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A Wavelet Transform Based Protein Sequence Similarity Model |
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PP: 1103-1110 |
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Author(s) |
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Jie Su,
Junpeng Bao,
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Abstract |
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| Protein sequence analysis is an important tool for researchers to study on bio-informatics and molecular biology, such as
proteins structure and function prediction, phylogenetic classification and different conservation pattern recognition. It is a significant
open issue to quickly efficiently find the similar proteins from a large scale of protein repository. This paper proposes a new method
based on Discrete Wavelet Transform (DWT) to measure the similarity of protein sequences, i.e. the ACDWT model, as well as two
amino acid encoding methods (HPC and ADCC) according to hydropathy properties and dissociation constants respectively. The model
employs only the approximation coefficients of DWT so that the feature vector is short. That brings the proposed model a great running
time promotion. According to the phylogenic trees about nine ND5 proteins made from our model and others, the experimental results
show that our model is efficient and a little better than the others. |
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