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Transmembrane helix prediction using amino acid property features and latent semantic analysis
BACKGROUND: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of free parameters in their models which are tuned to fit the little data available for training. Further, they are often res...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2008
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2259405/ https://www.ncbi.nlm.nih.gov/pubmed/18315857 http://dx.doi.org/10.1186/1471-2105-9-S1-S4 |