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Understanding the limits of animal models as predictors of human biology: lessons learned from the sbv IMPROVER Species Translation Challenge (2015)
| Content Provider | CiteSeerX |
|---|---|
| Author | Rhrissorrakrai, Kahn Belcastro, Vincenzo Bilal, Erhan Norel, Raquel Poussin, Carine Mathis, Carole Dulize, Remi H. J. Ivanov, Nikolai V. Alexopoulos, Leonidas Rice, J. Jeremy Peitsch, Manuel C. Stolovitzky, Gustavo Meyer, Pablo Hoeng, Julia |
| Abstract | Motivation: Inferring how humans respond to external cues such as drugs, chemicals, viruses or hormones is an essential question in biomedicine. Very often, however, this question cannot be addressed because it is not possible to perform experiments in humans. A rea-sonable alternative consists of generating responses in animal models and ‘translating ’ those results to humans. The limitations of such translation, however, are far from clear, and systematic assessments of its actual potential are urgently needed. sbv IMPROVER (systems biology verification for Industrial Methodology for PROcess VErification in Research) was designed as a series of challenges to address translatability between humans and rodents. This collabora-tive crowd-sourcing initiative invited scientists from around the world to apply their own computational methodologies on a multilayer systems biology dataset composed of phosphoproteomics, transcrip- |
| File Format | |
| Journal | Bioinformatics |
| Language | English |
| Publisher Date | 2015-01-01 |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
