Mining Inhibition Pathways for Protein Kinases on Skeletal Muscle

  • Qingfeng Chen
  • Baoshan Chen
  • Chengqi Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8335)

Abstract

The former two chapters propose approaches to discover positive regulation patterns of protein kinases in signal transduction. However, a deep study into the degree of activation and inhibition of catalytic and regulatory subunits of protein kinases, assists in understanding their profound effect on a cell. Especially, the inhibitors of kinase activity are a frequent cause of diseases, where kinases participate many aspects that control cell growth, movement and death. Thus, it is critical to discover the inhibition pathways for protein kinases. This chapter aims to investigate the potential inhibitive correlation between the subunit isoforms of AMP-activated protein kinase (AMPK), and the stimulus factors by using negative association rule mining and mutual information, respectively. The obtained rules not only prompt a comprehensive understanding of signalling pathways of protein kinase and indicate an attractive pharmacological target for disease treatment.

Keywords

Mutual Information Association Rule Minimum Support Frequent Itemsets Negative Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Qingfeng Chen
    • 1
    • 2
  • Baoshan Chen
    • 1
  • Chengqi Zhang
    • 2
  1. 1.School of Computer, Electronic and Information, State Key laboratory for Conservation and Utilization of Subtropical Agro-BioresourcesGuangxi UniversityNanningChina
  2. 2.Centre for Quantum Computation and Intelligent SystemsUniversity of Technology SydneyBroadwayAustralia

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