Database for exploration of functional context of genes implicated in ovarian cancer.
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. Access is free for academic and non-profit users and database can be accessed at http://apps.sanbi.ac.za/ddoc/.
Kaur
Mandeep
M
South African National Bioinformatics Institute, University of the Western Cape, Private Bag- X17, Modderdam Road, Bellville, Cape Town, South Africa.
Radovanovic
Aleksandar
A
Essack
Magbubah
M
Schaefer
Ulf
U
Maqungo
Monique
M
Kibler
Tracey
T
Schmeier
Sebastian
S
Christoffels
Alan
A
Narasimhan
Kothandaraman
K
Choolani
Mahesh
M
Bajic
Vladimir B
VB
D001665:Binding Sites; D030541:Databases, Genetic; D005260:Female; D053263:Gene Regulatory Networks; D052138:Genes, Neoplasm; D006801:Humans; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000378:metabolism; D011401:Promoter Regions, Genetic; D014157:Transcription Factors / Q000378:metabolism
D014157:Transcription Factors
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