By Petra Perner
This e-book constitutes the refereed complaints of the sixth business convention on info Mining, ICDM 2006, held in Leipzig, Germany in July 2006. provides forty five conscientiously reviewed and revised complete papers prepared in topical sections on info mining in medication, net mining and logfile research, theoretical facets of information mining, facts mining in advertising, mining indications and photographs, and points of information mining, and purposes similar to intrusion detection, and extra.
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Additional resources for Advances in Data Mining: Applications in Medicine, Web Mining, Marketing, Image and Signal Mining: 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 2006, Proceedings
Searching for similarity among biological sequences is an important research area of bioinformatics because it can provide insight into the evolutionary and genetic relationships between species that open doors to new scientiﬁc discoveries such as drug design and treament. In this paper, we introduce a novel measure of similarity between two biological sequences without the need of alignment. The method is based on the concept of spectral distortion measures developed for signal processing. The proposed method was tested using a set of six DNA sequences taken from Escherichia coli K-12 and Shigella ﬂexneri, and one random sequence.
Sensitivity is expressed by the number of HSLIPAS related sequences found among the ﬁrst closest 20 library sequences; whereas selectivity is expressed in terms of the number of HSLIPAS-related sequences of which distances are closer to HSLIPAS than others and are not truncated by the ﬁrst HSLIPAS-unrelated sequence. Among several distance measures introduced by Wu et al. , they concluded that the standardized Euclidean distance under the Markov chain models of base composition was generally recommended, of which sensitivity and selectivity are 18 and 17 sequences respectively, of order one for base composition, and 18 and 16 sequences, respectively, of order two for base composition; when all the distances of nine diﬀerent word sizes were combined.
Bioinformatics 17 (2001) 1131–1142 7. : Feature selection for high-dimensional genomic microarray data. In: Proc. 18th International Conference on Machine Learning (2001) 601–608 8. : Relevance, redundancy and differential prioritization in feature selection for multiclass gene expression data. S. ): Proc. 6th International Symposium on Biological and Medical Data Analysis (ISBMDA-05) (2005) 367–378 9. : Large margin DAGs for multiclass classification. Advances in Neural Information Processing Systems 12 (2000) 547–553 10.
Advances in Data Mining: Applications in Medicine, Web Mining, Marketing, Image and Signal Mining: 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 2006, Proceedings by Petra Perner