Data mining techniques to study the disulfide-bonding state in proteins: signal peptide is a strong descriptor
| Autor: | Colette Larré, Yves Popineau, Benjamin Bardiaux, Dominique Tessier |
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| Rok vydání: | 2004 |
| Předmět: |
Statistics and Probability
Signal peptide Information Storage and Retrieval Documentation Computational biology Protein Sorting Signals Biology Endoplasmic Reticulum Biochemistry Structure-Activity Relationship Sequence Analysis Protein Disulfide bonding Disulfides Association rule discovery Databases Protein Molecular Biology Natural Language Processing Binding Sites Disulfide bond Computer Science Applications Folding (chemistry) Computational Mathematics Computational Theory and Mathematics Database Management Systems State (computer science) Protein Binding Eucaryotic cell |
| Zdroj: | Bioinformatics. 20:2509-2512 |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/bth332 |
| Popis: | In the eucaryotic cell, the formation of disulfide bonds takes place in general inside the endoplasmic reticulum which provides a unique folding environment. The DisulfideDB database gathers information about this biological process with structural, evolutionary and neighborhood information on cysteines in proteins. Mining this information with an association rule discovery program permits to extract some strong rules for the prediction of the disulfide-bonding state of cysteines. Supplementary information: The web supplement to this paper, including the UML diagram of the database and some procedures used with the association rule discovery tool, may be found at http://www.nantes.inra.fr/centre/unites-recherche/urpvi/bioinformatique/publi.html. |
| Databáze: | OpenAIRE |
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