Title :
Designing artificial organisms for use in biological simulations
Author :
Ashlock, Wendy ; Ashlock, Daniel
Author_Institution :
Dept. of Comput. Sci. & Eng., York Univ. in Toronto, Toronto, ON, Canada
Abstract :
In this paper we investigate two types of artificial organism which have the potential to be useful in biological simulations at the genomic level, such as simulations of speciation or gene interaction. Biological problems of this type are usually studied either with simulations using artificial genes that are merely evolving strings with no phenotype, ignoring the possibly crucial contribution of natural selection, or with real biological data involving so much complexity that it is difficult to sort out the important factors. This research provides a middle ground. The artificial organisms are: gridwalkers (GWs), a variation on the self-avoiding walk problem, and plus-one-recall-store (PORS), a simple genetic programming maximum problem implemented with a context free grammar. Both are known to have rugged multimodal fitness landscapes. We define a new variation operator, a kind of aligned crossover for variable length strings, which we call Smith-Waterman crossover. The problems, using Smith-Waterman crossover, size-neutral crossover (a kind of non-aligned crossover defined in), mutation only, and horizontal gene transfer (such as occurs in biology with retroviruses) are explored. We define a measure called fitness preservation to quantify the differences in their fitness landscapes and to provide guidance to researchers in determining which problem/variation operator set is best for their simulation.
Keywords :
biology computing; context-free grammars; genetic algorithms; genetics; Smith-Waterman crossover; artificial genes; artificial organisms; biological simulations; context free grammar; gene interaction; genetic programming maximum problem; genomic level; gridwalkers; horizontal gene transfer; plus-one-recall-store; rugged multimodal fitness landscapes; self-avoiding walk problem; size-neutral crossover; variable length strings; Biological system modeling; Evolution (biology); Genomics; Grammar; Organisms; Shape;
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9896-3
DOI :
10.1109/CIBCB.2011.5948463