Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1994-08

AUTHORS

Jonathan D. Hirst, Ross D. King, Michael J. E. Sternberg

ABSTRACT

One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR)--the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives--has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions. More... »

PAGES

421-432

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00125376

DOI

http://dx.doi.org/10.1007/bf00125376

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008401791

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/7815093


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