Rappaport Noa, Twik Michal, Nativ Noam, Stelzer Gil, Bahir Iris, Stein Tsippi Iny, Safran Marilyn, Lancet Doron
Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
Curr Protoc Bioinformatics. 2014 Sep 8;47:1.24.1-19. doi: 10.1002/0471250953.bi0124s47.
Systems medicine provides insights into mechanisms of human diseases, and expedites the development of better diagnostics and drugs. To facilitate such strategies, we initiated MalaCards, a compendium of human diseases and their annotations, integrating and often remodeling information from 64 data sources. MalaCards employs, among others, the proven automatic data-mining strategies established in the construction of GeneCards, our widely used compendium of human genes. The development of MalaCards poses many algorithmic challenges, such as disease name unification, integrated classification, gene-disease association, and disease-targeted expression analysis. MalaCards displays a Web card for each of >19,000 human diseases, with 17 sections, including textual summaries, related diseases, related genes, genetic variations and tests, and relevant publications. Also included are a powerful search engine and a variety of categorized disease lists. This unit describes two basic protocols to search and browse MalaCards effectively.
系统医学有助于深入了解人类疾病的机制,并加速更好的诊断方法和药物的研发。为推动此类策略,我们启动了MalaCards项目,它是一个人类疾病及其注释的汇编,整合并常常重塑来自64个数据源的信息。MalaCards尤其采用了在构建GeneCards(我们广泛使用的人类基因汇编)过程中确立的经过验证的自动数据挖掘策略。MalaCards的开发带来了许多算法挑战,如疾病名称统一、综合分类、基因与疾病关联以及疾病靶向表达分析。MalaCards为19000多种人类疾病中的每一种都展示了一张网络卡片,包含17个部分,包括文本摘要、相关疾病、相关基因、基因变异与检测以及相关出版物。此外还包括一个强大的搜索引擎和各种分类疾病列表。本单元介绍两种有效搜索和浏览MalaCards的基本方案。