title: In silico biology.
abstract: Rather than studying existent living systems, we can increasingly produce computer models that capture the salient aspects of life. This provides us with unprecedented opportunities to examine, manipulate, and explore biological phenomena, allowing us to investigate some of the deepest issues in biology.
authors.affiliation: Department of Informatics, University of Sussex Falmer, Brighton, BN1 9RH, United Kingdom.
authors.forename: Chrisantha T
authors.initials: CT
authors.lastname: Fernando
authors.forename: Richard A
authors.initials: RA
authors.lastname: Goldstein
authors.forename: Phil
authors.initials: P
authors.lastname: Husbands
authors.forename: Dov J
authors.initials: DJ
authors.lastname: Stekel
mesh_terms: D044822:Biodiversity; D005075:Biological Evolution; D019295:Computational Biology; D003198:Computer Simulation; D008954:Models, Biological; D058615:Synthetic Biology; D049490:Systems Biology