In silico study of regulatory relationship between microRNA and cancer by gene expression profiles  function annotations and cancerous pathway information

ASIAIR > College of Computer Science > Department of Biomedical informatics > Theses & dissertations > Item 310904400/2670

Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/2670

Title:	In silico study of regulatory relationship between microRNA and cancer by gene expression profiles function annotations and cancerous pathway information
Authors:	Chia-Wei Weng
Contributors:	Department of Bioinformatics
Keywords:	microRNA;Microarray Data Analysis;Pearson Correlation Coefficient;Tumor Suppressor Gene;Oncogene
Date:	2009
Issue Date:	2009-11-06 14:33:47 (UTC+0)
Publisher:	Asia University
Abstract:	MicroRNA is a kind of non-coding RNA which can be discovered across animals, plants and viruses. MicroRNA can participate in many biological processes by repression and/or cleavage messenger RNA. Recently studies indicated that there is regulatory relationship between carcinogenesis and mutant or aberrant expression of microRNAs, such as carcinogenesis in breast cancer, lung cancer and liver cancer etc. Some studies even have revealed microRNAs can play the role of an oncogene or tumor suppressor gene. This study integrated various biological data to investigate the regulatory relationships between microRNA and cancer. In this study, we adopted data in the TarBase database and integrated RNA microarray profiles of NCI-60 mutation cancer cell lines. In order to quantify the strength of correlation for microRNA and mRNA expression in nine classes of cancer, which are the Breast cancer, Central Neural System, Colon, Lung, Leukemia, Melanoma, Ovarian, Prostate and Renal, the pearson correlation coefficient and spearman rank correlation coefficient are utilized to determine correlation. A negative correlation coefficient is used to filter out microRNA targeting genes in nine cancer tissues. In this study, OMIM database are adopted to evaluate the correlation coefficient. It is found that the correlation approach can identify certain microRNA targeting cancer genes. Our study also integrated the Gene Ontology and KEGG database records. This study have investigated specific GO terms with filtered information of negative correlated target genes in nine tissues. Another data of cancer related pathway, we have utilized this information to investigate regulatory pathways in microRNA target genes. We have utilized the above three pieces of information to provide a platform in investigation of potential cancer related microRNAs. Website: http://ppi.bioinfo.asia.edu.tw/mirna_target
Appears in Collections:	[Department of Biomedical informatics ] Theses & dissertations

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