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Using Grey Model GM(2,1) and Pseudo Amino Acid Composition to Predict Protein Subcellular Location

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2 Author(s)
Wei-Zhong Lin ; Sch. of Inf. Eng., Jing-De-Zhen Ceramic Inst., Jingdezhen ; Xuan Xiao

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.

Published in:

2008 2nd International Conference on Bioinformatics and Biomedical Engineering

Date of Conference:

16-18 May 2008