Lessons learned from the parallel universe of consumer electronics: Making Computer Aided Drug Design work on the platforms of the future
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Poster presented at the Gordon Research Conference: Computer Aided Drug Design 2015, describing a range of chemistry functionality that has been made to work on mobile apps. Each of these workflows involved removing a variety of barriers to adoption, both technical and sociological. The result is a strong platform for chemical informatics in drug discovery that has been tailored to the extremely high user experience required for the realm of consumer electronics. This is interesting not only for mobile apps, but also modern desktop or web applications, as customer expectations continue to rise to match those of other industries.