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Predicting Protein Subcellular Location Based on Principal Component Analysis

Author: ShiDuo
Tutor: GuHong
School: Dalian University of Technology
Course: Detection technology and automation devices
Keywords: Bioinformatics Protein subcellular Pseudo- amino acid composition of the model Principal Component Analysis Serial correlation factor
CLC: Q51
Type: Master's thesis
Year: 2010
Downloads: 104
Quote: 1
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Abstract


In recent years, with the completion of the drawing of the human genome , human genomic era into the post-genomic era . The massive surge in the Protein Data gradually become the hallmarks of the era , bioinformatics study found that the function and structure of proteins and subcellular location can play a different role in protein transport to a different location , in the need for a post-genomic era subcellular positioning to efficiently analyze the function of the protein . Protein characteristic information by the method of establishment of biological model to extract the key to become a research , wherein the amino acid model to its simplicity has been widely used, but this model ignores the sequence , i.e. between amino acids in the sequence order effect , Kuo -Chen Chou pseudo- amino acid composition of the model is a good solution to this problem . However , when the application of pseudo - amino acid composition model , it is difficult to obtain the optimal sequence associated factor , resulting in the selection process is time-consuming . Principal component analysis method , in this paper, to ensure that the model contains as many serial correlation factor information at the same time , on the basis of the feature space of the original protein extract key main characteristics . The test results show that the principal component analysis method can effectively improve the prediction performance , to some extent, to resolve the problem to select the sequence effect factor .

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CLC: > Biological Sciences > Biochemistry > Protein
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