Linked Life Data

19961429

Source:http://linkedlifedata.com/resource/pubmed/id/19961429

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2010-5-27
pubmed:abstractText
The early determination of family for a newly found enzyme molecule becomes important because it is directly related to the detail information about which specific target it acts on, as well as to its catalytic process and biological function. Unfortunately, it is still a hard work to distinguish enzyme classes by experiments. With an enormous amount of protein sequences uncovered in the genome research, it is both challenging and indispensable to develop an automatic method for fast and reliably classifying the enzyme family. Using the concept of Chou's pseudo amino acid composition, we developed a new method that coupled discrete wavelet transform with support vector machine based on the amino acid hydrophobicity to predict enzyme family. The overall success rate obtained by the 10-cross-validation for the identification of the six enzyme families was 91.9%, indicating the current method could be an effective and promising high-throughput method in the enzyme research.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1875-5305
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
715-22
pubmed:dateRevised
2011-3-31
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Using the concept of Chou's pseudo amino acid composition to predict enzyme family classes: an approach with support vector machine based on discrete wavelet transform.
pubmed:affiliation
Department of Chemistry, Nanchang University, Nanchang 330031, China. jdqiu@ncu.edu.cn
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't