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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 technique...

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Autores principales: Kaur, Mandeep, Radovanovic, Aleksandar, Essack, Magbubah, Schaefer, Ulf, Maqungo, Monique, Kibler, Tracey, Schmeier, Sebastian, Christoffels, Alan, Narasimhan, Kothandaraman, Choolani, Mahesh, Bajic, Vladimir B.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2686485/
https://www.ncbi.nlm.nih.gov/pubmed/18790805
http://dx.doi.org/10.1093/nar/gkn593
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author Kaur, Mandeep
Radovanovic, Aleksandar
Essack, Magbubah
Schaefer, Ulf
Maqungo, Monique
Kibler, Tracey
Schmeier, Sebastian
Christoffels, Alan
Narasimhan, Kothandaraman
Choolani, Mahesh
Bajic, Vladimir B.
author_facet Kaur, Mandeep
Radovanovic, Aleksandar
Essack, Magbubah
Schaefer, Ulf
Maqungo, Monique
Kibler, Tracey
Schmeier, Sebastian
Christoffels, Alan
Narasimhan, Kothandaraman
Choolani, Mahesh
Bajic, Vladimir B.
author_sort Kaur, Mandeep
collection PubMed
description 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/.
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spelling pubmed-26864852009-05-26 Database for exploration of functional context of genes implicated in ovarian cancer Kaur, Mandeep Radovanovic, Aleksandar Essack, Magbubah Schaefer, Ulf Maqungo, Monique Kibler, Tracey Schmeier, Sebastian Christoffels, Alan Narasimhan, Kothandaraman Choolani, Mahesh Bajic, Vladimir B. Nucleic Acids Res Articles 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/. Oxford University Press 2009-01 2008-09-12 /pmc/articles/PMC2686485/ /pubmed/18790805 http://dx.doi.org/10.1093/nar/gkn593 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Kaur, Mandeep
Radovanovic, Aleksandar
Essack, Magbubah
Schaefer, Ulf
Maqungo, Monique
Kibler, Tracey
Schmeier, Sebastian
Christoffels, Alan
Narasimhan, Kothandaraman
Choolani, Mahesh
Bajic, Vladimir B.
Database for exploration of functional context of genes implicated in ovarian cancer
title Database for exploration of functional context of genes implicated in ovarian cancer
title_full Database for exploration of functional context of genes implicated in ovarian cancer
title_fullStr Database for exploration of functional context of genes implicated in ovarian cancer
title_full_unstemmed Database for exploration of functional context of genes implicated in ovarian cancer
title_short Database for exploration of functional context of genes implicated in ovarian cancer
title_sort database for exploration of functional context of genes implicated in ovarian cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2686485/
https://www.ncbi.nlm.nih.gov/pubmed/18790805
http://dx.doi.org/10.1093/nar/gkn593
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