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Biochem Biophys Res Commun. 2007 Jun 22;358(1):136-9. Epub 2007 Apr 23.

Predicting the protein SUMO modification sites based on Properties Sequential Forward Selection (PSFS).

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Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, China.


Protein SUMO modification is an important post-translational modification and the optimization of prediction methods remains a challenge. Here, by using Support Vector Machines algorithm (SVM), a novel computational method was developed for SUMO modification site prediction based on Sequential Forward Selection (SFS) of hundreds of amino acid properties, which are collected by Amino Acid Index database ( Our method also compares with the 0/1 system, in which the 20 amino acids are represented by 20-dimensional vectors (A = 00000000000000000001, C = 00000000000000000010 and so on). The overall accuracy of leave-one-out cross-validation for our method reaches 89.18%, which is higher than 0/1 system. It indicated that the SUMO modification prediction process is highly related to the amino acid property and this approach here provide a helpful tool for further investigation of the SUMO modification and identification of sumoylation sites in proteins. The software is available at

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