Wednesday, November 11, 2015: 8:30 AM - 11:00 AM
255A (Salt Palace Convention Center)
Computational approaches to correlate, analyze, and understand large and complex data sets are playing increasingly important roles in the physical, chemical, and life sciences. This session solicits submissions pertaining to methodological advances and applications of data mining and machine learning methods, with particular emphasis on data-driven modeling and property prediction, statistical inference, big data, and informatics. Topics of interest include: algorithm development, inverse engineering, chemical property prediction, genomics/proteomics/metabolomics, (virtual) high-throughput screening, rational design, accelerated simulation, biomolecular folding, reaction networks, and quantum chemistry.
Computational Molecular Science and Engineering Forum
Andrew L. Ferguson Email: email@example.com
Johannes Hachmann Email: firstname.lastname@example.org
- indicates paper has an Extended Abstract file available on CD.
See more of this Group/Topical: Computational Molecular Science and Engineering Forum