If you use the LabelHash web server or the LabelHash command line version, we kindly ask that you acknowledge us. You can use the first reference below. This paper describes the web server and tools. The second reference describes the LabelHash algorithm in detail. The third reference describes a computational pipeline called FASST-MESH for detecting subtle patterns of structural variation within a class of related proteins. The paper is not about LabelHash per se, but uses it as a low-level routine. The last two references describe some preliminary results on the LabelHash algorithm; the first two references supersede them.
- M. Moll, D. H. Bryant, and L. E. Kavraki. The LabelHash Server and Tools for Substructure-Based Functional Annotation, Bioinformatics, 2011. DOI: 10.1093/bioinformatics/btr343.
- M. Moll, D. H. Bryant, and L.E. Kavraki. The LabelHash Algorithm for Substructure Matching, BMC Bioinformatics, 11(555), 2010. DOI: 10.1186/1471-2105-11-555.
- D.H. Bryant, M. Moll, B. Y. Chen, V.Y. Fofanov, and L.E. Kavraki, Analysis of Substructural Variation in Families of Enzymatic Proteins with Applications to Protein Function Prediction, BMC Bioinformatics, 11(242), May 2010. DOI: 10.1186/1471-2105-11-242.
- M. Moll and L.E. Kavraki. Matching of Structural Motifs Using Hashing on Residue Labels and Geometric Filtering for Protein Function Prediction. The Seventh Annual International Conference on Computational Systems Bioinformatics (CSB2008), pp. 157-168, Stanford, CA, 2008.
- M. Moll and L.E. Kavraki. LabelHash: A Flexible and Extensible Method for Matching Structural Motifs. Automated Function Prediction meeting, Toronto, Canada, 2008. [abstract] [poster]
If you have any questions about LabelHash, please contact Mark Moll by email at “mmoll” AT cs.rice.edu or send email to the LabelHash mailing list at email@example.com.