Extensive complementarity between gene function prediction methods | Zendy

Vedrana Vidulin | Zendy; Tomislav Šmuc | Zendy; Fran Supek | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Extensive complementarity between gene function prediction methods

Author(s) -

Vedrana Vidulin,

Tomislav Šmuc,

Fran Supek

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/btw532

Subject(s) - genome , computational biology , gene prediction , gene , function (biology) , annotation , gene ontology , complementarity (molecular biology) , biology , benchmark (surveying) , gene annotation , computer science , ranking (information retrieval) , data mining , genetics , machine learning , gene expression , geodesy , geography

The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions.

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