Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction | Zendy

Markus Hein | Zendy; Olivier Guipaud | Zendy; Fabien Milliat | Zendy; Valérie Buard | Zendy; Béatrice Micheau | Zendy; Georges Tarlet | Zendy; Marc Benderitter | Zendy; Farida Zehraoui | Zendy; Florence d’Alché–Buc | Zendy

Open Access

Detecting time periods of differential gene expression using Gaussian processes: an application to endothelial cells exposed to radiotherapy dose fraction

Author(s) -

Markus Hein,

Olivier Guipaud,

Fabien Milliat,

Valérie Buard,

Béatrice Micheau,

Georges Tarlet,

Marc Benderitter,

Farida Zehraoui,

Florence d’Alché–Buc

Publication year - 2014

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/btu699

Subject(s) - fraction (chemistry) , gaussian , gene expression , differential (mechanical device) , gene , radiation therapy , gaussian process , computational biology , computer science , expression (computer science) , biology , biological system , algorithm , mathematics , physics , genetics , chemistry , medicine , chromatography , programming language , thermodynamics , quantum mechanics

Identifying the set of genes differentially expressed along time is an important task in two-sample time course experiments. Furthermore, estimating at which time periods the differential expression is present can provide additional insight into temporal gene functions. The current differential detection methods are designed to detect difference along observation time intervals or on single measurement points, warranting dense measurements along time to characterize the full temporal differential expression patterns.

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