caa a22 4500 469053534 CHVBK 20180323132836.0 cr unu---uuuuu 170328e19920801xx s 000 0 eng 10.1007/BF00125944 doi (NATIONALLICENCE)springer-10.1007/BF00125944 Applications of rule-induction in the derivation of quantitative structure-activity relationships [Elektronische Daten] [Mohammed A-Razzak, Robert Glen] Summary: Recently, methods have been developed in the field of Artificial Intelligence (AI), specifically in the expert systems area using rule-induction, designed to extract rules from data. We have applied these methods to the analysis of molecular series with the objective of generating rules which are predictive and reliable. The input to rule-induction consists of a number of examples with known outcomes (a training set) and the output is a tree-structured series of rules. Unlike most other analysis methods, the results of the analysis are in the form of simple statements which can be easily interpreted. These are readily applied to new data giving both a classification and a probability of correctness. Rule-induction has been applied to in-house generated and published QSAR datasets and the methodology, application and results of these analyses are discussed. The results imply that in some cases it would be advantageous to use rule-induction as a complementary technique in addition to conventional statistical and pattern-recognition methods. Wellcome Foundation Ltd. and Infolink Decision Services Ltd, 1992 Artificial intelligence nationallicence CNS nationallicence Computational chemistry nationallicence GABA nationallicence Inotrope nationallicence Malaria nationallicence QSAR nationallicence Rule-induction nationallicence A-Razzak Mohammed Infolink Decision Services Ltd., 9-11 Grosvenor Gardens, SW1 W0BD, London, U.K. aut Glen Robert Wellcome Research Laboratories, Department of Physical Sciences, Langley Court, BR3 3BS, Beckenham, Kent, U.K. aut Journal of Computer-Aided Molecular Design Kluwer Academic Publishers 6/4(1992-08-01), 349-383 0920-654X 6:4<349 1992 6 10822 https://doi.org/10.1007/BF00125944 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00125944 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- A-Razzak Mohammed Infolink Decision Services Ltd., 9-11 Grosvenor Gardens, SW1 W0BD, London, U.K aut NATIONALLICENCE 700 1- Glen Robert Wellcome Research Laboratories, Department of Physical Sciences, Langley Court, BR3 3BS, Beckenham, Kent, U.K aut NATIONALLICENCE 773 0- Journal of Computer-Aided Molecular Design Kluwer Academic Publishers 6/4(1992-08-01), 349-383 0920-654X 6:4<349 1992 6 10822 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer