TY - CHAP
T1 - Gene expression mining guided by background knowledge
AU - Kléma, Jiří
AU - Železný, Filip
AU - Trajkovski, Igor
AU - Karel, Filip
AU - Crémilleux, Bruno
AU - Tolar, Jakub
PY - 2009
Y1 - 2009
N2 - 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, constraintbased 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.
AB - 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, constraintbased 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.
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U2 - 10.4018/978-1-60566-218-3.ch013
DO - 10.4018/978-1-60566-218-3.ch013
M3 - Chapter
AN - SCOPUS:84901558168
SN - 9781605662183
SP - 268
EP - 292
BT - Data Mining and Medical Knowledge Management
PB - IGI Global
ER -