4.5 Article

Revision of Boolean Models of Regulatory Networks Using Stable State Observations

Journal

JOURNAL OF COMPUTATIONAL BIOLOGY
Volume 27, Issue 2, Pages 144-155

Publisher

MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2019.0289

Keywords

Boolean functions; logical formalism; model revision; regulatory networks

Funding

  1. national funds through Fundacao para a Ciencia e a Tecnologia (FCT) [UID/CEC/50021/2019, ERGODiC PTDC/EEI-CTP/2914/2014, SFRH/BSAB/143643/2019, SFRH/BD/130253/2017]
  2. Fundação para a Ciência e a Tecnologia [SFRH/BSAB/143643/2019, SFRH/BD/130253/2017] Funding Source: FCT

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Models of biological regulatory networks are essential to understand cellular processes. However, the definition of such models is still mostly manually performed, and consequently prone to error. Moreover, as new experimental data are acquired, models need to be revised and updated. Here, we propose a model revision procedure and associated tool, capable of providing the set of minimal repairs to render a model consistent with a set of experimental observations. We consider four possible repair operations, using a lexicographic optimization criterion, giving preference to function repairs over topological ones. Also, we consider observations at stable state discarding the model dynamics. In this article, we extend our previous work to tackle the problem of repairing nodes with multiple reasons of inconsistency. We evaluate our tool on five publicly available logical models. We perform random changes considering several parameter configurations to assess the tool repairing capabilities. Whenever a model is repaired under the time limit, the tool successfully produces the optimal solutions to repair the model. Instances were generated without the previous limitation to validate this extended approach.

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