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The aquatic animals’ transcriptome resource for comparative functional analysis

Overview of attention for article published in BMC Genomics, May 2018
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Title
The aquatic animals’ transcriptome resource for comparative functional analysis
Published in
BMC Genomics, May 2018
DOI 10.1186/s12864-018-4463-x
Pubmed ID
Authors

Chih-Hung Chou, Hsi-Yuan Huang, Wei-Chih Huang, Sheng-Da Hsu, Chung-Der Hsiao, Chia-Yu Liu, Yu-Hung Chen, Yu-Chen Liu, Wei-Yun Huang, Meng-Lin Lee, Yi-Chang Chen, Hsien-Da Huang

Abstract

Aquatic animals have great economic and ecological importance. Among them, non-model organisms have been studied regarding eco-toxicity, stress biology, and environmental adaptation. Due to recent advances in next-generation sequencing techniques, large amounts of RNA-seq data for aquatic animals are publicly available. However, currently there is no comprehensive resource exist for the analysis, unification, and integration of these datasets. This study utilizes computational approaches to build a new resource of transcriptomic maps for aquatic animals. This aquatic animal transcriptome map database dbATM provides de novo assembly of transcriptome, gene annotation and comparative analysis of more than twenty aquatic organisms without draft genome. To improve the assembly quality, three computational tools (Trinity, Oases and SOAPdenovo-Trans) were employed to enhance individual transcriptome assembly, and CAP3 and CD-HIT-EST software were then used to merge these three assembled transcriptomes. In addition, functional annotation analysis provides valuable clues to gene characteristics, including full-length transcript coding regions, conserved domains, gene ontology and KEGG pathways. Furthermore, all aquatic animal genes are essential for comparative genomics tasks such as constructing homologous gene groups and blast databases and phylogenetic analysis. In conclusion, we establish a resource for non model organism aquatic animals, which is great economic and ecological importance and provide transcriptomic information including functional annotation and comparative transcriptome analysis. The database is now publically accessible through the URL http://dbATM.mbc.nctu.edu.tw/ .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 27%
Researcher 7 27%
Other 3 12%
Student > Master 3 12%
Professor 1 4%
Other 3 12%
Unknown 2 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 31%
Agricultural and Biological Sciences 6 23%
Medicine and Dentistry 3 12%
Engineering 2 8%
Unspecified 1 4%
Other 4 15%
Unknown 2 8%
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 17 May 2018.
All research outputs
#18,612,796
of 23,056,273 outputs
Outputs from BMC Genomics
#8,231
of 10,702 outputs
Outputs of similar age
#253,698
of 327,414 outputs
Outputs of similar age from BMC Genomics
#183
of 250 outputs
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