This page describes mining for molecules. Since molecules may be represented by molecular graphs this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics. Typical approaches to calculate chemical similarities use chemical fingerprints, but this loses the underlying information about the molecule topology. Mining the molecular graphs directly avoids this problem. So does the inverse QSAR problem which is preferable for vectorial mappings. Coding(Moleculei,Moleculeji) Kernel methods Marginalized graph kernel Optimal assignment kernel Pharmacophore kernel C++ (and R) implementation combining the marginalized graph kernel between labeled graphs extensions of the marginalized kernel Tanimoto kernels graph kernels based on tree patterns kernels based on pharmacophores for 3D structure of molecules Maximum Common Graph methods MCS-HSCS (Highest Scoring Common Substructure (HSCS) ranking strategy for single MCS) Small Molecule Subgraph Detector (SMSD)- is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. This will help us to find similarity/distance between two molecules. MCS is also used for screening drug like compounds by hitting molecules, which share common subgraph (substructure). Coding(Moleculei) Molecular query methods Warmr AGM PolyFARM FSG MolFea MoFa/MoSS Gaston LAZAR ParMol (contains MoFa, FFSM, gSpan, and Gaston) optimized gSpan SMIREP DMax SAm/AIm/RHC AFGen gRed G-Hash Methods based on special architectures of neural networks BPZ ChemNet CCS MolNet Graph machines See also Molecular Query Language Chemical graph theory QSAR ADME partition coefficient References Further reading Schölkopf, B., K. Tsuda and J. P. Vert: Kernel Methods in Computational Biology, MIT Press, Cambridge, MA, 2004. R.O. Duda, P.E. Hart, D.G. Stork, Pattern Classification, John Wiley & Sons, 2001. Gusfield, D., Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Cambridge University Press, 1997. R. Todeschini, V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH, 2000. External links Small Molecule Subgraph Detector (SMSD) - is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. 5th International Workshop on Mining and Learning with Graphs, 2007 Overview for 2006 Molecule mining (basic chemical expert systems) ParMol and master thesis documentation - Java - Open source - Distributed mining - Benchmark algorithm library TU München - Kramer group Molecule mining (advanced chemical expert systems) DMax Chemistry Assistant - commercial software AFGen - Software for generating fragment-based descriptors Cheminformatics Computational