Gene cards

GeneCards, gene cards, the gene cards gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression.

Download chapter PDF. Its popularity encouraged the expansion of the knowledgebase to provide the same functionality for diseases and pathways. Together with this growth came the realization that the depth and breadth of the data itself, while extremely useful in its own right, could be leveraged to solve problems. Today, there is increasing recognition by the scientific community that NGS is a pivotal technology for diagnosing the genetic cause of many human diseases; several large-scale projects implement NGS as a key instrument for elucidating the genetic components of rare diseases and cancer Bamshad et al. Other clinical studies aimed at deciphering monogenic and complex diseases have also demonstrated the effectiveness of NGS approaches including whole genome, whole exome, and gene panel sequencing van den Veyver and Eng ; Yang et al.

Gene cards

GeneCards www. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards' unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene's functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite. Database URL: www. Abstract GeneCards www. Publication types Research Support, Non-U.

It also presents manually curated gene expression at all developmental stages, gene cards well as data extracted from high-throughput experiments and large-scale in situ databases. Another example is a research study on synthetic lethality in cancer.

GeneCards is a database of human genes that provides genomic , proteomic , transcriptomic , genetic and functional information on all known and predicted human genes. The database aims at providing a comprehensive view of the current available biomedical information about the searched gene, including its aliases and identifiers, the encoded proteins , associated diseases and variations, its function, relevant publications and more. Since , the GeneCards database has been widely used by bioinformatics , genomics and medical communities for more than 24 years. Since the s, sequence information has become increasingly abundant; subsequently many laboratories realized this and began to store such information in central repositories-the primary database. Since , 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.

You must indicate the input species before inserting your gene set. This information is only required in order to identify your gene symbols and their orthologs. The matching algorithm considers genes and gene orthologs, and differs between the distinct sections:. Please note that changing the input species after inserting gene symbols will activate a new identification process. GeneAnalytics identifies official human and mouse gene symbols only.

Gene cards

Expression-based analysis is based on data which were manually collected, filtered, modeled, annotated and integrated in our knowledgebase. Gene expression data for normal and diseased tissues and cells are separated and displayed in different sections. Provides the most valuable results without the need for complex bioinformatics expertise or tools. Developed by biologists, for biologists! Results are directly linked to detailed cards in the LifeMap integrated biomedical knowledgebase and to relevant external data sources. Provides categorized results lists of matched tissues, cells, diseases, pathways, compounds and gene ontology GO terms to enhance gene set interpretation. The expression-based matching algorithm considers gene annotations including gene -disease association and gene specificity, enrichment or abundance in each specific tissue or cell.

Dakine shop germany

Before releasing a version of the knowledgebase, the system undergoes a semi-automated QA process. One study aimed to diagnose recurrent CNVs associated with syndromic short stature of unknown cause Homma et al. Inactivation targets were extracted after the microarray experiments of resistant and non-resistant neuroblastoma cell lines. BMC Genomics BMC Med Genomics Eur J Paediatr Neurol 20 1 — A list of matched phenotypes is shown in red in the top part. In this example, the genome of a 6 year old boy, who suffered from atypical epilepsy combined with retinitis pigmentosa, was sequenced. If material is not included in the chapter's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Article PubMed Google Scholar. Its popularity encouraged the expansion of the knowledgebase to provide the same functionality for diseases and pathways. PLoS One 8 7 :e The knowledgebase, for the most part, is automatically generated. We illustrate exploring and browsing of the various suite sites by describing the MalaCards Rappaport et al.

GeneCards www. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards' unique wealth of combinatorial annotations.

Subsequently, analysis pipelines sift these SNPs and indels by populating the VCF file with annotation data, such as segregation in affected families, genetic linkage information Smith et al. In this case, a family with a rare congenital autosomal dominant genetic skin disease was genotyped, leading to the identification of a CNV shared by all affected individuals. Secondly, the search result page shows all relevant minicards. It includes High, Medium, Low, and custom range. N Engl J Med 16 — Abstract GeneCards www. In this example, the genome of a 6 year old boy, who suffered from atypical epilepsy combined with retinitis pigmentosa, was sequenced. Specifically, GeneCards is gene-centered, the one-stop-shop for comprehensive details related to genes of interest. Clin Genet 87 6 — Publisher Name : Springer, Singapore.