Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 536561
Title Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
Author(s) Medema, Marnix H.
Source mSystems 3 (2018)2. - ISSN 2379-5077
DOI http://dx.doi.org/10.1128/mSystems.00182-17
Department(s) Bioinformatics
EPS
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) Bioinformatics - Biosynthetic gene cluster - Microbiome - Natural products - Specialized metabolism
Abstract Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pan-genomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting.
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