title: Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments.
abstract: In vitro selection experiments in biochemistry allow for the discovery of novel molecules capable of specific desired biochemical functions. However, this is not the only benefit we can obtain from such selection experiments. Since selection from a random library yields an unprecedented, and sometimes comprehensive, view of how a particular biochemical function is distributed across sequence space, selection experiments also provide data for creating and analyzing molecular fitness landscapes, which directly map function (phenotypes) to sequence information (genotypes). Given the importance of understanding the relationship between sequence and functional activity, reliable methods to build and analyze fitness landscapes are needed. Here, we present some statistical methods to extract this information from pools of RNA molecules. We also provide new computational tools to construct and study molecular fitness landscapes.
authors.affiliation: Departamento de Física, Facultad de Ciencias, Escuela Politécnica Nacional, Quito, Ecuador; Department of Chemistry and Biochemistry, Program in Biomolecular Science and Engineering, University of California, Santa Barbara, USA. Electronic address: ramon.xulvi@epn.edu.ec.
authors.forename: Ramon
authors.initials: R
authors.lastname: Xulvi-Brunet
authors.affiliation: Department of Chemistry and Biochemistry, Program in Biomolecular Science and Engineering, University of California, Santa Barbara, USA.
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Campbell
authors.affiliation: Indian Institute of Science Education and Research, Pune, India.
authors.forename: Sudha
authors.initials: S
authors.lastname: Rajamani
authors.affiliation: Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
authors.forename: José I
authors.initials: JI
authors.lastname: Jiménez
authors.affiliation: Department of Chemistry and Biochemistry, Program in Biomolecular Science and Engineering, University of California, Santa Barbara, USA. Electronic address: chen@chem.ucsb.edu.
authors.forename: Irene A
authors.initials: IA
authors.lastname: Chen
mesh_terms: D019020:Directed Molecular Evolution; D056084:Genetic Fitness; D005838:Genotype; D010641:Phenotype; D012313:RNA / Q000235:genetics*
chemical_list: D012313:RNA
keywords: Fitness landscape; In vitro evolution; RNA selection