Gene cards

GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human gene cards, diseases, gene cards, 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.

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.

Gene cards

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. 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 these analyses, variants are analyzed without regard to the disease phenotype of the sequenced individual. As a first step in introducing phenotype relationships, many pipelines use variant-disease relationships e. But a typical gene can have a multitude of variants that have not yet been documented to have a relationship with a disease or a phenotype. In many cases, none of the annotated variant-disease relations appears relevant to the sequenced subject.

Download as PDF Printable version, gene cards. MalaCards search results: a sorted, scored gene hits. Initially, at least 10 affiliated genes are shown all of the elite genes are always shownwith an option to see the complete list.

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. Version 3 of the database gathers information from more than 90 database resources based on a consolidated gene list.

GeneAnalytics is a powerful and user friendly gene set analysis tool that can rapidly contextualize experimental gene expression, and function, signatures derived from next generation sequencing of DNA and RNA and from microarray analyses. It leverages LifeMap's extensive integrated biomedical knowledgebase including, GeneCards , MalaCards and LifeMap Discovery , which utilize data from more than sources. Accessing this extensive biomedical knowledgebase enables GeneAnalytics to effectively identify tissues and cell types, and various diseases, that match experimental gene sets, based on shared gene expression patterns. GeneAnalytics can also identify diseases, biological pathways and compounds that are associated with experimental gene sets based on shared gene functionality. GeneAnalytics presents the analysis results attractively and interactively, with links to supporting data and further information. GeneAnalytics enables researchers to identify tissues and cell types related to their gene sets of interest. This results section is only leverages data for normal tissues and cells.

Gene cards

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. 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 these analyses, variants are analyzed without regard to the disease phenotype of the sequenced individual.

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Horm Res Paediatr 89 1 — It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Future Oncol 12 11 — Archived from the original PDF on Safran, M. As our heuristics are still evolving, problematic disease names e. It also presents manually curated gene expression at all developmental stages, as well as data extracted from high-throughput experiments and large-scale in situ databases. Navigation Find a journal Publish with us Track your research. Database Oxford baq Oncol Rep 35 6 —

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Springer, Singapore. Cell 3 — 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. Others reflect sophisticated behind-the-scenes data amalgamation: Compound groups, unified from 12 sources, with drug-specific and drug-gene annotations; GeneHancer Fishilevich et al. To this aim, TGex, the GeneCards Suite Knowledge-Driven Clinical Genetics Analysis platform, combines VarElect strength with comprehensive variant annotation and filtering capabilities in a consolidated view, which enables the genetic analyst to quickly pinpoint the strongest candidates. Trends in Genetics. CEN Case Rep 8 1 — Bibcode : NatSR Genes Nutr This evidence is combined by MalaCards-based evidence, showing queried phenotype associations in diseases associated with the gene SHOX, from various MalaCards sections, e. Another example is a research study on synthetic lethality in cancer.