Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulations

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Ferreira, PG (Author) Other; Silva, CG (Author) Other; Azevedo, PJ (Author) Other; Brito, RMM (Author) Other

Conference proceedings International

Title: COMPUTATIONAL INTELLIGENCE METHODS FOR BIOINFORMATICS AND BIOSTATISTICS

Pages: 156-+

5th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2008

Vietri sul Mare, 3 October 2008 through 4 October 2008

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 3 Citations

Scientific classification

CORDIS: Technological sciences > Engineering > Computer engineering ; Technological sciences > Technology > Knowledge technology

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering ; Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-007-R2H

DOI: 10.1007/978-3-642-02504-4_14

Abstract (EN): 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. © 2009 Springer Berlin Heidelberg.

Language: English

Type (Professor's evaluation): Scientific