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Prediction of protein structure classes with pseudo amino acid composition and fuzzy support vector machine network.
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ding, Yongsheng Zhang, Tong-Liang Chou, Kuo-Chen |
| Copyright Year | 2007 |
| Abstract | It is a critical challenge to develop automated methods for fast and accurately determining the structures of proteins because of the increasingly widening gap between the number of sequence-known proteins and that of structure-known proteins in the post-genomic age. The knowledge of protein structural class can provide useful information towards the determination of protein structure. Thus, it is highly desirable to develop computational methods for identifying the structural classes of newly found proteins based on their primary sequence. In this study, according to the concept of Chou's pseudo amino acid composition (PseAA), eight PseAA vectors are used to represent protein samples. Each of the PseAA vectors is a 40-D (dimensional) vector, which is constructed by the conventional amino acid composition (AA) and a series of sequence-order correlation factors as original introduced by Chou. The difference among the eight PseAA representations is that different physicochemical properties are used to incorporate the sequence-order effects for the protein samples. Based on such a framework, a dual-layer fuzzy support vector machine (FSVM) network is proposed to predict protein structural classes. In the first layer of the FSVM network, eight FSVM classifiers trained by different PseAA vectors are established. The 2nd layer FSVM classifier is applied to reclassify the outputs of the first layer. The results thus obtained are quite promising, indicating that the new method may become a useful tool for predicting not only the structural classification of proteins but also their other attributes. |
| Starting Page | 391 |
| Ending Page | 401 |
| Page Count | 11 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.researchgate.net/profile/Tongliang_Zhang/publication/5866468_Prediction_of_protein_structure_classes_with_pseudo_amino_acid_composition_and_fuzzy_support_vector_machine_network/links/0f47b739b7d6d2d3502e4e39.pdf |
| PubMed reference number | 17979824v1 |
| Volume Number | 14 |
| Issue Number | 8 |
| Journal | Protein and peptide letters |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Amino Acid Metabolism, Inborn Errors Amino Acids Class Dual Protein Structure Protein, Organized by Structure Pseudo brand of pseudoephedrine Support Vector Machine Thioctic Acid |
| Content Type | Text |
| Resource Type | Article |
