NAR Molecular Biology Database Collection entry number 1970
Rappaport, Noa; Twik, Michal; Plaschkes, Inbar; Nudel, Ron; Iny Stein, Tsippi; Levitt, Jacob; Gershoni, Moran; Morrey, C; Safran, Marilyn; Lancet, Doron
1 Department of Molecular Genetics, the Weizmann Institute of Science, Rehovot, 76100, Israel 2 Department of Information Systems and Technology, Utah Valley University, Orem, UT 84058, USA

Database Description

In 2013, we released MalaCards, an integrated compendium of diseases and their annotations (1). MalaCards tackles many of the problems that stem from the complexity of disease data and from the multiplicity of information sources. This is accomplished by employing sophisticated data-mining strategies modelled after the widely-used GeneCards database. The present report reviews these ongoing strategies, and highlights improvements and new implementations.
Diseases are mined from 68 data sources. MalaCards has a web card for each of ~20,000 disease entries, in six global categories (2). 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.


The authors thank Raphael Zidovetzki, Gil Stelzer, IrisBahir and Yaron Golan for assistance with data source allocation and database improvements. The authors also thank MalaCards users for their feedback and support. .This work was supported by LifeMap Sciences Inc., CA, USA, and by the Crown Human Genome Center at the Weizmann Institute of Science.


1. Rappaport,N., Nativ,N., Stelzer,G., Twik,M., Guan-Golan,Y., Stein,T.I., Bahir,I., Belinky,F., Morrey,C.P., Safran,M. et al. (2013) MalaCards: an integrated compendium for diseases and their annotation. Database, 2013, bat018.
2. Rappaport,N., Twik,M., Nativ,N., Stelzer,G., Bahir,I., Stein,T.I., Safran,M. and Lancet,D. (2014) MalaCards: a comprehensive automatically-mined database of human diseases. Curr. Protoc. Bioinformatics, 47, doi:10.1002/0471250953.bi0124s47.

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