Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Integrating Classification and Association Rule Mining: A Concept Lattice Framework
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Consensus algorithms for the generation of all maximal bicliques
Discrete Applied Mathematics - The fourth international colloquium on graphs and optimisation (GO-IV)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Review: Computational identification of microRNAs and their targets
Computational Biology and Chemistry
Detecting MicroRNA targets by linking sequence, MicroRNA and gene expression data
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Computers in Biology and Medicine
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The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures. This study proposes a computational method to discover the functional miRNA-mRNA regulatory modules (FMRMs), that is, groups of miRNAs and their target mRNAs that are believed to participate cooperatively in post-transcriptional gene regulation under specific conditions. The proposed method identifies negatively regulated patterns of miRNAs and mRNAs which associate with cancer and normal conditions, respectively, in a prostate cancer data set. GO and the literature also suggest that they may relate with prostate cancer. It can potentially identify the biologically relevant chains of 'miRNA-target gene - condition'.