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- W2370989738 abstract "Objective To deduce the interactions between genes from time series microarray data.Methods We used inter-transaction association rules mining technique and GO (Gene Ontology) annotation to analyze the microarray data. Results Using 2-fold-change method, 119 differential expression genes were identified from total 10 080 genes or ESTs, whose expression levels varied significantly on 6 periods of fetus cerebellar development. As a result, about 1 300 inter-transaction association rules were extracted and 10 top rules were kept for their maximum J-measure values. A genes association network graph was deduced based on the 10 top rules. Conclusion Inter-transaction association rules are able to deduce the interactions between genes from time series microarray data and the gene expression status can be predicted based on the association rules." @default.
- W2370989738 created "2016-06-24" @default.
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- W2370989738 date "2008-01-01" @default.
- W2370989738 modified "2023-09-25" @default.
- W2370989738 title "Mining inter-transaction association rules from time series microarray data" @default.
- W2370989738 hasPublicationYear "2008" @default.
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