Szczegóły publikacji

Opis bibliograficzny

Hybrid biclustering algorithms for data mining / Patryk ORZECHOWSKI, Krzysztof BORYCZKO // W: Applications of evolutionary computation : 19th European Conference, EvoApplications 2016 : Porto, Portugal, March 30–April 1, 2016 : proceedings, Pt. 1 / eds. Giovanni Squillero, Paolo Burelli. — Switzerland : Springer International Publishing, 2016. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 9597). — ISBN: 978-3-319-31203-3; e-ISBN: 978-3-319-31204-0. — S. 156–168. — Bibliogr. s. 166–168, Abstr. — Publikacja dostępna online od: 2016-03-15


Autorzy (2)


Słowa kluczowe

gene expression datamicroarray analysisbiclustering techniquesdata mining

Dane bibliometryczne

ID BaDAP104196
Data dodania do BaDAP2017-02-22
DOI10.1007/978-3-319-31204-0_11
Rok publikacji2016
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
Konferencja19th European Conference on Applications of Evolutionary Computation
Czasopisma/serieLecture Notes in Computer Science, Theoretical Computer Science and General Issues

Abstract

Hybrid methods are a branch of biclustering algorithms that emerge from combining selected aspects of pre-existing approaches. The syncretic nature of their construction enriches the existing methods providing them with new properties. In this paper the concept of hybrid biclustering algorithms is explained. A representative hybrid biclustering algorithm, inspired by neural networks and associative artificial intelligence, is introduced and the results of its application to microarray data are presented. Finally, the scope and application potential for hybrid biclustering algorithms is discussed.

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