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Identifying gene functional modules is an important step towards elucidating gene functions at a global scale. In this paper, we introduce a simple method to construct gene co-expression networks from microarray data, and then propose an efficient spectral clustering algorithm to identify natural communities, which are relatively densely connected sub-graphs, in the network. To assess the effectiveness of our approach and its advantage over existing methods, we develop a novel method to measure the agreement between the gene communities and the modular structures in other reference networks, including protein-protein interaction networks, transcriptional regulatory networks, and gene networks derived from gene annotations. We evaluate the proposed methods on two large-scale gene expression data in budding yeast and Arabidopsis thaliana. The results show that the clusters identified by our method are functionally more coherent than the clusters from several standard clustering algorithms, such as k-means, self-organizing maps, and spectral clustering, and have high agreement to the modular structures in the reference networks. [ABSTRACT FROM AUTHOR]

MicroRNAs are short, noncoding RNAs that play important roles in post-transcriptional regulation. Although many functions of microRNAs in plants and animals have been revealed in recent years, the transcriptional mechanism of microRNA genes is not well understood. To elucidate the transcriptional regulation of microRNA genes, we study and characterize, in a genome scale, the promoters of intergenic microRNA genes in Caenorhabditis elegans, Homo sapiens and Arabidopsis thaliana. Specifically, we show that the known microRNA genes in these species have the same type of promoters as the protein-coding genes. To further characterize the promoters of miRNA genes, we develop a miRNA core promoter prediction method, called common query voting (CoVote). We applied this new method to identify putative core promoters of most known microRNA genes in the three model species of choice. [ABSTRACT FROM AUTHOR]