A new approach to the prediction of transmembrane structures

• 来源期刊: 科学通报（英文版）
• 年，卷（期）: 2008,（7）
• 页码范围: 1011-1014
• 页数: 4页
• 语种: 英文
• DOI: 10.1007/s11434-008-0055-5

摘要

About 20%-30% of genome products have been predicted as membrane proteins, which have sig-nificant biological functions. The prediction of the amount and position for the transmembrane protein helical segments (TMHs) is the hot spot in bioinformatics. In this paper, a new approach, maximum spectrum of continuous wavelet transform (MSCWT), is proposed to predict TMHs. The predictions for eight SARS-CoV membrane proteins indicate that MSCWT has the same capacity with software TMpred. Moreover, the test on a dataset of 131 structure-known proteins with 548 TMHs shows that the predic-tion accuracy of MSCWT for TMHs is 91.6% and that for membrane protein is 89.3%.