PUEPro: A Computational Pipeline for Prediction of Urine Excretory Proteins
Authors: 
Yan Wang, Wei Du, Yanchun Liang, Xin Chen, Chi Zhang, Wei Pang, Ying XuAuthors Info & Claims
Yan Wang, Wei Du, Yanchun Liang, Xin Chen, Chi Zhang, Wei Pang, Ying XuAuthors Info & ClaimsPages 714 - 725
Abstract
A computational pipeline is developed to accurately predict urine excretory proteins and the possible origins of the proteins. The novel contributions of this study include: (i) a new method for predicting if a cellular protein is urine excretory based on unique features of proteins known to be urine excretory; and (ii) a novel method for identifying urinary proteins originating from the urinary system. By integrating these tools, our computational pipeline is capable of predicting the origin of a detected urinary protein, hence offering a novel tool for predicting potential biomarkers of a specific disease, which may have some of their proteins urine excreted. One application is presented for this prediction pipeline to demonstrate the effectiveness of its prediction. The pipeline and supplementary materials can be accessed at the following URL: http://csbl.bmb.uga.edu/PUEPro/.
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Information & Contributors
Information
Published In
Dec 2016
830 pages
ISBN:978-3-319-49585-9
DOI:10.1007/978-3-319-49586-6
- Editors:
- Jinyan Li,
- Xue Li,
- Shuliang Wang,
- Jianxin Li,
- Quan Z. Sheng
© Springer International Publishing AG 2016.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 12 December 2016
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