Application of canonical correlation analysis for identifying viral integration preferences | Zendy

Ergün Gümüş | Zendy; Olcay Kurşun | Zendy; Ahmet Sertbaş | Zendy; Duran Üstek | Zendy

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Application of canonical correlation analysis for identifying viral integration preferences

Author(s) -

Ergün Gümüş,

Olcay Kurşun,

Ahmet Sertbaş,

Duran Üstek

Publication year - 2012

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/bts027

Subject(s) - canonical correlation , canonical analysis , correlation , computer science , computational biology , econometrics , artificial intelligence , mathematics , machine learning , biology , geometry

Gene therapy aims at using viral vectors for attaching helpful genetic code to target genes. Therefore, it is of great importance to develop methods that can discover significant patterns around viral integration sites. Canonical correlation analysis is an unsupervised statistical tool that is used to describe the relations between two related views of the same semantic object, which fits well for identifying such salient patterns.

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