Summary
The invention of the so-called DNA sequencing more than 20 years ago has by now created an exponentially exploding flood of sequence data. For a computer scientist, such data consists of strings of symbols in an alphabet of size four. Being discrete by nature, the analysis and handling of sequence data is an exceptionally attractive and — noting its role in the heart of life — challenging application domain for combinatorial algorithmics. Hence it does not come as a surprise that computational molecular biology and bioinformatics are currently very active interdiciplinary research areas [5,10].
A work supported by the Academy of Finland.
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References
A. Alizadeh et al., Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature 403 (3 February 2000) 503–511.
S. Altschul, W. Gish, W. Miller, E. W. Myers & D. Lipman, A basic local aligment search tool, J. Mol. Biol 215 (1990) 403–410.
E. Anson & G. Myers, Algorithms for whole genome shotgun sequencing, RE-COMB99, ACM Press (1999) 1–9.
J. L. DeRisi, V. R. Iyer & P. O. Brown, Exploring the metabolic and genetic control of gene expression on a genomic scale, Science 278 (1997) 680–686.
D. Gusfield, Algorithms on Strings, Trees, and Sequences-Computer Science and Computational Biology, Cambridge University Press 1997.
H. Peltola, H. Söderlund, J. Tarhio & E. Ukkonen, Algorithms for some string matching problems arising in molecular genetics, Proc. 9th IFIP World Computer Congress, Elsevier (1983) 59–64.
R. Staden, Automation of the computer handling of gel reading data produced by the shotgun method of DNA sequencing, Nucleic Acids Research 10 (1982), 4731–4751.
J. Vilo, A. Brazma, I. Jonassen, A. Robinson & E. Ukkonen, Mining for putative regulatory elements in the yeast genome using gene expression data, Proc. Eighth Int. Conference on Intelligent Systems for Molecular Biology ISMB 2000, in press, AAAI Press (2000).
M. S. Waterman, Introduction to Computational Biology: Maps, Sequences, Genomes, Chapman and Hall 1995.
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Ukkonen, E. (2000). Toward Complete Genome Data Mining in Computational Biology. In: Algorithm Theory - SWAT 2000. SWAT 2000. Lecture Notes in Computer Science, vol 1851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44985-X_3
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DOI: https://doi.org/10.1007/3-540-44985-X_3
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