title: Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.
abstract: BACKGROUND
  Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters.
  
  
  RESULTS
  In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
  
  
  BACKGROUND
  julio@iim.csic.es or saezrodriguez@ebi.ac.uk.
authors.affiliation: Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, C/Eduardo Cabello 6, 36208 Vigo, Spain, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal and European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, C/Eduardo Cabello 6, 36208 Vigo, Spain, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal and European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: David
authors.initials: D
authors.lastname: Henriques
authors.affiliation: Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, C/Eduardo Cabello 6, 36208 Vigo, Spain, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal and European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Miguel
authors.initials: M
authors.lastname: Rocha
authors.affiliation: Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, C/Eduardo Cabello 6, 36208 Vigo, Spain, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal and European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Julio
authors.initials: J
authors.lastname: Saez-Rodriguez
authors.affiliation: Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, C/Eduardo Cabello 6, 36208 Vigo, Spain, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal and European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Julio R
authors.initials: JR
authors.lastname: Banga
mesh_terms: D000465:Algorithms; D001419:Bacteria; D003198:Computer Simulation; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics*; D008128:Logic; D008954:Models, Biological; D015233:Models, Statistical; D015398:Signal Transduction; D049490:Systems Biology / Q000379:methods / Q000592:standards*