NDLI: Predicting tyrosine phosphorylation from site-modification network

Content Provider	IEEE Xplore Digital Library
Author	Binghua Wang Minghui Wang Yujie Jiang Dongdong Sun Xiaoyi Xu
Copyright Year	2015
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China (Binghua Wang; Minghui Wang; Yujie Jiang; Dongdong Sun; Xiaoyi Xu)
Abstract	Phosphorylation plays a great role in regulating variety of cellular processes. Identification of the tyrosine phosphorylation is helpful for understanding the post-translational modifications regulation processes. Although a number of computational approaches have been developed, most of them only consider local sequence information, and currently few studies are concerned about the site with in situ PTM information, which refers to different types of PTMs occurring on the same modification site. In this study, we introduce a novel method (SMNBI) based on a site-modification network, which is constructed by integrating the site with in situ PTM information to predict tyrosine phosphorylation. In order to verify the effectiveness of our SMNBI method, we compare it with Protein-based collaborative filtering (ProteinCF). The results clearly show the superior performance of the SMNBI. Furthermore, to verify the importance of the site-modification network, we compare it with SVM and Bayesian decision theory based on local sequence information. These results demonstrate the site-modification network is useful for predicting tyrosine phosphorylation.
Starting Page	8569
Ending Page	8572
File Size	358441
Page Count	4
File Format	PDF
ISBN	9789881563897
ISSN	19341768
DOI	10.1109/ChiCC.2015.7260996
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Technical Committee on Control Theory, Chinese Association of Automation
Subject Keyword	Proteins Support vector machines site-modification network Peptides Decision theory Tyrosine phosphorylation Crosstalk local sequence information Bayes methods Resource management
Content Type	Text
Resource Type	Article

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