کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
505117 | 864474 | 2013 | 5 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: In silico identification of Gram-negative bacterial secreted proteins from primary sequence In silico identification of Gram-negative bacterial secreted proteins from primary sequence](/preview/png/505117.png)
In this study, we focus on different types of Gram-negative bacterial secreted proteins, and try to analyze the relationships and differences among them. Through an extensive literature search, 1612 secreted proteins have been collected as a standard data set from three data sources, including Swiss-Prot, TrEMBL and RefSeq. To explore the relationships among different types of secreted proteins, we model this data set as a sequence similarity network. Finally, a multi-classifier named SecretP is proposed to distinguish different types of secreted proteins, and yields a high total sensitivity of 90.12% for the test set. When performed on another public independent dataset for further evaluation, a promising prediction result is obtained. Predictions can be implemented freely online at http://cic.scu.edu.cn/bioinformatics/secretPv2_1/index.htm.
Journal: Computers in Biology and Medicine - Volume 43, Issue 9, 1 September 2013, Pages 1177–1181