Setting Parameters for Biological Models With ANIMO

Stefano Schivo, Jetse Scholma, Hermanus Bernardus Johannes Karperien, Janine Nicole Post, Jan Cornelis van de Pol, Romanus Langerak*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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 languageEnglish
Title of host publicationProceedings 1st International Workshop on Synthesis of Continuous Parameters
Subtitle of host publicationSynCoP'14
EditorsÉtienne André, Goran Frehse
PublisherOpen Publishing Association
Pages35-47
Number of pages13
DOIs
Publication statusPublished - 8 Apr 2014
Externally publishedYes
Event1st International Workshop on Synthesis of Continuous Parameters - Grenoble, France
Duration: 6 Apr 20146 Apr 2014
Conference number: 1
https://lipn.univ-paris13.fr/SynCoP2014/

Publication series

SeriesElectronic proceedings in theoretical computer science
ISSN2075-2180

Workshop

Workshop1st International Workshop on Synthesis of Continuous Parameters
Abbreviated titleSynCoP 2014
CountryFrance
CityGrenoble
Period6/04/146/04/14
Internet address

Keywords

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

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