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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F09%3A03151583%21RIV09-AV0-21230___
rdf:type
n16:Vysledek skos:Concept
dcterms:description
This chapter points out the role of genomic background knowledge in gene expression data mining. The authors demonstrate its application in several tasks such as relational descriptive analysis, constraint-based knowledge discovery, feature selection and construction or quantitative association rule mining. The chapter also accentuates diversity of background knowledge. In genomics, it can be stored in formats such as free texts, ontologies, pathways, links among biological entities and many others. The authors hope that understanding of automated integration of heterogeneous data sources helps researchers to reach compact and transparent as well as biologically valid and plausible results of their gene-expression data analysis. This chapter points out the role of genomic background knowledge in gene expression data mining. The authors demonstrate its application in several tasks such as relational descriptive analysis, constraint-based knowledge discovery, feature selection and construction or quantitative association rule mining. The chapter also accentuates diversity of background knowledge. In genomics, it can be stored in formats such as free texts, ontologies, pathways, links among biological entities and many others. The authors hope that understanding of automated integration of heterogeneous data sources helps researchers to reach compact and transparent as well as biologically valid and plausible results of their gene-expression data analysis. Tato kapitola popisuje roli apriorní znalosti při dolování dat genové exprese. Existující znalosti ve formě textů, genových ontologií nebo signálních a metabolických stezek mohou být využity k automatickému zpřesňování genomické klasifikace nebo předvýběru vysvětlitelných vzorů přítomných v datech genové exprese.
dcterms:title
Dolování dat genové exprese řízené apriorní znalostí Gene Expression Mining Guided by Background Knowledge Gene Expression Mining Guided by Background Knowledge
skos:prefLabel
Gene Expression Mining Guided by Background Knowledge Dolování dat genové exprese řízené apriorní znalostí Gene Expression Mining Guided by Background Knowledge
skos:notation
RIV/68407700:21230/09:03151583!RIV09-AV0-21230___
n3:aktivita
n11:P
n3:aktivity
P(1ET101210513)
n3:dodaniDat
n9:2009
n3:domaciTvurceVysledku
n7:5879523 n7:5523036 n7:7879830
n3:druhVysledku
n13:C
n3:duvernostUdaju
n6:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
316051
n3:idVysledku
RIV/68407700:21230/09:03151583
n3:jazykVysledku
n15:eng
n3:klicovaSlova
association rule; data mining; feature extraction; gene expression; knowledge; pattern
n3:klicoveSlovo
n8:data%20mining n8:pattern n8:feature%20extraction n8:association%20rule n8:gene%20expression n8:knowledge
n3:kontrolniKodProRIV
[1AEE949F2B90]
n3:mistoVydani
Hershey
n3:nazevZdroje
Data Mining and Medical Knowledge Management: Cases and Applications
n3:obor
n19:JC
n3:pocetDomacichTvurcuVysledku
3
n3:pocetStranKnihy
467
n3:pocetTvurcuVysledku
6
n3:projekt
n12:1ET101210513
n3:rokUplatneniVysledku
n9:2009
n3:tvurceVysledku
Trajkovski, I. Železný, Filip Kléma, Jiří Karel, Filip Cremilleux, B. Tolar, J.
s:numberOfPages
25
n18:hasPublisher
IGI Publishing
n20:isbn
978-1-60566-218-3
n14:organizacniJednotka
21230