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Verification of systems biology research in the age of collaborative competition

Nature Biotechnology 29, 811–815 (2011)
Meyer P, Alexopoulos LG, Bonk T, Califano A, Cho CR, de la Fuente A, de Graaf D, Hartemink AJ, Hoeng J, Ivanov NV, Koeppl H, Linding R, Marbach D, Norel R, Peitsch MC, Rice JJ, Royyuru A, Schacherer F, Sprengel J, Stolle K, Vitkup D, Stolovitzky G.

Improver NBT

Systems biology aims to provide a mechanistic understanding of biological systems from high-throughput data. Besides its intrinsic scientific value, this understanding will accelerate product design and development, facilitate health policy decisions and may reduce the need for long-term clinical trials. For this to happen, the knowledge generated by systems biology has to become sufficiently trustworthy for the empirical approach underlying long-term clinical trials to be supplanted by an approach in which mechanism and mechanistic understanding is a driver for decisions. This raises fundamental questions of how to evaluate the veracity of predictions from systems biology models and how to construct mechanistic models that best reflect biological phenomena—questions that are of interest to both academia and industry.

 

 

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