Discover novel approaches to network and pathway analysis and make more informed drug discovery decisions.
Save time and resources compiling data and building algorithms for OMICs data analysis to allow your teams to more efficiently discover new drug targets, new indications for existing drugs, novel drug combinations, biomarkers and more.
Analyze complex datasets using algorithms developed by a team of experienced bioinformaticians with insights from industry leaders.
Unlock hidden insights in your OMICs data with access to exclusive algorithms built from leading research published in peer-reviewed literature, you can easily perform more efficient bioinformatics analyses to make better informed decisions around drug development.
Expand the knowledge and capabilities of your bioinformatics team and allow them to focus on more value-added work.
Advance your research with insights from industry experts with at least 15 years of experience in bioinformatics analysis and software development, as well as through collaboration with peers among the top 50 pharma companies.
algorithms developed thus far
June 25, 2019
The minor update of CBDD package (14.2.1) has been posted. It contains performance enhancements and bug fixes for several algorithms. See NEWS file in the package source for more details. The R package and documentation are available for download in the ‘Downloads’ section.
May 31, 2019
The 2nd and last part of CBDD phase 14 is completed! The R packages and documentation are available for download in the ‘Downloads’ section. Workshop slide deck, R examples and Webex recording have been posted to ‘Presentations’ section
May 14, 2019
The voting to determine scope of phases 15 and 16 (the rest of 2019) started today. The voting will be open until June 15th.