DocumentCode
3732156
Title
Summary of Statistical Prediction of Posttranslational Modification Sites in Proteins
Author
Li-Shu Wen;Cai-Lian Yao
Author_Institution
Sch. of Sci., Shenyang Aerosp. Univ., Shenyang, China
fYear
2015
Firstpage
805
Lastpage
808
Abstract
Most proteins perform their functions after post-translational modifications (PTMs). Post-translational modifications play crucial roles in various cell functions and biological process. Computational identification of PTMs is an important way in contrast to experimental approach with its convenience. This review gave the process for prediction of Post-translational modification sites including benchmark dataset, feature construction, algorithm, evaluation measurement, and online web-server. Feature construction which reflects intrinsic correlation with proteins was emphasized mainly. Seven feature construction methods containing physiochemical properties and sequence information have been illustrated principally. Last nitro tyrosine was an application to design a site-specific predictor. The procedure was clearly described.
Keywords
"Proteins","Peptides","Amino acids","Support vector machines","Yttrium","Benchmark testing","Machine learning algorithms"
Publisher
ieee
Conference_Titel
Intelligent Transportation, Big Data and Smart City (ICITBS), 2015 International Conference on
Type
conf
DOI
10.1109/ICITBS.2015.203
Filename
7384149
Link To Document