Árpád Figyelmesi (ChemAxon, Hungary)
During the recent years like other segments, cheminformatics also entered the field of big data. As we see quick transition from the traditional methods towards the direction of need for handling significantly large sets of data often in unstructured or semistructured forms. Words and phrases like, terabytes, scalability, NoSQL, cloud solutions are integrated in our everyday language. I would like to present a few case studies to highlight key features of this transition. Such as sowing techniques and technologies for handling different aspects of this new area.
2. Big data
Big data is a term for data sets that are so large or complex that traditional data
processing application software is inadequate to deal with them.
(Wikipedia)
Big data is high-volume, high-velocity and/or high-variety information assets that
demand cost-effective, innovative forms of information processing that enable
enhanced insight, decision making, and process automation.
(Gartner – IT Glossary)
14. Chemical white-space analysis
• Find potential drug analogs/novel ring systems
• From synthetically feasible virtual chemical space
• As close as possible to known drugs
• As far as possible from patented compounds
15. Case study
• Filter drugs from ChEMBL
• Search analogs in GDB-13
• Analyze overlap with
SureChEMBL
https://www.chemaxon.com/app/uploads/2017/03
/mfss-study-poster-23-1-imre-gabor-1.pdf
20. Extreme fast search engines
• Search time is not a question anymore
• Hits as you draw
• Real-time clustering for search suggestions and
drill down
New ways of interactions fundamentally change
the chemical patent search
21. Beyond the search
• Real-time analysis of extreme large
compound libraries
• Proactive exploration of synthetically
feasible and patentable chemical space