Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction

Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction (1996)

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by Ashwin Srinivasan Muggleton , Ashwin Srinivasan , S. H. Muggleton , M. J. E. Sternberg , R. D. King

Venue:	Artificial Intelligence
Citations:	141 - 29 self

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Datum	Value	Source
TITLE	Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction	user correction - Legacy Corrections
AUTHOR NAME	Ashwin Srinivasan Muggleton	user correction - Legacy Corrections
AUTHOR NAME	Ashwin Srinivasan	user correction - Legacy Corrections
AUTHOR AFFIL	Oxford University Computing Laboratory	user correction - Legacy Corrections
AUTHOR ADDR	Wolfson Building, Parks Road, Oxford	user correction - Legacy Corrections
AUTHOR NAME	S. H. Muggleton	user correction - Legacy Corrections
AUTHOR AFFIL	Oxford University Computing Laboratory	user correction - Legacy Corrections
AUTHOR ADDR	Wolfson Building, Parks Road, Oxford	user correction - Legacy Corrections
AUTHOR NAME	M. J. E. Sternberg	user correction - Legacy Corrections
AUTHOR AFFIL	Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, Lincoln's Inn	user correction - Legacy Corrections
AUTHOR ADDR	Fields, London.	user correction - Legacy Corrections
AUTHOR NAME	R. D. King	user correction - Legacy Corrections
AUTHOR AFFIL	Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, Lincoln's Inn	user correction - Legacy Corrections
AUTHOR ADDR	Fields, London.	user correction - Legacy Corrections
ABSTRACT	A classic problem from chemistry is used to test a conjecture that in domains for which data are most naturally represented by graphs, theories constructed with Inductive Logic Programming (ILP) will significantly outperform those using simpler feature-based methods. One area that has long been associated with graph-based or structural representation and reasoning is organic chemistry. In this field, we consider the problem of predicting the mutagenic activity of small molecules: a property that is related to carcinogenicity, and an important consideration in developing less hazardous drugs. By providing an ILP system with progressively more structural information concerning the molecules, we compare the predictive power of the logical theories constructed against benchmarks set by regression, neural, and tree-based methods. 1 Introduction Constructing theories to explain observations occupies much of the creative hours of scientists and engineers. Programs from the field of Inductiv...	user correction - Legacy Corrections
YEAR	1996	INFERENCE
VENUE	Artificial Intelligence	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	277--299	INFERENCE
VOLUME	85	INFERENCE
CITATIONS	21 found	ParsCit 1.0