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Construction of Protein Phosphorylation Network Based on Boolean Network Methods Using Proteomics Data

  • Han Yu
  • Yaou Zhao
  • Shiyuan Han
  • Yuehui ChenEmail author
  • Wenxing HeEmail author
  • Likai Dong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9771)

Abstract

Post-translational Modification (PTM) of Proteins is a key biological process in the regulation of protein function. This paper discusses the problem of construction of PTM network based on the reverse engineering principles, which is constructed by using PBIL and TDE algorithms. Experiments which are based on two well-known pathways by the time series data of protein phosphorylation data show that the new method can be successfully validated and further reveal the regulation of protein phosphorylation.

Keywords

PTM Computational intelligence Phosphorylation network PBIL TDE 

Notes

Acknowledgement

This research was partially supported by Program for Scientific research innovation team in Colleges and universities of Shandong Province 2012–2015, the Key Project of Natural Science Foundation of Shandong Province (ZR2011FZ001), the Natural Science Foundation of Shandong Province (ZR2011FL022, ZR2013FL002), the Youth Science and Technology Star Program of Jinan City (201406003), the Shandong Provincial Key Laboratory of Network Based Intelligent Computing and Shandong Provincial Natural Science Foundation, China, under Grant ZR2015JL025. This work was also supported by the National Natural Science Foundation of China (Grant No. 61302128) and Shandong Distinguished Middle-Aged and Young Scientist Encourage and Reward Foundation Grant BS2014DX015. Research Fund for the Doctoral Program of University of Jinan (No. XBS1604). The scientific research foundation of University of Jinan (XKY1410, XKY1411). Authors would like to thank Huixiang Xu of School of Information Science and Engineering, University of Jinan. Thanks the anonymous referees for the technical suggestions and remarks which helped to improve the contents and the quality of presentation.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Information Science and EngineeringUniversity of JinanJinanChina
  2. 2.Shandong Provincial Key Laboratory of Network Based Intelligent ComputingJinanChina
  3. 3.School of Biological Science and TechnologyUniversity of JinanJinanChina

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