Linked Life Data

19783671

Source:http://linkedlifedata.com/resource/pubmed/id/19783671

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2009-10-20
pubmed:abstractText
Palmitoylation is an important hydrophobic protein modification activity that participates many cellular processes, including signaling, neuronal transmission, membrane trafficking and so on. So it is an important problem to identify palmitoylated proteins and the corresponding sites. Comparing with the expensive and time-consuming biochemical experiments, the computational methods have attracted much attention due to their good performances in predicting palmitoylation sites. In this paper, we develop a novel automated computational method to perform this work. For a sequence segment in a given protein, the encoding scheme based on the composition of k-spaced amino acid pairs (CKSAAP) is introduced, and then the support vector machine is used as the predictor. The proposed prediction model CKSAAP-Palm outperforms the existing method CSS-Palm2.0 on both cross-validation experiments and some independent testing data sets. These results imply that our CKSAAP-Palm is able to predict more potential palmitoylation sites and increases research productivity in palmitoylation sites discovery. The corresponding software can be freely downloaded from http://www.aporc.org/doc/wiki/CKSAAP-Palm.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1741-0134
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
707-12
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Prediction of palmitoylation sites using the composition of k-spaced amino acid pairs.
pubmed:affiliation
College of Science, China Agricultural University, Beijing 100083, People's Republic of China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't