FAIRsharing record for: MalaCards

This FAIRsharing record describes: The MalaCards human disease database (http://www. malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ?20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards? affiliation with the GeneCards Suite of databases. MalaCards? capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ?flat? disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.本FAIRsharing记录介绍如下内容：人类疾病数据库MalaCards（官网地址：http://www.malacards.org）是一套整合自68个数据源的注释疾病集成汇编。MalaCards为约20000个疾病条目提供了专属网页卡片，涵盖六大全球疾病分类，包含15个板块的多维度注释主题，具体包括摘要、症状、解剖背景、药物、基因检测、变异及文献等。其“别名与分类”板块集成了一套可解决多源疾病名称冲突的算法，能够实现高效的注释信息整合。该数据库的核心特色之一是均衡化的基因板块，其内置评分可反映疾病与基因之间关联的强度。此外，依托与GeneCards Suite数据库套件的隶属关系，MalaCards还附带了通路、小鼠表型及基因本体（Gene Ontology，GO）术语等其他与基因相关的疾病信息。MalaCards能够整合互补数据源的信息，搭配其完善的检索功能、关系型数据库架构与便捷的数据导出功能，可应对丰富的疾病注释场景，并支持系统分析与基因组序列解读工作。MalaCards采用“扁平化”的疾病卡片设计模式，但每张卡片均映射至主流的分层本体体系（如国际疾病分类（International Classification of Diseases）、人类表型本体（Human Phenotype Ontology）及统一医学语言系统（Unified Medical Language System）），同时还包含疾病间的多层次关联信息，从而成为疾病表征与审校的理想工具。