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运筹学学报 >

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

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

运筹学

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

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  • 1. 澳大利亚联邦大学信息与应用最优化研究中心, 巴拉瑞特 Vic3353, 澳大利亚; 2.  澳大利亚斯文本科技大学分子模型开发实验室, 墨尔本 Vic3122, 澳大利亚

收稿日期: 2017-04-13

  网络出版日期: 2017-06-15

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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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  • 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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摘要

图论、最优化理论显然在蛋白质结构的研究中大有用场. 首先, 调查/回顾了研究蛋白质结构的所有图论模型. 其后, 建立了一个图论模型: 让蛋白质的侧链来作为图的顶点, 应用图论的诸如团、 $k$-团、 社群、 枢纽、聚类等概念来建立图的边. 然后, 应用数学最优化的现代摩登数据挖掘算法/方法来分析水牛普里昂蛋白结构的大数据. 成功与令人耳目一新的数值结果将展示给朋友们.

关键词： 图论; 最优化理论; 数据挖掘; 应用于大数据

本文引用格式

张家普, CHATTERJEE Subhojyoti, 王凤 . 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[J]. 运筹学学报, 2017 , 21(2) : 73 -83 . DOI: 10.15960/j.cnki.issn.1007-6093.2017.02.009

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

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