Use of keyword hierarchies to interpret gene expression patterns | Zendy

Daniel R. Masys | Zendy; John Welsh | Zendy; J. Lynn Fink | Zendy; Michael Gribskov | Zendy; Igor Klacansky | Zendy; Jacques Corbeil | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Use of keyword hierarchies to interpret gene expression patterns

Author(s) -

Daniel R. Masys,

John Welsh,

J. Lynn Fink,

Michael Gribskov,

Igor Klacansky,

Jacques Corbeil

Publication year - 2001

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/17.4.319

Subject(s) - cluster analysis , information retrieval , variety (cybernetics) , computer science , interpretation (philosophy) , hierarchical clustering , search engine indexing , expression (computer science) , subject (documents) , similarity (geometry) , computational biology , data science , data mining , artificial intelligence , biology , library science , image (mathematics) , programming language

High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results.

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