title: A case study where biology inspired a solution to a computer science problem.
abstract: This paper describes how the biological theory of gene duplication described in Susumu Ohno's provocative book, Evolution by Means of Gene Duplication, was brought to bear on a vexatious problem from the domain of automated machine learning, namely the problem of architecture discovery. Six new architecture-altering operations for genetic programming were motivated by the way that new biological structures, functions, and behaviors arise in nature using gene duplication. Genetic programming with the new architecture-altering operations was then applied to the transmembrane protein segment identification problem. The out-of-sample error rate for the best genetically-evolved program achieved was slightly better than that of previously-reported human-written algorithms for this problem.
authors.affiliation: Computer Science Department, Stanford University, CA 94305, USA. Koza@CS.Stanford.Edu
authors.forename: J R
authors.initials: JR
authors.lastname: Koza
authors.forename: D
authors.initials: D
authors.lastname: Andre
mesh_terms: D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D017353:Gene Deletion; D008957:Models, Genetic; D005810:Multigene Family; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000235:genetics*; D012641:Selection, Genetic; D012984:Software
chemical_list: D011506:Proteins