Identifying the Subfamilies of Voltage-Gated Potassium Channels Using Feature Selection Technique
| Autor: | En-Ze Deng, Wei-Wei Chen, Weixin Liu, Hao Lin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Support Vector Machine
Channel (digital image) voltage-gated potassium channel subfamily optimized tripeptide composition support vector machine feature selection Feature selection Overfitting Biology Bioinformatics Catalysis Article lcsh:Chemistry Inorganic Chemistry User-Computer Interface Dimension (vector space) Jackknife test Physical and Theoretical Chemistry Databases Protein lcsh:QH301-705.5 Molecular Biology Spectroscopy Internet business.industry Organic Chemistry Computational Biology Pattern recognition General Medicine Computer Science Applications Support vector machine lcsh:Biology (General) lcsh:QD1-999 Potassium Channels Voltage-Gated Benchmark (computing) Artificial intelligence business Oligopeptides Algorithms |
| Zdroj: | International Journal of Molecular Sciences International Journal of Molecular Sciences; Volume 15; Issue 7; Pages: 12940-12951 International Journal of Molecular Sciences, Vol 15, Iss 7, Pp 12940-12951 (2014) |
| ISSN: | 1422-0067 |
| Popis: | Voltage-gated K+ channel (VKC) plays important roles in biology procession, especially in nervous system. Different subfamilies of VKCs have different biological functions. Thus, knowing VKCs’ subfamilies has become a meaningful job because it can guide the direction for the disease diagnosis and drug design. However, the traditional wet-experimental methods were costly and time-consuming. It is highly desirable to develop an effective and powerful computational tool for identifying different subfamilies of VKCs. In this study, a predictor, called iVKC-OTC, has been developed by incorporating the optimized tripeptide composition (OTC) generated by feature selection technique into the general form of pseudo-amino acid composition to identify six subfamilies of VKCs. One of the remarkable advantages of introducing the optimized tripeptide composition is being able to avoid the notorious dimension disaster or over fitting problems in statistical predictions. It was observed on a benchmark dataset, by using a jackknife test, that the overall accuracy achieved by iVKC-OTC reaches to 96.77% in identifying the six subfamilies of VKCs, indicating that the new predictor is promising or at least may become a complementary tool to the existing methods in this area. It has not escaped our notice that the optimized tripeptide composition can also be used to investigate other protein classification problems. |
| Databáze: | OpenAIRE |
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