Abstract
A knowledge discovery approach from chemical information with focusing on negative information in positive data is described. Reported experimental chemical reactions are classified into some reaction groups according to similarities in physicochemical features with a self-organizing mapping (SOM) method. In one of the reaction groups, functional groups of reactants are divided into two categories according to the experimental results whether they reacted or not. The classes of the functional groups are used for derivation of knowledge on chemical reactivity and condition intensity. The approach is demonstrated with a model dataset.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Funatsu, K., Sasaki, S.: Computer-Assisted Synthesis Design and Reaction Prediction System AIPHOS. Tetrahedron Comput. Method 1, 27 (1988)
Gasteiger, J., Ihlenfeldt, W.D.: A collection of computer methods for synthesis design and reaction prediction. Recl. Trav. Chim. Pays-Bas. 111, 270 (1992)
Röse, P., Gasteiger, J.: Automated derivation of reaction rules for the EROS 6.0 system for reaction prediction. Anal. Chim. Acta. 235, 163 (1990)
Satoh, H., Funatsu, K.: SOPHIA, a Knowledge Base-Guided Reaction Prediction System - Utilizing of a Knowledge Base Derived from a Reaction Database. J. Chem. Inf. Comput. Sci. 35, 34 (1995)
Satoh, H., Funatsu, K.: Further Development of a Reaction Generator in the SOPHIA System for Organic Reaction Prediction. Knowledge-Guided Addition of Suitable Atoms and/or Atomic Groups to Product Skeleton. J. Chem. Inf. Comput. Sci. 36, 173 (1996)
Chen, L., Gasteiger, J.: Organic Reactions Classified by Neural Networks: Michael Additions, Friedel-Crafts Alkylations by Alkenes, and Related Reactions. Angew. Chem. 108, 844 (1996); Angew. Chem. Int. Ed. Engl. 35, 763 (1996)
Satoh, H., Sacher, O., Nakata, T., Chen, L., Gasteiger, J., Funatsu, K.: Classification of Organic Reactions: Similarity of Reactions Based on Changes in the Electronic Features of Oxygen Atoms at the Reaction Sites. J. Chem. Inf. Comput. Sci. 38, 210 (1998)
Satoh, H., Itono, S., Funatsu, K., Takano, K., Nakata, T.: A Novel Method for Characterization of Three-dimensional Reaction Fields Based on Electrostatic and Steric Interactions toward the Goal of Quantitative Analysis and Understandingg of Organic Reactions. J. Chem. Inf. Comput. Sci. 39, 671 (1999)
Satoh, H., Funatsu, K., Takano, K., Nakata, T.: Classification and Prediction of Reagents’ Roles by FRAU System with Self-organizing Neural Network Model. Bull. Chem. Soc. Jpn. 73, 1955 (2000)
Satoh, H., Koshino, H., Funatsu, K., Nakata, T.: Novel Canonical Coding Method for Representation of Three-dimensional Structures. J. Chem. Inf. Comput. Sci. 40, 622 (2000)
Satoh, H., Koshino, H., Funatsu, K., Nakata, T.: Representation of Configurations by CAST Coding Method. J. Chem. Inf. Comput. Sci. 41, 1106 (2001)
Satoh, H., Koshino, H., Nakata, T.: Extended CAST Coding Method for Exact Search of Stereochemical Structures. J. Comput. Aided. Chem. 3, 48 (2002)
Distributed Chemical Graphics, Inc.
Kohonen, T.: Self-organized Formation of Topologically Correct Feature Maps. Biol. Cybern. 43, 59 (1982)
Laboratory of Prof. Kimito Funatsu in Toyohashi University of Technology
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Satoh, H., Nakata, T. (2003). Knowledge Discovery on Chemical Reactivity from Experimental Reaction Information. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_48
Download citation
DOI: https://doi.org/10.1007/978-3-540-39644-4_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20293-6
Online ISBN: 978-3-540-39644-4
eBook Packages: Springer Book Archive