Frequent Substructure-Based Approaches for Classifying Chemical Compounds
IEEE Transactions on Knowledge and Data Engineering
Optimization study with ligand-design interval rules
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Discovering frequent geometric subgraphs
Information Systems
A neuro-fuzzy approach to virtual screening in molecular bioinformatics
Fuzzy Sets and Systems
A compact representation of graph databases
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Generalization rules for binarized descriptors
ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
Supervised neuro-fuzzy clustering for life science applications
ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
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From the Publisher:Screening techniques are very common in biochemistry and biology to find out if new molecules are potential drugs. The huge amounts of new potential drugs are tested in most of the cases in a screening in view of only one special disease or one special function. There is not enough human power or financial resources to test these substances with common screening methods in order to know if they are active or helpful. Virtual screening can help industry to increase their efficiency drastically by estimating the activity of compounds no in an experiment, but with the computer.