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Proceedings of the International Beilstein Workshop. Chemical Data Analysis in the Large: The Challenge of the Automation Age

Martin G. Hicks [Hrsg.]

ISBN 978-3-89722-938-9
132 Seiten, Erscheinungsjahr: 2002
Preis: 38.50 €
Managing and effectively utilizing large collections of highly diverse chemical data - especially when chemical structures are involved - is a major challenge for the chemical and pharmaceutical industries and universities, as well as for the producers of large publicly available databases. Automated techniques, such as, combinatorial chemistry coupled with high throughput screening result in the routine generation of enormous amounts of data. Methods of information handling such as knowledge discovery and data mining, machine learning, statistical analysis, and visualization, whose origins lie outside chemistry, are becoming more and more applicable in the area of chemical sciences. The aim of this workshop was to bring together experts from chemical and non-chemical fields to discuss new and better methods for handling and analysing large amounts of data of a chemical nature. Over three days a series of invited talks were heard, which covered the following areas:

1. Knowledge Discovery and Data Mining
2. Information Extraction and Text Mining
3. Data Compression and Clustering of Large Data Sets
4. Chemical Structure Representations
5. Structure Browsing and Similarity Indexes
6. Virtual Screening and Library Design
7. Property Prediction
8. Visualization of Data and Physicochemical Properties

The scientific program was compiled by Martin Hicks (Beilstein-Institut), Gerald Maggiora (Pharmacia) and Peter Willett (University of Sheffield).

Keywords:
  • Chemical Data Managing
  • Knowledge Discovery
  • Data Mining
  • Analysis of Chemical Data

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