Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms | Zendy

Gaëlle Lelandais | Zendy; Pierre Vincens | Zendy; Anne Badel-Chag | Zendy; Stéphane Vialette | Zendy; Claude Jacq | Zendy; S. Hazout | Zendy

Open Access

Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms

Author(s) -

Gaëlle Lelandais,

Pierre Vincens,

Anne Badel-Chag,

Stéphane Vialette,

Claude Jacq,

S. Hazout

Publication year - 2006

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/btl087

Subject(s) - gene , expression (computer science) , organism , computational biology , genome , space (punctuation) , source code , biology , exploit , code (set theory) , gene expression , model organism , computer science , theoretical computer science , genetics , set (abstract data type) , computer security , programming language , operating system

Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons.

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