A general model of error-prone PCR


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dc.contributor.author Pritchard, Leighton
dc.contributor.author Corne, D.
dc.contributor.author Kell, Douglas B.
dc.contributor.author Winson, Mike K.
dc.contributor.author Rowland, Jeremy John
dc.date.accessioned 2006-04-24T14:47:16Z
dc.date.available 2006-04-24T14:47:16Z
dc.date.issued 2005-06-21
dc.identifier.citation Pritchard , L , Corne , D , Kell , D B , Winson , M K & Rowland , J J 2005 , ' A general model of error-prone PCR ' Journal of Theoretical Biology , vol 234 , no. 4 , pp. 497-509 . , 10.1016/j.jtbi.2004.12.005 en
dc.identifier.issn 0022-5193
dc.identifier.other PURE: 67963
dc.identifier.other dspace: 2160/124
dc.identifier.uri http://hdl.handle.net/2160/124
dc.identifier.uri http://dbkgroup.org/Papers/JTheoreticalBiology_234_497-509.pdf en
dc.description Pritchard, L., Corne, D., Kell, D.B., Rowland, J. & Winson, M. (2005) A general model of error-prone PCR. Journal of Theoretical Biology 234, 497-509. en
dc.description.abstract In this paper, we generalise a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation of the model to these conditions improves the correspondence to observed and expected behaviours of PCR, and restricts the extent to which the model may explore sequence space for a prescribed set of parameters. Error-prone PCR in realistic reaction conditions is predicted to be less effective at generating grossly divergent sequences than the original model. The estimate of mutation rate per cycle by sampling sequences from an in vitro PCR experiment is correspondingly affected by the choice of model and parameters. en
dc.format.extent 13 en
dc.language.iso eng
dc.relation.ispartof Journal of Theoretical Biology en
dc.subject PCR en
dc.subject Polymerase chain reaction en
dc.subject Error-prone en
dc.subject Model en
dc.title A general model of error-prone PCR en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1016/j.jtbi.2004.12.005
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Bioinformatics and Computational Biology Group en
dc.description.status Peer reviewed en

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