Protein is a fundamental material of life. There are many kinds of proteins in the body. If one of them malfunctions, it will cause physical problems. Therefore, many scientists try to analyze the functions of proteins. It is believed that the protein structure determines its function. The more similar the structures are, the more similar their functions are. Therefore, the prediction and
comparison of protein structures are important topics in
bioinformatics. Typically, distance RMSD (Root Mean Square
Deviation) is a method used by most scientists to measure the distance between two structures. In this thesis, we propose a new algorithm to compare two protein structures, which is based on the comparison of curves in the space. To test and verify our method, we randomly choose some families in the CATH database and try to identify them. Experimental results show that our method outperforms
RMSD. Furthermore, we also use the SVM (Support Vector Machine) tool to help us to obtain the better classification.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0827106-160923 |
| Date | 27 August 2006 |
| Creators | Lo, Yu-chieh |
| Contributors | Bang-ye Wu, Chung-lung Cho, Chia-ning Yang, Yow-ling Shiue, Chang-biau Yang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0827106-160923 |
| Rights | off_campus_withheld, Copyright information available at source archive |
Page generated in 0.0019 seconds