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Pattern mining and visualization for molecular dynamics simulation
- Date Issued:
- 2014
- Summary:
- Molecular dynamics is a computer simulation technique for expressing the ultimate details of individual particle motions and can be used in many fields, such as chemical physics, materials science, and the modeling of biomolecules. In this thesis, we study visualization and pattern mining in molecular dynamics simulation. The molecular data set has a large number of atoms in each frame and range of frames. The features of the data set include atom ID; frame number; position in x, y, and z plane; charge; and mass. The three main challenges of this thesis are to display a larger number of atoms and range of frames, to visualize this large data set in 3-dimension, and to cluster the abnormally shifting atoms that move with the same pace and direction in different frames. Focusing on these three challenges, there are three contributions of this thesis. First, we design an abnormal pattern mining and visualization framework for molecular dynamics simulation. The proposed framework can visualize the clusters of abnormal shifting atom groups in a three-dimensional space, and show their temporal relationships. Second, we propose a pattern mining method to detect abnormal atom groups which share similar movement and have large variance compared to the majority atoms. We propose a general molecular dynamics simulation tool, which can visualize a large number of atoms, including their movement and temporal relationships, to help domain experts study molecular dynamics simulation results. The main functions for this visualization and pattern mining tool include atom number, cluster visualization, search across different frames, multiple frame range search, frame range switch, and line demonstration for atom motions in different frames. Therefore, this visualization and pattern mining tool can be used in the field of chemical physics, materials science, and the modeling of biomolecules for the molecular dynamic simulation outcomes.
Title: | Pattern mining and visualization for molecular dynamics simulation. |
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91 downloads |
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Name(s): |
Kong, Xue, author Zhu, Xingquan, Thesis advisor Florida Atlantic University, Degree grantor College of Computer Science and Engineering Department of Computer and Electrical Engineering and Computer Science |
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Type of Resource: | text | |
Genre: | Electronic Thesis Or Dissertation | |
Date Created: | 2014 | |
Date Issued: | 2014 | |
Publisher: | Florida Atlantic University | |
Place of Publication: | Boca Raton, Fla. | |
Physical Form: | application/pdf | |
Extent: | 88 p. | |
Language(s): | English | |
Summary: | Molecular dynamics is a computer simulation technique for expressing the ultimate details of individual particle motions and can be used in many fields, such as chemical physics, materials science, and the modeling of biomolecules. In this thesis, we study visualization and pattern mining in molecular dynamics simulation. The molecular data set has a large number of atoms in each frame and range of frames. The features of the data set include atom ID; frame number; position in x, y, and z plane; charge; and mass. The three main challenges of this thesis are to display a larger number of atoms and range of frames, to visualize this large data set in 3-dimension, and to cluster the abnormally shifting atoms that move with the same pace and direction in different frames. Focusing on these three challenges, there are three contributions of this thesis. First, we design an abnormal pattern mining and visualization framework for molecular dynamics simulation. The proposed framework can visualize the clusters of abnormal shifting atom groups in a three-dimensional space, and show their temporal relationships. Second, we propose a pattern mining method to detect abnormal atom groups which share similar movement and have large variance compared to the majority atoms. We propose a general molecular dynamics simulation tool, which can visualize a large number of atoms, including their movement and temporal relationships, to help domain experts study molecular dynamics simulation results. The main functions for this visualization and pattern mining tool include atom number, cluster visualization, search across different frames, multiple frame range search, frame range switch, and line demonstration for atom motions in different frames. Therefore, this visualization and pattern mining tool can be used in the field of chemical physics, materials science, and the modeling of biomolecules for the molecular dynamic simulation outcomes. | |
Identifier: | FA00004212 (IID) | |
Degree granted: | Thesis (M.S.)--Florida Atlantic University, 2014. | |
Collection: | FAU Electronic Theses and Dissertations Collection | |
Note(s): | Includes bibliography. | |
Subject(s): |
Data mining Information visualization Molecular dynamics -- Computer simulation Molecules -- Mathematical models Pattern perception |
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Held by: | Florida Atlantic University Libraries | |
Sublocation: | Digital Library | |
Links: | http://purl.flvc.org/fau/fd/FA00004212 | |
Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00004212 | |
Use and Reproduction: | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. | |
Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
Host Institution: | FAU | |
Is Part of Series: | Florida Atlantic University Digital Library Collections. |