Maqungo Monique, Kaur Mandeep, Kwofie Samuel K, Radovanovic Aleksandar, Schaefer Ulf, Schmeier Sebastian, Oppon Ekow, Christoffels Alan, Bajic Vladimir B
South African National Bioinformatics Institute, University of the Western Cape, Private Bag-X17, Modderdam Road, Bellville, Cape Town, South Africa.
Nucleic Acids Res. 2011 Jan;39(Database issue):D980-5. doi: 10.1093/nar/gkq849. Epub 2010 Sep 29.
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/.
前列腺癌(PC)是男性中最常被诊断出的癌症之一。由于缺乏明显的早期症状,PC相对难以诊断。对PC的广泛研究产生了大量关于PC的数据。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愈方法。尽管有这些积累的信息,但有效的诊断和治疗仍然难以实现。我们开发了前列腺癌相关基因龙数据库(DDPC),作为一个经过实验验证与PC相关的基因的综合知识库。DDPC与其他数据库的不同之处在于:(i)它提供了关于PC的预编译生物医学文本挖掘信息,否则需要繁琐的计算分析;(ii)它整合了分子相互作用、途径、基因本体、分子水平的基因调控、PC相关基因启动子上预测的转录因子结合位点以及与这些结合位点对应的转录因子的数据;(iii)它包含与PC相关药物的药物银行数据。我们相信这个资源将作为PC研究的有用信息来源。学术和非营利用户可通过http://apps.sanbi.ac.za/ddpc/和http://cbrc.kaust.edu.sa/ddpc/免费访问DDPC。