Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes
- 1 January 1997
- book chapter
- Published by Springer Nature
Abstract
No abstract availableKeywords
This publication has 13 references indexed in Scilit:
- Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.Proceedings of the National Academy of Sciences, 1996
- Polynomial learnability and Inductive Logic Programming: Methods and resultsNew Generation Computing, 1995
- Inverse entailment and progolNew Generation Computing, 1995
- The Use of the GRID Program in the 3-D QSAR Analysis of a Series of Calcium-Channel AgonistsJournal of Medicinal Chemistry, 1994
- Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase.Proceedings of the National Academy of Sciences, 1992
- Protein secondary structure prediction using logic-based machine learningProtein Engineering, Design and Selection, 1992
- Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitorsJournal of Medicinal Chemistry, 1991
- Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. Correlation with molecular orbital energies and hydrophobicityJournal of Medicinal Chemistry, 1991
- Comparison of the inhibition of Escherichia coli and Lactobacillus casei dihydrofolate reductase by 2,4-diamino-5-(substituted-benzyl)pyrimidines: quantitative structure-activity relationships, x-ray crystallography, and computer graphics in structure-activity analysisJournal of Medicinal Chemistry, 1982
- Correlation analysis of Baker's studies on enzyme inhibition. 1. Guanine deaminase, xanthine oxidase, dihydrofolate reductase, and complementJournal of Medicinal Chemistry, 1976