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MalaCards: an integrated compendium for diseases and their annotation

机译:马拉卡:疾病及其注释的综合纲要

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摘要

Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research.>Database URL:
机译:全面的疾病分类,整合和注释对于生物医学发现至关重要。目前,疾病的汇编还不完整,种类繁多,而且常常缺乏系统的询问机制。我们以人类基因GeneCards数据库的架构和策略为模型,介绍MalaCards,这是一个人类疾病及其注释的集成数据库。 MalaCards挖掘并合并了44个数据源,以针对16 919种人类疾病中的每一种生成计算机化卡片。每个MalaCard都包含特定于疾病的优先注释,以及疾病间的连接,这些连接由GeneCards关系数据库,其搜索和GeneDecks集分析支持。首先,我们使用疾病名称统一启发式方法从15个排名来源生成疾病列表。接下来,我们使用四种方案来填充MalaCards部分:(i)直接询问疾病资源,以建立综合的疾病名称,同义词,摘要,药物/治疗方法,临床特征,基因检测和解剖背景; (ii)在GeneCards中搜索相关出版物,以及具有相应相关性得分的相关基因; (iii)分析GeneDecks中与疾病相关的基因集,以产生相关的途径,表型,化合物和GO术语,并按综合相关性得分排序,并带有GeneCards链接; (iv)在MalaCards本身内进行搜索,例如用于其他相关疾病和解剖背景。后者构成了基于共享的MalaCards注释构建疾病网络的基础,体现了基于病因,临床特征和临床状况的关联。这个分布广泛的网络具有幂律度分布,表明这可能是此类网络的固有属性。正在进行的工作包括等级疾病分类,本体映射和疾病集分析,努力使MalaCards成为用于生物医学研究的更加有效的工具。>数据库URL:

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