Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information
โ Scribed by Gianluca Pollastri; Alberto JM Martin; Catherine Mooney; Alessandro Vullo
- Book ID
- 115000798
- Publisher
- BioMed Central
- Year
- 2007
- Tongue
- English
- Weight
- 349 KB
- Volume
- 8
- Category
- Article
- ISSN
- 1471-2105
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## Abstract Protein structural class prediction solely from protein sequences is a challenging problem in bioinformatics. Numerous efficient methods have been proposed for protein structural class prediction, but challenges remain. Using novel combined sequence information coupled with predicted se
A primary and a secondary neural network are applied to secondary structure and structural class prediction for a database of 681 non-homologous protein chains. A new method of decoding the outputs of the secondary structure prediction network is used to produce an estimate of the probability of fin