Revisiting the training of logic models of protein signaling networks with ASP

S. Videla, C. Guziolowski, F. Eduati, S. Thiele, N. Grabe, J. Saez-Rodriguez, A. Siegel

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

11 Citations (Scopus)

Abstract

A fundamental question in systems biology is the construction and training to data of mathematical models. Logic formalisms have become very popular to model signaling networks because their simplicity allows us to model large systems encompassing hundreds of proteins. An approach to train (Boolean) logic models to high-throughput phospho-proteomics data was recently introduced and solved using optimization heuristics based on stochastic methods. Here we demonstrate how this problem can be solved using Answer Set Programming (ASP), a declarative problem solving paradigm, in which a problem is encoded as a logical program such that its answer sets represent solutions to the problem. ASP has significant improvements over heuristic methods in terms of efficiency and scalability, it guarantees global optimality of solutions as well as provides a complete set of solutions. We illustrate the application of ASP with in silico cases based on realistic networks and data.

Original languageEnglish
Title of host publicationComputational Methods in Systems Biology - 10th International Conference, CMSB 2012, Proceedings
Pages342-361
Number of pages20
Volume7605 LNBI
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event10th International Conference on Computational Methods in Systems Biology, CMSB 2012 - London, United Kingdom
Duration: 3 Oct 20125 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7605
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Computational Methods in Systems Biology, CMSB 2012
Country/TerritoryUnited Kingdom
CityLondon
Period3/10/125/10/12

Keywords

  • answer set programming
  • Logic modeling
  • protein signaling networks

Fingerprint

Dive into the research topics of 'Revisiting the training of logic models of protein signaling networks with ASP'. Together they form a unique fingerprint.

Cite this