Accelerate your research with advanced analytics and actionable insights
The evolution of systems biology has allowed for easier integration of OMICs data, prior knowledge of networks and pathways, and tools for network analysis. However, many bioinformatics teams spend significant time and effort producing, collecting and analyzing OMICs data to create networks and pathways that support R&D decisions. The resulting analyses are only as accurate and useful as the analytical methods used to evaluate the OMICs data, so additional help is needed.
The Computational Biology Methods for Drug Discovery (CBDD) group brings together industry leaders and innovators to collaborate on the development and implementation of state-of-the-art approaches for network and pathway analyses. Established in 2015, CBDD has developed more than 50 exclusive algorithms for biological data analysis ̶ all with the goal of accelerating drug discovery. Ultimately, the collaboration and resulting algorithms free up internal resources, so your bioinformatics teams can spend less time developing algorithms and more time focusing on value-added work.
Collaborate with peers to develop and leverage industry leading analysis
Interested in learning how to become a member? Want to learn more about the algorithms and methodologies?