About: ELM: enhanced lowest common ancestor based method for detecting a pathogenic virus from a large sequence dataset

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About: ELM: enhanced lowest common ancestor based method for detecting a pathogenic virus from a large sequence dataset Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	ELM: enhanced lowest common ancestor based method for detecting a pathogenic virus from a large sequence dataset
Creator	Ito, Kimihito Ishii, Akihiro Ueno, Keisuke
Source	Medline; PMC
abstract	BACKGROUND: Emerging viral diseases, most of which are caused by the transmission of viruses from animals to humans, pose a threat to public health. Discovering pathogenic viruses through surveillance is the key to preparedness for this potential threat. Next generation sequencing (NGS) helps us to identify viruses without the design of a specific PCR primer. The major task in NGS data analysis is taxonomic identification for vast numbers of sequences. However, taxonomic identification via a BLAST search against all the known sequences is a computational bottleneck. DESCRIPTION: Here we propose an enhanced lowest-common-ancestor based method (ELM) to effectively identify viruses from massive sequence data. To reduce the computational cost, ELM uses a customized database composed only of viral sequences for the BLAST search. At the same time, ELM adopts a novel criterion to suppress the rise in false positive assignments caused by the small database. As a result, identification by ELM is more than 1,000 times faster than the conventional methods without loss of accuracy. CONCLUSIONS: We anticipate that ELM will contribute to direct diagnosis of viral infections. The web server and the customized viral database are freely available at http://bioinformatics.czc.hokudai.ac.jp/ELM/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2105-15-254) contains supplementary material, which is available to authorized users.
has issue date	2014-07-28(xsd:dateTime)
bibo:doi	10.1186/1471-2105-15-254
bibo:pmid	25069839
has license	cc-by
sha1sum (hex)	fd1910cd1f9847cf0b72bbcf0d94447807c9de66
schema:url	https://doi.org/10.1186/1471-2105-15-254
resource representing a document's title	ELM: enhanced lowest common ancestor based method for detecting a pathogenic virus from a large sequence dataset
has PubMed Central identifier	PMC4124145
has PubMed identifier	25069839
schema:publication	BMC Bioinformatics
resource representing a document's body	covid:fd1910cd1f9847cf0b72bbcf0d94447807c9de66#body_text
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