Data-mining protein structure by clustering, segmentation and evolutionary algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F09%3A00067124" target="_blank" >RIV/00216224:14330/09:00067124 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-01088-0_10" target="_blank" >http://dx.doi.org/10.1007/978-3-642-01088-0_10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-01088-0_10" target="_blank" >10.1007/978-3-642-01088-0_10</a>
Alternative languages
Result language
angličtina
Original language name
Data-mining protein structure by clustering, segmentation and evolutionary algorithms
Original language description
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 canbe combined to obtain a larger segment and therefore be able to infer higher level functions for a protein.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Data Mining: Theoretical Foundations and Applications
ISBN
9783642010873
ISSN
1860-949X
e-ISSN
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Number of pages
28
Pages from-to
221-248
Publisher name
Springer Verlag
Place of publication
Germany
Event location
Germany
Event date
Jan 1, 2009
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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