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Signal Processing for Metagenomics: Extracting Information from the Soup

Identifieur interne : 000B82 ( Main/Exploration ); précédent : 000B81; suivant : 000B83

Signal Processing for Metagenomics: Extracting Information from the Soup

Auteurs : Gail L. Rosen [États-Unis] ; Bahrad A. Sokhansanj [États-Unis] ; Robi Polikar [États-Unis] ; Mary Ann Bruns [États-Unis] ; Jacob Russell [États-Unis] ; Elaine Garbarine [États-Unis] ; Steve Essinger [États-Unis] ; Non Yok [États-Unis]

Source :

RBID : PMC:2808676

Abstract

Traditionally, studies in microbial genomics have focused on single-genomes from cultured species, thereby limiting their focus to the small percentage of species that can be cultured outside their natural environment. Fortunately, recent advances in high-throughput sequencing and computational analyses have ushered in the new field of metagenomics, which aims to decode the genomes of microbes from natural communities without the need for cultivation. Although metagenomic studies have shed a great deal of insight into bacterial diversity and coding capacity, several computational challenges remain due to the massive size and complexity of metagenomic sequence data. Current tools and techniques are reviewed in this paper which address challenges in 1) genomic fragment annotation, 2) phylogenetic reconstruction, 3) functional classification of samples, and 4) interpreting complementary metaproteomics and metametabolomics data. Also surveyed are important applications of metagenomic studies, including microbial forensics and the roles of microbial communities in shaping human health and soil ecology.


Url:
DOI: 10.2174/138920209789208255
PubMed: 20436876
PubMed Central: 2808676


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<li>University Park (Pennsylvanie)</li>
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