DDPC: Dragon Database of Genes associated with Prostate Cancer.

DDPC: Dragon Database of Genes associated with Prostate Cancer.
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DOI:
10.1093/nar/gkq849
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发表时间:
2011-01
影响因子:
14.9
通讯作者:
Bajic VB
Bajic VB
中科院分区:
生物学2区
文献类型:
--
作者:
Maqungo M;Kaur M;Kwofie SK;Radovanovic A;Schaefer U;Schmeier S;Oppon E;Christoffels A;Bajic VB

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前列腺癌(PC)是男性最常见的癌症之一。由于缺乏明确的早期症状,PC相对较难诊断。对PC的广泛研究使得PC上的大量数据变得可用。数百个基因与PC的不同阶段有关,这可能有助于开发诊断方法甚至治疗方法。尽管有这些积累的信息,有效的诊断和治疗仍然是含糊其辞的。我们已经开发了与前列腺癌相关的基因龙数据库(DDPC),作为经实验验证与前列腺癌相关的基因的完整知识库。DDPC与其他数据库的不同之处在于:(I)它提供了PC上预先汇编的生物医学文本挖掘信息,否则需要进行繁琐的计算分析;(Ii)它集成了分子相互作用、途径、基因本体论、分子水平上的基因调控、预测的PC相关基因启动子上的转录因子结合位点以及与这些结合位点相对应的转录因子;(Iii)它包含与PC相关的药物的DrugBank数据。我们相信,这一资源将成为PC研究的有用信息来源。学术和非营利组织用户可以通过http://apps.sanbi.ac.za/ddpc/和http://cbrc.kaust.edu.sa/ddpc/.免费访问DDPC
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. DDPC is freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/ddpc/ and http://cbrc.kaust.edu.sa/ddpc/.
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