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Toward Genomic Hypothesis Creator: View Designer for Discovery

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Discovey Science (DS 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1532))

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Abstract

Software tools for genomic researches like homology search are very useful and have contributed on the progress of the genomic researches. However, these tools are not designed directly toward scientific discovery and more discovery-oriented software tools are strongly expected to assist scientific discovery in genomic researches. We have designed and developed a multistrategic and discovery-oriented system Genomic Hypothesis Creator by introducing two notions: view on data and view space on data. With these newly defined notions, we describe a View Designer, a component of Genomic Hypothesis Creator, which dynamically creates new views on data and searches a view space for more appropriate views. A good view obtained from Genomic Hypothesis Creator makes it possible for us to understand the data and eventually attain to the goal of discovery. Genomic Hypothesis Creator can be extended by adding user’s own views on data and hypothesis generators into the system with plug-in interfaces. Therefore it would be feasible to apply this system to other problems than genomic researches

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References

  1. Arikawa, S., Haraguchi, M., Inoue, H., Kawasaki, Y., Miyahara, T., Miyano, S., Oshima, K., Sakai, H., Shinohara, T., Shiraishi, S., Takeda, M., Takeya, S., Yamamoto, A., and Yuasa, H. The text database management system SIGMA: An improvement of the main engine. In Proc. Berliner Informatik-Tage (1989), pp. 72–81.

    Google Scholar 

  2. Arikawa, S., and Shinohara, T. A run-time efficient realization of Aho-Corasick pattern matching machines. New Generation Computing 2 (1984), 171–186.

    Article  Google Scholar 

  3. Bairoch, A. PROSITE: a dictionary of sites and patterns in proteins. Nucleic Acids Res. 19 (1991), 2241–2245.

    Google Scholar 

  4. Brazma, A., Vilo, J., Ukkonen, E., and Valtonen, K. Data mining for regulatory elements in yeast genome. In Proc. 5th Int. Conf. Intelligent Systems for Molecular Biology (ISMB-97) (1997), AAAI Press, pp. 65–74.

    Google Scholar 

  5. Bryant, R. Graph-based algorithms for Boolean function manipulation. IEEE Transactions on Computers 35 (1986), 677–691.

    Article  MATH  Google Scholar 

  6. Fayyad, U., Haussler, D., and Stolorz, P. Mining scientific data. Commun. ACM 39,11 (1996), 51–57.

    Article  Google Scholar 

  7. Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. The KDD process for extracting useful knowledge from volumes of data. Commun. ACM 39,11 (1996), 27–34.

    Article  Google Scholar 

  8. Fukuda, T., Morimoto, Y., Morishita, S., and Tokuyama, T. Interval finding and its application to data mining. In Proc. 7th International Symposium on Algorithms and Computation (ISAAC’ 96) (1996), Lecture Notes in Computer Science 1178, Springer-Verlag, pp. 55–64.

    Google Scholar 

  9. Kohavi, R., and eds., F. P. Machine Learning. Kluwer Academic Publishers, 1998.

    Google Scholar 

  10. Michalski, R. S., Bratko, I., and Kubat, M. Machine Learning and Data Mining: Methods and Applications. John Wiley & Sons, Ltd., 1998.

    Google Scholar 

  11. Michalski, R. S., and eds., J. W. Machine Learning. Kluwer Academic Publishers, 1997.

    Google Scholar 

  12. Michalski, R. S., Kerschberg, L., Kaufman, K., and Ribeiro, J. Mining for knowledge in databases: The INLEN architechure, initail implementation and first results. J. Intelligent Information System: Integrating AI and Database Technologies 1 (1992).

    Google Scholar 

  13. Quinlan, J.R. Induction of decision trees. Machine Learning 1 (1986), 81–106.

    Google Scholar 

  14. Shimozono, S., Shinohara, A., Shinohara, T., Miyano, S., Kuhara, S., and Arikawa, S. Knowledge acquisition from amino acid sequences by machine learning system BONSAI. Trans. Information Processing Society of Japan 35 (1994), 2009–2018.

    Google Scholar 

  15. Srinivasan, A., and King, R. D. Feature construction with inductive logic programming: a study of quantitative predictions of biological activity by structural attributes. In Proc. 6th International Workshop on Inductive Logic Programming (ILP-96) (1997), Springer-Verlag, pp. 89–104.

    Google Scholar 

  16. Wadman, M. Company aims to beat NIH human genome efforts. NATURE 393 (1998), 101.

    Article  Google Scholar 

  17. Wirth, R., Shearer, C., Grimmer, U., Reinartz, T., Schlosser, J., Breitner, C., Engels, R., and Lindner, G. Towards process-oriented tool support for knowledge discovery in databases. In Proc. First European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD’ 97) (1997), Springer-Verlag.

    Google Scholar 

  18. Wrobel, S., Wettschereck, D., Sommer, E., and Emde, W. Extensibility in data mining systems. In Proc. of the 2nd International Conference On Knowledge Discovery and Data Mining (KDD-96) (1996), pp. 214–219.

    Google Scholar 

  19. Xu, Y., Einstein, J. R., Mural, R. J., Shah, M., and Uberbacher, E. C. An improved system for exon recognition and gene modeling in human DNA sequences. In Proc. the Second Internatinal Conference on Intelligent Systems for Molecular Biology (1994), AAAI Press, pp. 376–383.

    Google Scholar 

  20. http://www.genome-www.stanford.edu/, ftp://ncbi.nlm.nih.gov/genbank/genomes/, http://www.genetics.wisc.edu/, http://www.mbl.edu/html/riley/monica.html, http://www.genome.ad.jp/.

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© 1998 Springer-Verlag Berlin Heidelberg

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Maruyama, O., Uchida, T., Shoudai, T., Miyano, S. (1998). Toward Genomic Hypothesis Creator: View Designer for Discovery. In: Arikawa, S., Motoda, H. (eds) Discovey Science. DS 1998. Lecture Notes in Computer Science(), vol 1532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49292-5_10

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  • DOI: https://doi.org/10.1007/3-540-49292-5_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65390-5

  • Online ISBN: 978-3-540-49292-4

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