Chemical Data Analysis in the Large: The Challenge of the Automation Age
May 22nd - 26th , 2000, Bozen, Italy
The scientific program lists all speakers and lecture topics.
The challenge of managing and effectively utilising the massive amounts of diverse data that are now becoming available from large chemical databases, from the results of increased automation in drug research, and from the genomics revolution, are facing industry and universities alike. From well-ordered databases to large, sparse, and messy datasets, from molecular modelling to the in-silico modelling of biological systems, new techniques and methods are being developed to meet the evolving needs of the chemical sciences. New methods in areas such as knowledge discovery and data mining, exploratory data analysis, machine learning, simulation and prediction, and data visualisation are already providing useful tools that are impacting chemical research, but much remains to be done before these methodologies realise their full potential.
This workshop provided a forum for experts in a range of fields to bring details their work, and of others to the attention of an invited audience of leading members of the computer-aided molecular design and chemoinformatics community, so as to enable the invitees to identify new methods and technologies that might be applicable to information handling in chemistry and related sciences.
Scientific Committee: Gerald Maggiora (Pharmacia and Upjohn, USA), Peter Willett (University of Sheffield, UK) and Martin Hicks (Beilstein-Institut, Germany)
