Linked Life Data

16140260

Source:http://linkedlifedata.com/resource/pubmed/id/16140260

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2005-9-23
pubmed:abstractText
Cell membranes are vitally important to living cells. Although the infrastructure of biological membrane is provided by the lipid bilayer, membrane proteins perform most of the specific functions. Knowledge of membrane protein types often provides crucial hints toward determining the function of an uncharacterized membrane protein. With the avalanche of new protein sequences generated in the post-genomic era, it is highly demanded to develop a high throughput tool in identifying the type of newly found membrane proteins according to their primary sequences, so as to timely annotate them for reference usage in both basic research and drug discovery. To realize this, the key is to establish a powerful identifier that can catch their characteristic sequence patterns for different membrane protein types. However, it is not easy because they are buried in a pile of long and complicated sequences. In this paper, based on the concept of the pseudo-amino acid composition [K.C. Chou, PROTEINS: Struct., Funct., Genet. 43 (2001) 246-255], the low-frequency Fourier spectrum analysis is introduced. The merits by doing so are that the sequence pattern information can be more effectively incorporated into a set of discrete components, and that all the existing prediction algorithms can be straightforwardly used on such a formulation for protein samples. High success rates were observed by the re-substitution test, jackknife test, and independent dataset test, indicating that the low-frequency Fourier spectrum approach may become a very useful tool for membrane protein type prediction. The novel approach also holds a high potential for predicting many other attributes of proteins.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0006-291X
pubmed:author
pubmed:issnType
Print
pubmed:day
28
pubmed:volume
336
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
737-9
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Low-frequency Fourier spectrum for predicting membrane protein types.
pubmed:affiliation
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, China.
pubmed:publicationType
Journal Article, Evaluation Studies