Database for exploration of functional context of genes implicated in ovarian cancer
Database for exploration of functional context of genes implicated in ovarian cancer
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DOI：
10.1093/nar/gkn593
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发表时间：
2009-01-01
影响因子：
14.9
通讯作者：
Bajic, Vladimir B.
中科院分区：
文献类型：
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作者：
Kaur, Mandeep;Radovanovic, Aleksandar;Bajic, Vladimir B.
卵巢癌（OC）正在成为发达国家最常见的妇科癌症，也是最致命的妇科恶性肿瘤。它也是女性所有癌症相关死亡的第五大原因。 OC 诊断生物标志物的鉴定和早期检测技术的开发很大程度上取决于对该疾病所涉及基因的复杂功能和调控的理解。不幸的是，有关这些 OC 基因的信息分散在文献和各种数据库中，使得提取相关功能信息成为一项复杂的任务。为了减少这个问题，我们开发了一个专门针对 OC 基因的数据库，以支持与 OC 相关的功能表征和生物过程分析的探索。该数据库包含有关 OC 基因的一般信息，并通过转录调控序列分析和相关文本挖掘的结果进行丰富，以深入了解 OC 基因与其他基因、代谢物、途径和核蛋白的关联。总体而言，它能够从多个角度探索OC基因的相关信息，使其成为OC的独特资源，并将成为对OC遗传学感兴趣的现有公共资源的有益补充。学术和非营利用户可以免费访问，数据库可以通过 http://apps.sanbi.ac.za/ddoc/ 访问。
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/.