Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets | Zendy

Sahand Hormoz | Zendy; Gyan Bhanot | Zendy; Michael Biehl | Zendy; Erhan Bilal | Zendy; Pablo Meyer | Zendy; Raquel Norel | Zendy; Kahn Rhrissorrakrai | Zendy; Adel Dayarian | Zendy

Open Access

Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets

Author(s) -

Sahand Hormoz,

Gyan Bhanot,

Michael Biehl,

Erhan Bilal,

Pablo Meyer,

Raquel Norel,

Kahn Rhrissorrakrai,

Adel Dayarian

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/btu569

Subject(s) - transcriptome , computational biology , biology , gene , gene expression , inference , drug development , set (abstract data type) , translation (biology) , computer science , systems biology , messenger rna , genetics , drug , artificial intelligence , pharmacology , programming language

Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development. However, in many cases, a naive 'extrapolation' between the two species has not succeeded. As a result, clinical trials of new drugs sometimes fail even after considerable success in the mouse or rat stage of development. In addition to in vitro studies, inter-species translation requires analytical tools that can predict the enriched gene sets in human cells under various stimuli from corresponding measurements in animals. Such tools can improve our understanding of the underlying biology and optimize the allocation of resources for drug development.

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