Cargando…
A stochastic context free grammar based framework for analysis of protein sequences
BACKGROUND: In the last decade, there have been many applications of formal language theory in bioinformatics such as RNA structure prediction and detection of patterns in DNA. However, in the field of proteomics, the size of the protein alphabet and the complexity of relationship between amino acid...
Autores principales: | Dyrka, Witold, Nebel, Jean-Christophe |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2765975/ https://www.ncbi.nlm.nih.gov/pubmed/19814800 http://dx.doi.org/10.1186/1471-2105-10-323 |
Ejemplares similares
-
Estimating probabilistic context-free grammars for proteins using contact map constraints
por: Dyrka, Witold, et al.
Publicado: (2019) -
Searching for universal model of amyloid signaling motifs using probabilistic context-free grammars
por: Dyrka, Witold, et al.
Publicado: (2021) -
Evolving stochastic context--free grammars for RNA secondary structure prediction
por: WJ Anderson, James, et al.
Publicado: (2012) -
Probabilistic grammatical model for helix‐helix contact site
classification
por: Dyrka, Witold, et al.
Publicado: (2013) -
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction
por: Dowell, Robin D, et al.
Publicado: (2004)