title: Simultaneous structure discovery and parameter estimation in gene networks using a multi-objective GP-PSO hybrid approach.
abstract: This paper presents a hybrid algorithm based on Genetic Programming (GP) and Particle Swarm Optimisation (PSO) for the automated recovery of gene network structure. It uses gene expression time series data as well as phenotypic data pertaining to plant flowering time as its input data. The algorithm then attempts to discover simple structures to approximate the plant gene regulatory networks that produce model gene expressions and flowering times that closely resemble the input data. To show the efficacy of the proposed approach, simulation results applied to flowering time control in Arabidopsis thaliana are demonstrated and discussed.
authors.affiliation: Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66502, USA. xinye@ksu.edu
authors.forename: Xinye
authors.initials: X
authors.lastname: Cai
authors.forename: Praveen
authors.initials: P
authors.lastname: Koduru
authors.forename: Sanjoy
authors.initials: S
authors.lastname: Das
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Welch
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks / Q000235:genetics*