Modeling and optimization of dna recombination

Gregory L. Moore, Costas D. Maranas, Kevin R. Gutshall, Jean E. Brenchley

Research output: Contribution to journalConference articlepeer-review

10 Scopus citations


This paper discusses predictive models for quantifying the outcome of DNA recombination employed in directed evolution experiments for the generation of novel enzymes. Specifically, predictive models are outlined for (i) tracking the DNA fragment size distribution after random fragmentation and subsequent assembly into genes of full length and (ii) estimating the fraction of the assembled full length sequences matching a given nucleotide target. Based on these quantitative models, optimization formulations are constructed which are aimed at identifying the optimal recombinatory length and parent sequences for maximizing the assembly of a sought after sequence target. Computational results show that the recombination outcome is a 'complex' function of the recombinatory length and recombined sequences and illustrate the magnitude of improvements that can be realized. (C) 2000 Elsevier Science Ltd.

Original languageEnglish (US)
Pages (from-to)693-699
Number of pages7
JournalComputers and Chemical Engineering
Issue number2-7
StatePublished - Jul 15 2000
Event7th International Symposium on Process Systems Engineering - Keystone, CO, USA
Duration: Jul 16 2000Jul 21 2000

All Science Journal Classification (ASJC) codes

  • General Chemical Engineering
  • Computer Science Applications


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