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The UCSC Known Genes

Overview of attention for article published in Bioinformatics, February 2006
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user
patent
8 patents
facebook
1 Facebook page
q&a
1 Q&A thread

Citations

dimensions_citation
452 Dimensions

Readers on

mendeley
280 Mendeley
citeulike
12 CiteULike
connotea
4 Connotea
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Title
The UCSC Known Genes
Published in
Bioinformatics, February 2006
DOI 10.1093/bioinformatics/btl048
Pubmed ID
Authors

Fan Hsu, W. James Kent, Hiram Clawson, Robert M. Kuhn, Mark Diekhans, David Haussler

Abstract

The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 280 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 5%
Germany 4 1%
France 4 1%
United Kingdom 4 1%
Brazil 2 <1%
Australia 1 <1%
Italy 1 <1%
China 1 <1%
New Zealand 1 <1%
Other 2 <1%
Unknown 247 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 77 28%
Student > Ph. D. Student 71 25%
Student > Master 29 10%
Student > Bachelor 18 6%
Professor > Associate Professor 15 5%
Other 47 17%
Unknown 23 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 126 45%
Biochemistry, Genetics and Molecular Biology 68 24%
Computer Science 22 8%
Medicine and Dentistry 20 7%
Engineering 4 1%
Other 15 5%
Unknown 25 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 September 2023.
All research outputs
#2,525,389
of 25,374,917 outputs
Outputs from Bioinformatics
#1,860
of 12,809 outputs
Outputs of similar age
#5,436
of 91,225 outputs
Outputs of similar age from Bioinformatics
#3
of 62 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,809 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 91,225 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.