Browsing by Author "Maqungo, Monique"

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    Database for exploration of functional context of genes implicated in ovarian cancer
    (Oxford Journals, 2009) Kaur, Mandeer; Radovanovic, Aleksander; Essack, Magbubah; Schaefer, Ulf; Maqungo, Monique; Kibler, Tracey; Schmeier, Sebastian; Christoffels, Alan; Narasimhan, Kothandaraman; Choolani, Mahesh; Bajic, Vladimir B.
    Ovarian cancer (OC) is becoming the most common gynecological cancer in developed countries and the most lethal gynecological malignancy. It is also the fifth leading cause of all cancer-related deaths in women. The identification of diagnostic biomarkers and development of early detection techniques for OC largely depends on the understanding of the complex functionality and regulation of genes involved in this disease. Unfortunately, information about these OC genes is scattered throughout the literature and various databases making extraction of relevant functional information a complex task. To reduce this problem, we have developed a database dedicated to OC genes to support exploration of functional characterization and analysis of biological processes related to OC. The database contains general information about OC genes, enriched with the results of transcription regulation sequence analysis and with relevant text mining to provide insights into associations of the OC genes with other genes, metabolites, pathways and nuclear proteins. Overall, it enables exploration of relevant information for OC genes from multiple angles, making it a unique resource for OC and will serve as a useful complement to the existing public resources for those interested in OC genetics.
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    DDPC: Dragon database of genes associated with prostate cancer
    (Oxford Journals, 2011) Maqungo, Monique; Kaur, Mandeep; Kwofie, Samuel K.; Radovanovic, Aleksander; Schaefer, Ulf; Schmeier, Sebastian; Oppon, Ekow; Christoffels, Alan; Bajic, Vladimir B.
    Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC.