Web Resources for Metagenomics Studies
Identifieur interne : 000056 ( Main/Merge ); précédent : 000055; suivant : 000057Web Resources for Metagenomics Studies
Auteurs : Pravin Dudhagara [Inde] ; Sunil Bhavsar [Inde] ; Chintan Bhagat [Inde] ; Anjana Ghelani [Inde] ; Shreyas Bhatt [Inde] ; Rajesh Patel [Inde]Source :
- Genomics, Proteomics & Bioinformatics [ 1672-0229 ] ; 2015.
Abstract
The development of next-generation sequencing (NGS) platforms spawned an enormous volume of data. This explosion in data has unearthed new scalability challenges for existing bioinformatics tools. The analysis of metagenomic sequences using bioinformatics pipelines is complicated by the substantial complexity of these data. In this article, we review several commonly-used online tools for
Url:
DOI: 10.1016/j.gpb.2015.10.003
PubMed: 26602607
PubMed Central: 4678780
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Web Resources for Metagenomics Studies</title>
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<author><name sortKey="Bhavsar, Sunil" sort="Bhavsar, Sunil" uniqKey="Bhavsar S" first="Sunil" last="Bhavsar">Sunil Bhavsar</name>
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<author><name sortKey="Bhagat, Chintan" sort="Bhagat, Chintan" uniqKey="Bhagat C" first="Chintan" last="Bhagat">Chintan Bhagat</name>
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<author><name sortKey="Patel, Rajesh" sort="Patel, Rajesh" uniqKey="Patel R" first="Rajesh" last="Patel">Rajesh Patel</name>
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<series><title level="j">Genomics, Proteomics & Bioinformatics</title>
<idno type="ISSN">1672-0229</idno>
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<front><div type="abstract" xml:lang="en"><p>The development of next-generation sequencing (NGS) platforms spawned an enormous volume of data. This explosion in data has unearthed new scalability challenges for existing bioinformatics tools. The analysis of metagenomic sequences using bioinformatics pipelines is complicated by the substantial complexity of these data. In this article, we review several commonly-used online tools for <bold>metagenomics</bold>
data analysis with respect to their quality and detail of analysis using simulated <bold>metagenomics</bold>
data. There are at least a dozen such <bold>software tools</bold>
presently available in the public domain. Among them, MGRAST, IMG/M, and METAVIR are the most well-known tools according to the number of citations by peer-reviewed scientific media up to mid-2015. Here, we describe 12 online tools with respect to their web link, annotation pipelines, clustering methods, online user support, and availability of data storage. We have also done the rating for each tool to screen more potential and preferential tools and evaluated five best tools using <bold>synthetic metagenome</bold>
. The article comprehensively deals with the contemporary problems and the prospects of <bold>metagenomics</bold>
from a bioinformatics viewpoint.</p>
</div>
</front>
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</back>
</TEI>
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