Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Applying the Subdue Substructure Discovery System to the Chemical Toxicity Domain
Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Ilp: a short look back and a longer look forward
The Journal of Machine Learning Research
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
LogCHEM: Interactive Discriminative Mining of Chemical Structure
BIBM '08 Proceedings of the 2008 IEEE International Conference on Bioinformatics and Biomedicine
Large-scale graph mining using backbone refinement classes
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
April: an inductive logic programming system
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
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Structural activity prediction is one of the most important tasks in chemoinformatics. The goal is to predict a property of interest given structural data on a set of small compounds or drugs. Ideally, systems that address this task should not just be accurate, but they should also be able to identify an interpretable discriminative structure which describes the most discriminant structural elements with respect to some target. The application of ILP in an interactive software for discriminative mining of chemical fragments is presented in this paper. In particular, it is described the coupling of an ILP system with a molecular visualisation software that allows a chemist to graphically control the search for interesting patterns in chemical fragments. Furthermore, we show how structural information, such as rings, functional groups such as carboxyls, amines, methyls, and esters, are integrated and exploited in the search.