title: Inference in signal transduction pathways using em algorithm and an implicit algorithm: incomplete data case.
abstract: We summarize here the Implicit statistical inference approach as an alternative to Bayesian networks and we give an effective iterative algorithm analogous to the Expectation Maximization algorithm to infer signal transduction network when the set of data is incomplete. We proved the convergence of our algorithm that we called Implicit algorithm and we apply it to simulated data for a simplified signal transduction pathway of the EGFR protein.
authors.affiliation: Unit of Bioinformatics and Biostatistics, Centre of Biotechnology of Sfax, Sfax, Tunisia.
authors.forename: Hanen Ben
authors.initials: HB
authors.lastname: Hassen
authors.forename: Afif
authors.initials: A
authors.lastname: Masmoudi
authors.forename: Ahmed
authors.initials: A
authors.lastname: Rebai
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D066246:ErbB Receptors / Q000378:metabolism; D006801:Humans; D008954:Models, Biological; D015398:Signal Transduction
chemical_list: C512478:EGFR protein, human; D066246:ErbB Receptors