QUBIC: a bioconductor package for qualitative biclustering analysis of gene co-expression data | Zendy

Yu Zhang | Zendy; Juan Xie | Zendy; Jinyu Yang | Zendy; Anne Fennell | Zendy; Chi Zhang | Zendy; Qin Ma | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

QUBIC: a bioconductor package for qualitative biclustering analysis of gene co-expression data

Author(s) -

Yu Zhang,

Juan Xie,

Jinyu Yang,

Anne Fennell,

Chi Zhang,

Qin Ma

Publication year - 2016

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/btw635

Subject(s) - bioconductor , biclustering , r package , expression (computer science) , computer science , computational biology , gene expression , mega , data mining , gene , biology , cluster analysis , genetics , artificial intelligence , programming language , cure data clustering algorithm , correlation clustering , physics , astronomy

Biclustering is widely used to identify co-expressed genes under subsets of all the conditions in a large-scale transcriptomic dataset. The program, QUBIC, is recognized as one of the most efficient and effective biclustering methods for biological data interpretation. However, its availability is limited to a C implementation and to a low-throughput web interface.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research