| Literature DB >> 29255991 |
Alejandro Peña1, Francesco Del Carratore1, Matthew Cummings1, Eriko Takano1, Rainer Breitling2.
Abstract
The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.Entities:
Keywords: BGC; Genomics; Natural products; Prioritisation; Synthetic biology
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Year: 2017 PMID: 29255991 DOI: 10.1007/s10295-017-1993-1
Source DB: PubMed Journal: J Ind Microbiol Biotechnol ISSN: 1367-5435 Impact factor: 3.346