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Efficient assembly and annotation of the transcriptome of catfish by RNA-Seq analysis of a doubled haploid homozygote

Overview of attention for article published in BMC Genomics, November 2012
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Title
Efficient assembly and annotation of the transcriptome of catfish by RNA-Seq analysis of a doubled haploid homozygote
Published in
BMC Genomics, November 2012
DOI 10.1186/1471-2164-13-595
Pubmed ID
Authors

Shikai Liu, Yu Zhang, Zunchun Zhou, Geoff Waldbieser, Fanyue Sun, Jianguo Lu, Jiaren Zhang, Yanliang Jiang, Hao Zhang, Xiuli Wang, KV Rajendran, Lester Khoo, Huseyin Kucuktas, Eric Peatman, Zhanjiang Liu

Abstract

Upon the completion of whole genome sequencing, thorough genome annotation that associates genome sequences with biological meanings is essential. Genome annotation depends on the availability of transcript information as well as orthology information. In teleost fish, genome annotation is seriously hindered by genome duplication. Because of gene duplications, one cannot establish orthologies simply by homology comparisons. Rather intense phylogenetic analysis or structural analysis of orthologies is required for the identification of genes. To conduct phylogenetic analysis and orthology analysis, full-length transcripts are essential. Generation of large numbers of full-length transcripts using traditional transcript sequencing is very difficult and extremely costly.

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 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Australia 2 2%
India 2 2%
Chile 1 <1%
Brazil 1 <1%
Italy 1 <1%
Switzerland 1 <1%
Philippines 1 <1%
Unknown 100 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 26%
Student > Master 21 19%
Researcher 18 16%
Student > Doctoral Student 8 7%
Other 6 5%
Other 22 19%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 65%
Biochemistry, Genetics and Molecular Biology 19 17%
Environmental Science 2 2%
Medicine and Dentistry 2 2%
Computer Science 2 2%
Other 4 4%
Unknown 11 10%
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 05 November 2012.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from BMC Genomics
#9,840
of 11,244 outputs
Outputs of similar age
#178,562
of 199,440 outputs
Outputs of similar age from BMC Genomics
#185
of 201 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 199,440 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 201 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.