KNOWLEDGE DISCOVERY IN MOLECULAR DATABASES

Authors
CONKLIN D FORTIER S GLASGOW J
Citation
D. Conklin et al., KNOWLEDGE DISCOVERY IN MOLECULAR DATABASES, IEEE transactions on knowledge and data engineering, 5(6), 1993, pp. 985-987
Citations number
16
Categorie Soggetti
Information Science & Library Science","Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence
Journal title
IEEE transactions on knowledge and data engineering → ACNP
ISSN journal
10414347
Volume
5
Issue
6
Year of publication
1993
Pages
985 - 987
Database
ISI
SICI code
1041-4347(1993)5:6<985:KDIMD>2.0.ZU;2-X
Abstract
This paper describes an approach to knowledge discovery in complex mol ecular databases. The machine learning paradigm used is structured con cept formation, in which objects described in terms of components and their interrelationships are clustered and organized in a knowledge ba se. Symbolic images are used to represent classes of structured object s. A discovered molecular knowledge base is successfully used in the i nterpretation of a high resolution electron density map.