Biological Data Warehousing System for Identifying Transcriptional Regulatory Sites From Gene Expressions of Microarray Data

[[abstract]]Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and oneORnucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems

miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes

Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNA targets. The known miRNA genes in four mammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based on comparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNA targets within the conserved regions in 3′-UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap. The database is freely available at

miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes

Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNAtargets. The knownmiRNAgenes in fourmammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based oncomparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNAtargets within the conserved regions in 30-UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap

miRTarBase: a database curates experimentally validated microRNA–target interactions

MicroRNAs (miRNAs), i.e. small non-coding RNA molecules (∼22 nt), can bind to one or more target sites on a gene transcript to negatively regulate protein expression, subsequently controlling many cellular mechanisms. A current and curated collection of miRNA–target interactions (MTIs) with experimental support is essential to thoroughly elucidating miRNA functions under different conditions and in different species. As a database, miRTarBase has accumulated more than 3500 MTIs by manually surveying pertinent literature after data mining of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assays, western blot, or microarray experiments with overexpression or knockdown of miRNAs. miRTarBase curates 3576 experimentally verified MTIs between 657 miRNAs and 2297 target genes among 17 species. miRTarBase contains the largest amount of validated MTIs by comparing with other similar, previously developed databases. The MTIs collected in the miRTarBase can also provide a large amount of positive samples to develop computational methods capable of identifying miRNA–target interactions. miRTarBase is now available on http://miRTarBase.mbc.nctu.edu.tw/, and is updated frequently by continuously surveying research articles

Analysis of NQO1 polymorphisms and p53 protein expression in patients with hepatocellular carcinoma

NAD(P)H: quinone oxidoreductase 1 (NQO1), a cytosolic enzyme which catalyzes the twoelectron reduction of quinone compounds, has been suggested to prevent the generation of semiquinone free radicals and reactive oxygen species, thus protecting cells from oxidative damage. However, the enzymatic activity of NQO1 strongly depends on the individual genetic polymorphism of the NQO1 gene. A common NQO1 polymorphism is a C to T transition at position 609, which results in an inactive enzyme. Recent studies showed that NQO1 is an important enzyme for stabilizing p53 protein, which is involved in antitumorigenesis. Thus, the lack of enzymatic activity in the homozygous C609T NQO1 polymorphism may play a pivotal role in tumor development. This study aimed to investigate the relationship between C609T NQO1 polymorphism and p53 expression in human hepatocellular carcinoma (HCC). Genotyping of NQO1 was performed on 100 HCC specimens by PCR-RFLP analysis. In addition, NQO1 and p53 protein expression in HCC samples at different TNM stages was determined by immunohistochemistry. Our data showed that (1) the frequency of C609T NQO1 was significantly increased in TNM stage III HCC patients; (2) no significant association was found between p53 expression and C609T polymorphism of NQO1 gene; and (3) a tumor/non-tumor (T/N) ratio > 1.27 of NQO1 expression revealed by real-time qPCR analyses was positively correlated with poorer survival in patients with tumors >5 cm, suggesting that an increase of NQO1 expression may be an indicator of advanced tumor progression. This study provides important information about NQO1 genotypes and its expression to HCC tumor development and progression

Large-Scale Investigation of Human TF-miRNA Relations Based on Coexpression Profiles

Noncoding, endogenous microRNAs (miRNAs) are fairly well known for regulating gene expression rather than protein coding. Dysregulation of miRNA gene, either upregulated or downregulated, may lead to severe diseases or oncogenesis, especially when the miRNA disorder involves significant bioreactions or pathways. Thus, how miRNA genes are transcriptionally regulated has been highlighted as well as target recognition in recent years. In this study, a large-scale investigation of novel cis- and trans-elements was undertaken to further determine TF-miRNA regulatory relations, which are necessary to unravel the transcriptional regulation of miRNA genes. Based on miRNA and annotated gene expression profiles, the term “coTFBS” was introduced to detect common transcription factors and the corresponding binding sites within the promoter regions of each miRNA and its coexpressed annotated genes. The computational pipeline was successfully established to filter redundancy due to short sequence motifs for TFBS pattern search. Eventually, we identified more convinced TF-miRNA regulatory relations for 225 human miRNAs. This valuable information is helpful in understanding miRNA functions and provides knowledge to evaluate the therapeutic potential in clinical research. Once most expression profiles of miRNAs in the latest database are completed, TF candidates of more miRNAs can be explored by this filtering approach in the future

miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes

Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNAtargets. The knownmiRNAgenes in fourmammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based oncomparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNAtargets within the conserved regions in 30-UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap