|Human genes and model orthologues|
|Research center||Crown Human Genome Center, WIS|
|Primary citation||PMID 9097728|
GeneCards is a database of human genes that provides genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. It is being developed and maintained by the Crown Human Genome Center at the Weizmann Institute of Science.
The database aims at providing a quick overview of the current available biomedical information about the searched gene, including the human genes, the encoded proteins, and the relevant diseases. The GeneCards database provides access to free Web resources about more than 7000 all known human genes that integrated from >90 data resources, such as HGNC, Ensembl, and NCBI. The core gene list is based on approved gene symbols published by the HUGO Gene Nomenclature Committee (HGNC). The information is carefully gathered and selected from these databases by its engine. If the search does not return any results, this database will give several suggestions to help users accomplish their search depending on the type of query and offer direct links to other databases’ search engine.
Over time, the GeneCards database has developed a suite of tools (GeneDecks, GeneLoc, GeneALaCart) that has more specialised capability. Since 1998, the GeneCards database has been widely used by bioinformatics, genomics and medical communities for more than 15 years.
Since the 1980s, sequence information has become increasingly abundant; subsequently many laboratories realized this and began to store such information in central repositories-the primary database. However, the information provided by the primary sequence databases (lower level databases) focus on different aspects. To gather these scattered data, the Weizmann Institute of Science's Crown Human Genome Centre developed a database called ‘GeneCards’ in 1997. This database mainly dealt with human genome information, human genes, the encoded proteins’ functions, and related diseases, though it has expanded since that time.
Initially, the GeneCards database had two main features: delivery of integrated biomedical information for a gene in ‘card’ format, and a text-based search engine. Since 1998, the database has integrated more data resources and data types, such as protein expression and gene network information. It has also improved the speed and sophistication of the search engine, and expanded from a gene-centric dogma to contain gene-set analyses. Version 3 of the database gathers information from more than 90 database resources based on a consolidated gene list. It has also added a suite of GeneCards tools which focus on more specific purposes. "GeneNote and GeneAnnot for transcriptome analyses, GeneLoc for genomic locations and markers, GeneALaCart for batch queries and GeneDecks for finding functional partners and for gene set distillations.". The database updates on a 3-year cycle of planning, implementation, development, semi-automated quality assurance, and deployment. Technologies used include Eclipse, Apache, Perl, XML, PHP, Propel, Java, R and MySQL.
GeneCards can be freely accessed by non-profit institution for educational and research purpose at https://www.genecards.org/ and academic mirror sites. Commercial usage requires a license.
GeneDecks is a novel analysis tool to identify similar or partner genes, which provides a similarity metric by highlighting shared descriptors between genes, based on GeneCards’ unique wealth of combinatorial annotations of human genes.
GeneALaCart is a gene-set-orientated batch-querying engine based on the popular GeneCards database. It allows retrieval of information about multiple genes in a batch query.
The GeneLoc suit member presents an integrated human chromosome map, which is very important for designing a custom-made capture chip, based on data integrated by the GeneLoc algorithm. GeneLoc includes further links to GeneCards, NCBI's Human Genome Sequencing, UniGene, and mapping resources.
Firstly, enter a search term into the blank on the homepages. Searching methods include Keywords, Symbol only, Symbol/Alias/Identifier and Symbol/Alias. The default search option is searching by keywords. When a user searches by keywords, MicroCard and MiniCard are shown. However, when a user searches by Symbol only, they will be directed to GeneCard. Searches may be furthered by clicking on advanced search, where a user can choose section, category, GIFtS, Symbol Source and gene sets directly. Sections include Aliases & Descriptions, Disorders, Drugs & Compounds, Expression in Human Tissues, Function, Genomic Location, Genomic Variants, Orthologs, Paralogs, Pathways & Interactions, Protein Domains/Families, Proteins, Publications, Summaries and Transcripts. The default option is searching for all sections. Categories include Protein-coding, Pseudogenes, RNA genes Genetic Loci, Gene clusters and Uncategorized. The default option is searching for all categories. GIFtS is the GeneCards Inferred Functionality Scores, which gives objective numbers to show the knowledge level about the functionality of human genes. It includes High, Medium, Low, and custom range. Symbol Sources include HGNC (HUGO Gene Nomenclature Committee), EntrezGene (gene-centered information at NCBI), Ensembl, GeneCards RNA genes, CroW21 and so on.
Moreover, the user can choose to search for All GeneCards or Within Gene Subset, which would be more specific and with priority.
Secondly, the search result page shows all relevant minicards. Symbol, Description, Category, GIFtS, GC id and Score are displayed on the page. A user may click on the plus button for each of the mini-cards to open the minicard. Also, the user can click directly on the symbol to see the details of a particular GeneCard.
For a particular GeneCard (example: GeneCard for TGFB1), it is consist of the following contents.
GeneCards is used widely in the biological and biomedical fields. For example, S.H. Shah extracted data of early-onset coronary artery disease from GeneCards to identify genes that contributes to the disease. Chromosome 3q13, 1q25 etc. are confirmed to take effects and this paper further discussed the relationship between morbid genes and serum lipoproteins with the help of GeneCard.
Another example is a research study on synthetic lethality in cancer. Synthetic lethality appears when a mutation in a single gene has no effect on the function of a cell but a mutation in an additional gene leads to cell death. This study aimed to find novel methods of treating cancer through blocking the lethality of drugs. GeneCards was used when comparing data of a given target gene with all possible genes. In this process, the annotation sharing score was calculated using GeneDecks Partner Hunter (now called Genes Like Me) to give paralogy. Inactivation targets were extracted after the microarray experiments of resistant and non-resistant neuroblastoma cell lines.