Data mining techniques to study the disulfide-bonding state in proteins: signal peptide is a strong descriptor | Zendy

Dominique Tessier | Zendy; Benjamin Bardiaux | Zendy; Colette Larré | Zendy; Yves Popineau | Zendy

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Data mining techniques to study the disulfide-bonding state in proteins: signal peptide is a strong descriptor

Author(s) -

Dominique Tessier,

Benjamin Bardiaux,

Colette Larré,

Yves Popineau

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bth332

Subject(s) - disulfide bond , signal (programming language) , state (computer science) , computer science , data mining , signal peptide , peptide , chemistry , computational biology , algorithm , biochemistry , peptide sequence , biology , programming language , gene

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.

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