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Summary of Statistical Prediction of Posttranslational Modification Sites in Proteins
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.
Summary of Statistical Prediction of Posttranslational Modification Sites in Proteins
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.
Summary of Statistical Prediction of Posttranslational Modification Sites in Proteins
Wen, Li-Shu (Autor:in) / Yao, Cai-Lian (Autor:in)
01.12.2015
207400 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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