应用图论分析与最优化理论来数据挖掘大规模水牛普里昂蛋白结构数据

doi:10.15960/j.cnki.issn.1007-6093.2017.02.009

Operations Research Transactions

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

ZHANG Jiapu^1,2,* CHATTERJEE Subhojyoti² WANG Feng²

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:2017-04-13 Online:2017-06-15 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)

Abstract

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

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, doi: 10.15960/j.cnki.issn.1007-6093.2017.02.009.

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

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