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ShrimpGPAT: a gene and protein annotation tool for knowledge sharing and gene discovery in shrimp

Overview of attention for article published in BMC Genomics, June 2014
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Title
ShrimpGPAT: a gene and protein annotation tool for knowledge sharing and gene discovery in shrimp
Published in
BMC Genomics, June 2014
DOI 10.1186/1471-2164-15-506
Pubmed ID
Authors

Parpakron Korshkari, Sirintra Vaiwsri, Timothy W Flegel, Sudsanguan Ngamsuriyaroj, Burachai Sonthayanon, Anuphap Prachumwat

Abstract

Although captured and cultivated marine shrimp constitute highly important seafood in terms of both economic value and production quantity, biologists have little knowledge of the shrimp genome and this partly hinders their ability to improve shrimp aquaculture. To help improve this situation, the Shrimp Gene and Protein Annotation Tool (ShrimpGPAT) was conceived as a community-based annotation platform for the acquisition and updating of full-length complementary DNAs (cDNAs), Expressed Sequence Tags (ESTs), transcript contigs and protein sequences of penaeid shrimp and their decapod relatives and for in-silico functional annotation and sequence analysis.Description: ShrimpGPAT currently holds quality-filtered, molecular sequences of 14 decapod species (~500,000 records for six penaeid shrimp and eight other decapods). The database predominantly comprises transcript sequences derived by both traditional EST Sanger sequencing and more recently by massive-parallel sequencing technologies. The analysis pipeline provides putative functions in terms of sequence homologs, gene ontologies and protein-protein interactions. Data retrieval can be conducted easily either by a keyword text search or by a sequence query via BLAST, and users can save records of interest for later investigation using tools such as multiple sequence alignment and BLAST searches against pre-defined databases. In addition, ShrimpGPAT provides space for community insights by allowing functional annotation with tags and comments on sequences. Community-contributed information will allow for continuous database enrichment, for improvement of functions and for other aspects of sequence analysis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 17%
Student > Master 6 17%
Student > Bachelor 4 11%
Student > Ph. D. Student 3 9%
Professor > Associate Professor 2 6%
Other 7 20%
Unknown 7 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 26%
Computer Science 6 17%
Biochemistry, Genetics and Molecular Biology 5 14%
Business, Management and Accounting 2 6%
Environmental Science 1 3%
Other 3 9%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 June 2014.
All research outputs
#20,231,820
of 22,757,541 outputs
Outputs from BMC Genomics
#9,263
of 10,637 outputs
Outputs of similar age
#192,912
of 228,422 outputs
Outputs of similar age from BMC Genomics
#162
of 199 outputs
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We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.