The UCSC Genome Browser Database: 2008 update
By Matthew L. Speir, Ann S. Zweig, Kate R. Rosenbloom, Brian J. Raney, Benedict Paten, Parisa Nejad, Brian T. Lee, Katrina Learned, Donna Karolchik, A. Hinrichs and 13 more. Nucleic Acids Res., 2007
560 citations recorded by the source corpus.
The University of California, Santa Cruz, Genome Browser Database (GBD) provides integrated sequence and annotation data for a large collection of vertebrate and model organism genomes. Seventeen new assemblies have been added to the database in the past year, for a total coverage of 19 vertebrate and 21 invertebrate species as of September 2007. For each assembly, the GBD contains a collection of annotation data aligned to the genomic sequence. Highlights of this year's additions include a 28-species human-based vertebrate conservation annotation, an enhanced UCSC Genes set, and more human variation, MGC, and ENCODE data. The database is optimized for fast interactive performance with a set of web-based tools that may be used to view, manipulate, filter and download the annotation data. New toolset features include the Genome Graphs tool for displaying genome-wide data sets, session saving and sharing, better custom track management, expanded Genome Browser configuration options and a Genome Browser wiki site. The downloadable GBD data, the companion Genome Browser toolset and links to documentation and related information can be found at: http://genome.ucsc.edu/.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/cd3feb81b88f200d9f36852c9df9692b59611365
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Citations in the corpus
- Ensembl 2009 (2008, methodology): “In comparison to similar projects based at the University of California Santa Cruz (1) and the National Center for Biotechnology Information (2), some of the distinguishing characteristics of the Ensembl project are:”
- Most mammalian mRNAs are conserved targets of microRNAs. (2008, background): “Because mutation, gene conversion, and crossover rates vary throughout the genome (Wolfe et al. 1989; Hwang and Green 2004; Kauppi et al. 2004), different UTRs have substantially different background conservation levels.”
- Distinguishing protein-coding and noncoding genes in the human genome (2007, background): “The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers.”
- Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network (2011, unknown): “Coding exon sequence alignment data for 30 species including the mouse were downloaded from the UCSC genome browser (build 9mm, http://hgdownload.cse.ucsc.edu/goldenPath/mm9/ multiz30way/) (24).”
- The UCSC Genome Browser database: update 2011 (2010, methodology): “Users can upload and view their data in the context of the other browser tracks using the custom tracks tool (8).”
- The UCSC Genome Browser database: 2017 update (2016, methodology): “One widely used feature of the browser is the ‘Sessions’ tool, which allows the user to save the configuration settings of the current browser view for later viewing and sharing (40).”
- The CGView Server: a comparative genomics tool for circular genomes (2008, background): “For many fully sequenced genomes, web-based genome browsers offer graphical maps that are integrated with underlying databases of sequences, annotations and analyses (2–5).”
- Global analysis of the insulator binding protein CTCF in chromatin barrier regions reveals demarcation of active and repressive domains. (2008, methodology): “Genome-wide distribution of binding sites Genome-wide distribution of CTCF-binding sites and barrier CTCF sites was determined with reference to RefSeq genes downloaded from UCSC genome browser (Karolchik et al. 2008).”
- The UCSC Genome Browser database: 2014 update (2013, background): “…offers extensive conservation and evolutionary comparisons, a large collection of gene models including the locally generated UCSC Genes track (6,7), regulation, expression, epigenetics and tissue differentiation, variation, phenotype and disease association data, and data that have been…”
- Discovery and characterization of chromatin states for systematic annotation of the human genome (2010, methodology): “as of December 14, 2008 obtained from the UCSC genome browser browse”
- A Methodological Framework for the Reconstruction of Contiguous Regions of Ancestral Genomes and Its Application to Mammalian Genomes (2008, methodology): “N We first downloaded the chained and netted pairwise alignments from the UCSC Genome Bioinformatics site [32] and the coordinates of all the alignments of the human genome (build hg18, March 2006 [60]) against respectively macaca (build rheMac2, January 2006 [61]), mouse (build mm9, July 2007 [62])”
- GtRNAdb: a database of transfer RNA genes detected in genomic sequence (2008, methodology): “If the eukaryotic or microbial genomes are available in external genome browsers (5,6), users can follow the provided links to study each tRNA within the context of neighboring genes.”
- Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data (2008, methodology): “Genome-wide distribution of identified binding sites was determined with reference to RefSeq genes downloaded from UCSC genome browser (20).”
- The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes. (2009, unknown): “The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers.”
- CpG islands – ‘A rough guide’ (2009, unknown): “Y Total CGIs = 28 226 [89]”
- The UCSC Genome Browser database: extensions and updates 2011 (2011, methodology): “For human and mouse assemblies, we also offer a locally generated UCSC Genes track based upon RefSeq, GenBank, CCDS and UniProt data (7,8).”