MersV1, Main, Exploration, bibRecord, 000002

eCAMI: simultaneous classification and motif identification for enzyme annotation.

Identifieur interne : 000002 ( Main/Exploration ); précédent : 000001; suivant : 000003

eCAMI: simultaneous classification and motif identification for enzyme annotation.

Auteurs : Jing Xu [République populaire de Chine] ; Han Zhang [République populaire de Chine] ; Jinfang Zheng [États-Unis] ; Philippe Dovoedo [États-Unis] ; Yanbin Yin [États-Unis]

Source :

Bioinformatics (Oxford, England) [ 1367-4811 ] ; 2020.

RBID : pubmed:31794006

Abstract

Carbohydrate-active enzymes (CAZymes) are extremely important to bioenergy, human gut microbiome, and plant pathogen researches and industries. Here we developed a new amino acid k-mer-based CAZyme classification, motif identification and genome annotation tool using a bipartite network algorithm. Using this tool, we classified 390 CAZyme families into thousands of subfamilies each with distinguishing k-mer peptides. These k-mers represented the characteristic motifs (in the form of a collection of conserved short peptides) of each subfamily, and thus were further used to annotate new genomes for CAZymes. This idea was also generalized to extract characteristic k-mer peptides for all the Swiss-Prot enzymes classified by the EC (enzyme commission) numbers and applied to enzyme EC prediction.

DOI: 10.1093/bioinformatics/btz908
PubMed: 31794006

Affiliations:

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eCAMI: simultaneous classification and motif identification for enzyme annotation.

eCAMI: simultaneous classification and motif identification for enzyme annotation.

Source :

Abstract

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