MalaCards: an integrated compendium for diseases and their annotation.
MalaCards: an integrated compendium for diseases and their annotation.
复制标题
DOI：
10.1093/database/bat018
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Lancet D
中科院分区：
文献类型：
--
作者：
Rappaport N;Nativ N;Stelzer G;Twik M;Guan-Golan Y;Stein TI;Bahir I;Belinky F;Morrey CP;Safran M;Lancet D
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，疾病汇编不完整，异构，往往缺乏系统的查询机制。我们介绍MalaCards，人类疾病及其注释的综合数据库，仿照人类基因的GeneCards数据库的架构和策略。MalaCards挖掘并合并了44个数据源，为16919种人类疾病中的每一种生成了一张计算机化的卡片。每个MalaCard都包含疾病特异性优先注释，以及疾病间的联系，由GeneCards关系数据库，其搜索和GeneDecks集分析授权。首先，我们从15个排名的来源，使用疾病名称统一算法生成一个疾病列表。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，以建立综合疾病名称、同义词、摘要、药物/治疗、临床特征、基因测试和解剖学背景;（ii）搜索GeneCards以获得相关出版物和具有相应相关性分数的相关基因;（iii）分析GeneDeck中的疾病相关基因集以产生附属途径、表型、化合物和GO术语，其通过复合相关性得分排序并与GeneCards链接一起呈现;以及（iv）在MalaCards本身内进行搜索，例如寻找其他相关疾病和解剖背景。后者形成了基于共享MalaCards注释的疾病网络构建的基础，体现了基于病因学、临床特征和临床状况的关联。这个广泛分布的网络具有幂律度分布，这表明这可能是此类网络的固有属性。正在进行的工作包括疾病分级分类、本体映射和疾病集分析，努力使MalaCards成为生物医学研究的更有效工具。数据库URL：http://www.malacards.org/
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: http://www.malacards.org/