Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulations

被引：0

作者：

Gabriel Ferreira, Pedro ^{[1
]}

Silva, Candida G. ^{[2
,3
]}

Azevedo, Paulo J. ^{[4
]}

Brito, Rui M. M. ^{[2
,3
]}

机构：

[1] Ctr Genom Regulat, Genome Bioinformat Lab, Barcelona, Spain

[2] Univ Coimbra, Dept Chem, Fac Sci, Coimbra, Portugal

[3] Univ Coimbra, Ctr Neurosci, Cell Biol, Coimbra, Portugal

[4] Univ Minho, Dept Informat, CCTC, Braga, Portugal

来源：

COMPUTATIONAL INTELLIGENCE METHODS FOR BIOINFORMATICS AND BIOSTATISTICS | 2009年 / 5488卷

关键词：

D O I：

暂无

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Molecular dynamics simulations is a. valuable tool to study protein unfolding in silico. Analyzing the relative spatial position of the residues during the simulation may indicate which residues are essential in determining the protein structure. We present a method, inspired by a popular data mining technique called Frequent Itemset Mining, that clusters sets of amino acid residues with a synchronized trajectory during the unfolding process. The proposed approach has several advantages over traditional hierarchical clustering.

引用

页码：156 / +

页数：2

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