Data Mining in the Presence of Quantitatively and Qualitatively Diverse Information

IDM-0415190

Anne M. Denton <anne.denton@ndsu.edu>

North Dakota State University
Homepage: http://www.cs.ndsu.nodak.edu/~adenton/
Abstract

Project Pages

Graph-Relational Data Mining

Length-Dependent Sequence Clustering

Journal Publications

• Dietmar H. Dorr, Anne M. Denton, "Generalised Sequence Signatures through Symbolic Clustering," International Journal of Data Mining and Bioinformatics, (in press).
• Dietmar H. Dorr, Anne M. Denton, "Clustering Sequences by Overlap," International Journal of Data Mining and Bioinformatics, (in press).
• Anne M. Denton, Christopher A. Besemann and Dietmar H. Dorr, " Pattern-based Time-series Subsequence Clustering Using Radial Distribution Functions," Knowledge and Information Systems (KAIS) journal, (in press).
• C. Besemann, A. Denton, N. J. Carr and B. M Pruess, "BISON: bio-interface for the semi-global analysis of network patterns," Source Code for Biology and Medicine, 1:8, 2006.
• B. M. Prüβ, C.  Besemann, A. Denton, and Alan .J. Wolfe, "A complex transcription network controls the early stages of biofilm formation," J. Bacteriol. 188:3731-3739, 2006.
  

Conference and Workshop Publications

• Dietmar Dorr and Anne Denton, "A pattern mining approach toward discovering generalized sequence signatures," SIAM International Conference on Data Mining (SDM08), Atlanta, GA, April 24-26, 2008.
• Jianfei Wu and Anne Denton, " Mining Vector-Item Patterns for Annotating Protein Domains," Mining Multiple Information Sources Workshop in conjunction with the ACM KDD '07 Conference on Knowledge Discovery and Data Mining, San Jose, CA, Aug. 12, 2007, ISBN: 978-1-59593-840-4.
• Dietmar Dorr and Anne Denton, "Generalized Sequence Signatures through Symbolic Clustering," Workshop on Machine Learning in Biomedicine and Bioinformatics in conjunction with the Sixth International Conference on Machine Learning and Applications, Cincinnati, OH, Dec. 13-15, 2007.
• A. Denton and A. Kar, "Finding Differentially Expressed Genes Through Noise Elimination," Workshop on Data Mining for Biomedical Informatics in conj. with the Sixth SIAM Int'l Conference on Data Mining, Minneapolis, MN, April 28, 2007.
• C. Besemann and A. Denton, "Mining Edge-disjoint Patterns in Graph-relational Data," Workshop on Data Mining for Biomedical Informatics in conj. with the Sixth SIAM Int'l Conf. on Data Mining, Minneapolis, MN, April 28, 2007.
• A. Denton, "Kernel-density-based clustering of time series subsequences using a continuous random-walk noise model," In Proceedings The Fifth IEEE Int'l Conf' on Data Mining (ICDM'05), Houston, Texas, Nov. 27-30, pp 122-129, 2005.

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This material is based upon work supported by the National Science Foundation under Grant No. IDM-0415190.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.