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Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments

Xulvi-Brunet, R, Campbell, GW, Rajamani, S, Jimenez, JI and Chen, IA (2016) Computational analysis of fitness landscapes and evolutionary networks from in vitro evolution experiments Methods, 106. pp. 86-96.

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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.

Item Type: Article
Subjects : Biosciences
Divisions : Faculty of Health and Medical Sciences > School of Biosciences and Medicine
Authors :
AuthorsEmailORCID
Xulvi-Brunet, RUNSPECIFIEDUNSPECIFIED
Campbell, GWUNSPECIFIEDUNSPECIFIED
Rajamani, SUNSPECIFIEDUNSPECIFIED
Jimenez, JIUNSPECIFIEDUNSPECIFIED
Chen, IAUNSPECIFIEDUNSPECIFIED
Date : 19 May 2016
Identification Number : 10.1016/j.ymeth.2016.05.012
Copyright Disclaimer : © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords : In vitro evolution, RNA selection, fitness landscape
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 02 Jun 2016 07:45
Last Modified : 27 Oct 2016 12:27
URI: http://epubs.surrey.ac.uk/id/eprint/810899

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