Abstract
The meta-analysis of the challenging data set on the mutagenicity of nitroaromatic compounds has been performed. There are two ways of structure coding: standard topological indexes or so-called fingerprint descriptors. In our previous work, a unique structure coding by fingerprint descriptors was used for the discovery of mutagenes with GUHA+/- software system. GUHA can process nominal variables, which are transformed to binary strings in the course of computation. Any structure coding can then be used for GUHA. The data encoded by topological indexes were processed by GUHA+/- software system as well. The hypotheses on the reasons for mutagenicity of nitroaromatic compounds were generated by GUHA+/- for Windows. Processing of data encoded by topological indexes was rather demanding because of the large number of structure descriptors. Meta-analysis by combining fingerprint descriptors for a posteriori structure templates resulting from previous analyses and more flexible topological indexes seems to be more appropriate.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Todorowski, L., Dzeroski, S.: Experiments in Meta-level Learning with ILP, In: J.M. Zytkow, J. Rauch (Eds): Proceedings of The Third European Conference on Principles of Data Mining and Knowledge Discovery, PKDD’99, Prague 1999 (Prague School of Economics), Lecture Notes in Computer Science, LNCS 1704, Springer Verlag Berlin, Heidelberg, New York, Tokyo 1999
Debnath, A.K., Lopez de Compadre, R.L., Debnath, G., Schusterman, A.J., Hansch, C.: Structure Activity Relationship of Mutagenic Aromatic and Heteroaromatic Nitro Compounds. Correlation with molecular orbital energies and hydrophobicity, Journal of Medicinal Chemistry, 34(2) (1991) 786
Muggleton, S., Srinivasan, A., King, R.D., Sternberg, M.J.E.: Biochemical Knowledge Discovery Using Inductive Logic Programming In: Motoda, H., Arikawa, S.,: (Eds.): Proceedings of The First International Conference on Discovery Science, Lecture Notes in Computer Science, LNCS 1532, pp. 291–302, Springer Verlag Berlin, Heidelberg, New York, Tokyo (1998)
Inokuchi, A. et al.: Applying Algebraic Mining Method of Graph Substructures to Mutagenesis Data Analysis, In. Suzuki E. (Ed): International Workshop of KDD Challenge on Real-world Data, 4th. Pacific Asia Conference on Knowledge Discovery and Data Mining, Kyoto, 2000
Inokuchi, A. Washio, T., Motoda, H.: An Apriori Algorithm for Mining Frequent Substructures form Graph Data, In Zighed, D.A., Komorowski, J., Zytkow, J. (Eds) Proceedings of The Fourth European Conference on Principles of Data Mining and Knowledge Discovery, PKDD 2000, Lyon, Lecture Notes in Computer Science, LNCS 1910, Springer Verlag Berlin, Heidelberg, New York, Tokyo 2000
Okada, T.: SAR Discovery on the Mutagenicity of Aromatic Nitro Compound Studied by the Cascade Model, In. Suzuki E. (Ed): International Workshop of KDD Challenge on Real-world Data, 4th. Pacific Asia Conference on Knowledge Discovery and Data Mining, Kyoto, 2000
Matsuda, T., Horiuchi, T., Motoda, H., Washio, T.: Graph-Based Induction for General Graph Structure Data and Its Application to Chemical Compound Data. In: Arikawa, S., Morishita, S., (Eds. Proceedings of the Third International Conference on Discovery Science, Kyoto 2000, LNCS 1967 Springer Verlag Berlin, Heidelberg, Tokyo.
Chytil, M., Hajek, P., Havel, I.: The GUHA method of automated hypotheses generation, Computing, 293–308, 1966
Smyth, P., Goodman, R. M.: An Information Theoretic Approach to Rule Induction From Databases. IEEE Transactions on Knowledge and Data Engineering 4(4)(1992) 301.
Balaban, A.I., Chiriac, A., Motoc I., Simon, Z.: Steric Fit in Quantitative-Structure Activity Relationships, Springer Verlag, Berlin 1980
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zak, P., Spacil, P., Halova, J. (2001). Meta-analysis of Mutagenes Discovery. In: Jantke, K.P., Shinohara, A. (eds) Discovery Science. DS 2001. Lecture Notes in Computer Science(), vol 2226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45650-3_46
Download citation
DOI: https://doi.org/10.1007/3-540-45650-3_46
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42956-2
Online ISBN: 978-3-540-45650-6
eBook Packages: Springer Book Archive