ArticleBMC bioinformatics2006
STAR: predicting recombination sites from amino acid sequence.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Improvement of thermal stability via outer-loop ion pair interaction of mutated T1 lipase from Geobacillus zalihae strain T1.International journal of molecular sciences · 2012Article
- Random dissection to select for protein split sites and its application in protein fragment complementation.Protein science : a publication of the Protein Society · 2009Article
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Authors and funding
4 authors.
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Abstract
backgroundDesigning novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone.
resultsWe present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89).
conclusionSTAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.
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