Cross species analysis of microarray expression data | Zendy

Yong Lu | Zendy; Peter Huggins | Zendy; Ziv BarJoseph | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Cross species analysis of microarray expression data

Author(s) -

Yong Lu,

Peter Huggins,

Ziv BarJoseph

Publication year - 2009

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/btp247

Subject(s) - dna microarray , microarray analysis techniques , function (biology) , exponential growth , gene chip analysis , computational biology , expression (computer science) , computer science , data mining , sequence (biology) , microarray , biology , r package , contrast (vision) , gene , gene expression , genetics , artificial intelligence , mathematics , mathematical analysis , computational science , programming language

Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied.

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