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@inproceedings{831677, author = {Lexa, Matej and Snášel, Václav and Zelinka, Ivan}, address = {Germany}, booktitle = {Data Mining: Theoretical Foundations and Applications}, doi = {http://dx.doi.org/10.1007/978-3-642-01088-0_10}, keywords = {data mining; bioinformatics; protein structure; biological sequence analysis; segmentation}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Germany}, isbn = {978-3-642-01087-3}, pages = {221-248}, publisher = {Springer Verlag}, title = {Data-mining protein structure by clustering, segmentation and evolutionary algorithms}, url = {http://dx.doi.org/10.1007/978-3-642-01088-0_10}, year = {2009} }
TY - JOUR ID - 831677 AU - Lexa, Matej - Snášel, Václav - Zelinka, Ivan PY - 2009 TI - Data-mining protein structure by clustering, segmentation and evolutionary algorithms PB - Springer Verlag CY - Germany SN - 9783642010873 KW - data mining KW - bioinformatics KW - protein structure KW - biological sequence analysis KW - segmentation UR - http://dx.doi.org/10.1007/978-3-642-01088-0_10 N2 - After a brief introduction to Bioinformatics, the authors discuss how Evolutionary Algorithms can be used to solve problems from Bioinformatics. Later, the authors describe how clustering techniques can group protein fragments and how short fragments can be combined to obtain a larger segment and therefore be able to infer higher level functions for a protein. ER -
LEXA, Matej, Václav SNÁŠEL and Ivan ZELINKA. Data-mining protein structure by clustering, segmentation and evolutionary algorithms. In \textit{Data Mining: Theoretical Foundations and Applications}. Germany: Springer Verlag, 2009, p.~221-248. ISBN~978-3-642-01087-3. Available from: https://dx.doi.org/10.1007/978-3-642-01088-0\_{}10.
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