Mining protein function from text using term-based support vector machines
β Scribed by Simon B Rice; Goran Nenadic; Benjamin J Stapley
- Book ID
- 115000139
- Publisher
- BioMed Central
- Year
- 2005
- Tongue
- English
- Weight
- 290 KB
- Volume
- 6
- Category
- Article
- ISSN
- 1471-2105
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Computational methods can be used to predict the effects of single amino acid substitutions (single-point mutations). In contrast to previous methods that need many protein sequence and structural features, we applied support vector machines (SVMs) to predict protein function changes associated with
## 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