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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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