THIS IS THE HOMEPAGE!
sbv IMPROVER at a Glance
sbv IMPROVER stands for Systems Biology Verification combined with Industrial Methodology for Process Verification in Research. This approach aims to provide a measure of quality control of industrial research and development by verifying the methods used. The sbv IMPROVER project is a collaborative effort led and funded by PMI Research and Development. For more information please see Nature Biotechnology (2011) or Bioinformatics (2012).
It is different from other scientific crowdsourcing approaches as it focuses on the verification of processes in an industrial context, and not just on basic questions regarding science. The sbv IMPROVER approach allows an organization to benchmark its methods and industrial processes.
Today the scope of sbv IMPROVER is the verification of methods and concepts in systems biology research. However, the scope of the project could be extended to the verification of research processes in other industries such as pharmaceuticals, biotechnology, nutrition and environmental safety, to name a few.
Approach to Challenge Design
Why you should be Part of sbv IMPROVER
- Take the opportunity to compete for research grants
- Receive an independent assessment of your methods
- Gain access to high quality data
- Enhance your visibility and gain recognition from an international team of eminent scientists
- Publish: the results of the challenge and the identity of the best performing entrants will be submitted to a high impact peer reviewed journal
- Present your results at the sbv IMPROVER Symposium: the best performing entrants will be invited to present their approach at an international symposium
sbv IMPROVER. Verified by you.
The Network Verification Challenge presents an opportunity to redefine COPD to the benefit of real-world clinical practice. The models being produced have the potential to complement clinical experience with a robust, molecular-level understanding of COPD, which ultimately can translate to improved disease diagnosis and patient management.
[..] the project addresses both the technical and biological challenges inherent in making predictions between species.