Genomic data integration using guided clustering | Zendy

Matthias Maneck | Zendy; Alexandra Schrader | Zendy; Dieter Kube | Zendy; Rainer Spang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Genomic data integration using guided clustering

Author(s) -

Matthias Maneck,

Alexandra Schrader,

Dieter Kube,

Rainer Spang

Publication year - 2011

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/btr363

Subject(s) - cluster analysis , computer science , data mining , data integration , software , computational biology , consensus clustering , bioinformatics , cure data clustering algorithm , biology , correlation clustering , artificial intelligence , programming language

In biomedical research transcriptomic, proteomic or metabolomic profiles of patient samples are often combined with genomic profiles from experiments in cell lines or animal models. Integrating experimental data with patient data is still a challenging task due to the lack of tailored statistical tools.

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