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Operations Research Transactions >

2017 , Vol. 21 >Issue 2: 73 - 83

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2017.02.009

Using graph theory and optimization theory to do data mining the large scale buffalo prion protein structure database

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  • 1. Centre of Informatics and Applied Optimisation, The Federation University Australia,  Ballarat Vic3353, Australia; 2. Molecular Model Discovery Laboratory, Swinburne University of Technology, Melbourne Vic3122, Australia

Received date: 2017-04-13

  Online published: 2017-06-15

Supported by

This research was supported by a Melbourne Bioinformatics grant numbered FED0001 on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government (Australia)

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Abstract

 Graph theory and optimization theory are clearly very useful in the study of protein structures. Firstly, this paper is to research/review graph theory models in studies of protein structures. Secondly, we build a graph theory model to let the side-chain of a protein as a node, in the use of graph theory concepts such as clique, k-clique, community, hub, and cluster to build the edges. Thirdly, we solve the graph theory model built, using optimization theory/modern data mining algorithms/methods. Successful and fresh numerical results of data mining the large scale buffalo prion protein database will be illuminated.

Key words： graph theory; optimization theory; data mining; application to large scale databases

Cite this article

ZHANG Jiapu, CHATTERJEE Subhojyoti, WANG Feng .

Using graph theory and optimization theory to do data mining the large scale buffalo prion protein structure database
[J]. Operations Research Transactions, 2017 , 21(2) : 73 -83 . DOI: 10.15960/j.cnki.issn.1007-6093.2017.02.009

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