GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73,000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. 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.genecards.org.

/pdf/genecards-version-3-the-human-gene-integrator-16k6diq69z.pdf

GeneCards Version 3: the human gene integrator.

The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting.

/pdf/the-ucsc-genome-browser-and-associated-tools-4ivktf0xcg.pdf

The UCSC genome browser and associated tools

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation. IMGT/GENE-DB is freely available at http://imgt.cines.fr.

/pdf/imgt-gene-db-a-comprehensive-database-for-human-and-mouse-3gcieka12y.pdf

IMGT/GENE-DB: a comprehensive database for human and mouse immunoglobulin and T cell receptor genes

The University of California Santa Cruz (UCSC) Genome Browser is a popular Web-based tool for quickly displaying a requested portion of a genome at any scale, accompanied by a series of aligned annotation "tracks." The annotations generated by the UCSC Genome Bioinformatics Group and external collaborators include gene predictions, mRNA and expressed sequence tag alignments, simple nucleotide polymorphisms, expression and regulatory data, phenotype and variation data, and pairwise and multiple-species comparative genomics data. All information relevant to a region is presented in one window, facilitating biological analysis and interpretation. The database tables underlying the Genome Browser tracks can be viewed, downloaded, and manipulated using another Web-based application, the UCSC Table Browser. Users can upload personal datasets in a wide variety of formats as custom annotation tracks in both browsers for research or educational purposes. This unit describes how to use the Genome Browser and Table Browser for genome analysis, download the underlying database tables, and create and display custom annotation tracks.

/pdf/the-ucsc-genome-browser-3kubny2naq.pdf

The UCSC Genome Browser.

Background
The regulatory mechanisms underlying tissue specificity are a crucial part of the development and maintenance of multicellular organisms. A genome-wide analysis of promoters in the context of gene-expression patterns in tissue surveys provides a means of identifying the general principles for these mechanisms.

/pdf/promoter-features-related-to-tissue-specificity-as-measured-3grh4cvfll.pdf

Promoter features related to tissue specificity as measured by Shannon entropy

Recent enhancements and current research in the GeneCards (GC) (http://bioinfo.weizmann.ac.il/cards/) project are described, including the addition of gene expression profiles and integrated gene locations. Also highlighted are the contributions of specialized associated human gene-centric databases developed at the Weizmann Institute. These include the Unified Database (UDB) (http://bioinfo.weizmann.ac.il/udb) for human genome mapping, the human Chromosome 21 database at the Weizmann Insti-tute (CroW 21) (http:// bioinfo.weizmann.ac.il/crow21), and the Human Olfactory Receptor Data Explora-torium (HORDE) (http://bioinfo.weizmann.ac.il/HORDE). The synergistic relationships amongst these efforts have positively impacted the quality, quantity and usefulness of the GeneCards gene compendium.

Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE

Olfactory receptors (ORs) constitute the largest gene-family in the vertebrate genome. We have attempted to provide a comprehensive view of the OR universe through diverse tools of bioinformatics and computational biology. Among others, we have constructed the Human Olfactory Receptor Data Exploratorium (HORDE, http://bioportal.weizmann.ac.il/HORDE/) as a free online resource, which integrates information on ORs from different species. We studied the genomic organization of 853 human ORs and divided the repertoire into 135 clusters, accessible through our new cluster viewer feature. An analysis of intact and pseudogenized ORs in different clusters, as well as of OR expression patterns, is provided, relevant to OR transcription control. Coding single nucleotide polymorphisms were integrated; these are to be used for genotype-phenotype correlation studies. HORDE allows a unique opportunity for discerning protein structural and functional information of the individual OR proteins. By applying novel data analysis strategies to the >3000 OR genes of mouse, dog and human within HORDE, we have generated a set of refined rhodopsin-based homology models for ORs. For model improvement, we employed a novel analysis of specific positions along the seven transmembrane helices at which prolines generate helix-breaking kinks. The model shows family-specific structural features, including idiosyncratic kink patterns, which lead to significant differences in the inferred odorant binding site structure. Such analyses form a basis for a comprehensive sequence-based classification of OR proteins in terms of potential odorant binding specificities.

/pdf/the-olfactory-receptor-universe-from-whole-genome-analysis-3eg5toxzjw.pdf

The olfactory receptor universe--from whole genome analysis to structure and evolution.

From subgenome analysis to protein structure.

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Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE

The olfactory receptor universe--from whole genome analysis to structure and evolution.

From subgenome analysis to protein structure.