title: Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.
abstract: Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.
authors.affiliation: Dept. of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Mitsos
authors.forename: Ioannis N
authors.initials: IN
authors.lastname: Melas
authors.forename: Melody K
authors.initials: MK
authors.lastname: Morris
authors.forename: Julio
authors.initials: J
authors.lastname: Saez-Rodriguez
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Lauffenburger
authors.forename: Leonidas G
authors.initials: LG
authors.lastname: Alexopoulos
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017143:Fuzzy Logic; D022781:Hepatocytes / Q000378:metabolism*; D006801:Humans; D007257:Information Theory; D008954:Models, Biological; D017711:Nonlinear Dynamics; D010750:Phosphoproteins / Q000378:metabolism*; D061251:Primary Cell Culture; D025941:Protein Interaction Mapping; D020543:Proteome; D015398:Signal Transduction
chemical_list: D010750:Phosphoproteins; D020543:Proteome