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An Atlas of annotations of Hydra vulgaris transcriptome

Overview of attention for article published in BMC Bioinformatics, September 2016
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3 tweeters

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Title
An Atlas of annotations of Hydra vulgaris transcriptome
Published in
BMC Bioinformatics, September 2016
DOI 10.1186/s12859-016-1172-9
Pubmed ID
Authors

Daniela Evangelista, Kumar Parijat Tripathi, Mario Rosario Guarracino

Abstract

RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable. Starting from a previous work, Transcriptator, we present the Atlas of Hydra's vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism. Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments. WEB RESOURCE URL: http://www-labgtp.na.icar.cnr.it/Atlas .

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 38%
Student > Bachelor 4 19%
Professor > Associate Professor 2 10%
Professor 2 10%
Researcher 2 10%
Other 2 10%
Unknown 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 29%
Agricultural and Biological Sciences 5 24%
Computer Science 3 14%
Engineering 2 10%
Neuroscience 2 10%
Other 1 5%
Unknown 2 10%

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 12 February 2017.
All research outputs
#9,480,198
of 12,378,687 outputs
Outputs from BMC Bioinformatics
#3,561
of 4,543 outputs
Outputs of similar age
#172,972
of 266,784 outputs
Outputs of similar age from BMC Bioinformatics
#92
of 127 outputs
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We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.