Prediction of protein structure class by coupling improved genetic algorithm and support vector machine
β Scribed by Z.-C. Li; X.-B. Zhou; Y.-R. Lin; X.-Y. Zou
- Publisher
- Springer
- Year
- 2008
- Tongue
- English
- Weight
- 291 KB
- Volume
- 35
- Category
- Article
- ISSN
- 0939-4451
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The support vector machines (SVMs) method was introduced for predicting the structural class of protein domains. The results obtained through the self-consistency test, jack-knife test, and independent dataset test have indicated that the current method and the elegant component-coupled algorithm de
## Abstract The prediction of secondary structure is a fundamental and important component in the analytical study of protein structure and functions. How to improve the predictive accuracy of protein structural classification by effectively incorporating the sequenceβorder effects is an important