Name
Abstract | ||
|---|---|---|
Protein structure comparison is an important tool to explore and understand the different aspects of protein 3D structures. In this paper, a novel representation of protein structure (complete information set of Cα–Cα distances, CISD) is formulated at first. Then an FDOD score scheme is developed to measure the similarity between two representations. Numerical experiments of the new method are conducted in four different protein datasets and clustering analyses are given to verify the effectiveness of this new similarity measure. Furthermore, preliminary results of detecting homologous protein pairs of an existing non-redundant subset of CATH v2.5.1 based on the new similarity are given as a pilot study. All the results show that this new approach to measure the similarities between protein structures is simple to implement, computationally efficient and fast. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11750321_49 | TAMC |
Keywords | Field | DocType |
different aspect,information discrepancy,protein structure comparison,protein pair,new similarity,cath v2,protein structure,new similarity measure,new method,new approach,different protein datasets | Information structure,Discrete mathematics,Similitude,Pattern recognition,Similarity measure,Computer science,Protein superfamily,Artificial intelligence,Root-mean-square deviation,Cluster analysis,Complete information,Protein structure | Conference |
Volume | ISSN | ISBN |
3959 | 0302-9743 | 3-540-34021-1 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zikai Wu | 1 | 31 | 3.40 |
| Yong Wang | 2 | 575 | 46.58 |
| En-Min Feng | 3 | 8 | 1.87 |
| Jin-Cheng Zhao | 4 | 0 | 0.34 |