DocumentCode :
1654210
Title :
Using Grey Model GM(2,1) and Pseudo Amino Acid Composition to Predict Protein Subcellular Location
Author :
Lin, Wei-Zhong ; Xiao, Xuan
Author_Institution :
Sch. of Inf. Eng., Jing-De-Zhen Ceramic Inst., Jingdezhen
fYear :
2008
Firstpage :
718
Lastpage :
721
Abstract :
Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. Based on the concept of pseudo amino acid composition, a novel representation of protein sequence, grey pseudo amino acid (grey-PseAA) was introduced. The advantage by incorporating the grey-PseAA into the pseudo amino acid composition is that it can catch the essence of the overall sequence pattern of a protein and hence more effectively reflect its sequence-order effects. It was demonstrated thru the jackknife cross validation test and independent dataset test that the overall success rates by the new approach were significantly improved. It is anticipated that the concept of grey-PseAA composition can be also used to predict many other protein attributes, such as membrane protein type, enzyme functional class, GPCR type, protease type, among many others.
Keywords :
cellular biophysics; genetics; molecular biophysics; proteins; GPCR type; enzyme functional class; gene product functional annotation; gene product representation; grey model GM(2,1); grey pseudoamino acid; grey-PseAA; independent dataset test; jackknife cross validation test; membrane protein type; protease type; protein sequence pattern; protein subcellular location prediction; pseudoamino acid composition; sequence order effects; subcellular protein localization; Amino acids; Biochemistry; Biomembranes; Ceramics; Electron microscopy; Prediction algorithms; Predictive models; Protein engineering; Protein sequence; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
Type :
conf
DOI :
10.1109/ICBBE.2008.175
Filename :
4535055
Link To Document :
بازگشت