Abstract
The article describes two new clustering algorithms for DNA nucleotide sequences, summarizes the results of experimental analysis of performance of these algorithms for an ITS-sequence data set, and compares the results with known biologically significant clusters of this data set. It is shown that both algorithms are efficient and can be used in practice.
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References
Baldi, P., Brunak, S.: Bioinformatics: The Machine Learning Approach. MIT Press, Cambridge (2001)
Durbin, R., Eddy, S.R., Krogh, A., Mitchison, G.: Biological Sequence Analysis. Cambridge University Press, Cambridge (1999)
Gedeon, T.D., Fung, L.C.C. (eds.): AI 2003. LNCS (LNAI), vol. 2903. Springer, Heidelberg (2003)
Gusfield, D.: Algorithms on Strings, Trees, and Sequences. Computer Science and Computational Biology. Cambridge University Press, Cambridge (1997)
Jones, N.C., Pevzner, P.A.: An Introduction to Bioinformatics Algorithms. MIT Press, Cambridge (2004), http://www.bioalgorithms.info/
Kang, B.H.: Pacific Knowledge Acquisition Workshop. In: Part of the 8th Pacific Rim Internat. Conf. on Artificial Intelligence, Auckland, New Zealand (2004)
Kang, B.H., Kelarev, A.V., Sale, A.H.J., Williams, R.N.: A model for classifying DNA code embracing neural networks and FSA. In: Pacific Knowledge Acquisition Workshop, PKAW 2006, Guilin, China, August 7-8, pp. 201–212 (2006)
Kelarev, A.V.: Ring Constructions and Applications. World Scientific, River Edge (2002)
Kang, B.H., Kelarev, A.V., Sale, A.H.J., Williams, R.N.: Labeled directed graphs and FSA as classifiers of strings. In: 17th Australasian Workshop on Combinatorial Algorithms, AWOCA 2006, pp. 93–109 (2006)
Li, J., Yang, Q., Tan, A.-H. (eds.): BioDM 2006. LNCS (LNBI), vol. 3916. Springer, Heidelberg (2006)
Mount, D.: Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory (2001), http://www.bioinformaticsonline.org/
Steane, D.A., Nicolle, D., Mckinnon, G.E., Vaillancourt, R.E., Potts, B.M.: High-level relationships among the eucalypts are resolved by ITS-sequence data. Australian Systematic Botany 15, 49–62 (2002)
Webb, G.I., Yu, X. (eds.): AI 2004. LNCS (LNAI), vol. 3339. Springer, Heidelberg (2004)
WEKA, Waikato Environment for Knowledge Analysis (viewed 20.06.2006), http://www.cs.waikato.ac.nz/ml/weka
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Elsevier/Morgan Kaufman, Amsterdam (2005)
Yang, J.Y., Ersoy, O.K.: Combined supervised and unsupervised learning in genomic data mining, School of Electrical and Computer Engineering, Purdue University (2003)
Zhang, C., Guesgen, H.W., Yeap, W.-K. (eds.): PRICAI 2004. LNCS (LNAI), vol. 3157. Springer, Heidelberg (2004)
Zhang, S., Jarvis, R.A. (eds.): AI 2005. LNCS (LNAI), vol. 3809. Springer, Heidelberg (2005)
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Kelarev, A., Kang, B., Steane, D. (2006). Clustering Algorithms for ITS Sequence Data with Alignment Metrics. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_116
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DOI: https://doi.org/10.1007/11941439_116
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49787-5
Online ISBN: 978-3-540-49788-2
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