ed. / Étienne André; Goran Frehse. Open Publishing Association, 2014. p. 35-47 (Electronic Proceedings in Theoretical Computer Science; Vol. 145).

Research output: Scientific - peer-reviewConference contribution

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AB - ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.

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PB - Open Publishing Association

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Schivo S, Scholma J, Karperien HBJ, Post JN, van de Pol JC, Langerak R. Setting Parameters for Biological Models With ANIMO. In André É, Frehse G, editors, Proceedings 1st International Workshop on Synthesis of Continuous Parameters. Open Publishing Association. 2014. p. 35-47. (Electronic Proceedings in Theoretical Computer Science). Available from, DOI: 10.4204/EPTCS.145.5