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Oasis 2: improved online analysis of small RNA-seq data

Overview of attention for article published in BMC Bioinformatics, February 2018
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Oasis 2: improved online analysis of small RNA-seq data
Published in
BMC Bioinformatics, February 2018
DOI 10.1186/s12859-018-2047-z
Pubmed ID
Authors

Raza-Ur Rahman, Abhivyakti Gautam, Jörn Bethune, Abdul Sattar, Maksims Fiosins, Daniel Sumner Magruder, Vincenzo Capece, Orr Shomroni, Stefan Bonn

Abstract

Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing. Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment. Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users 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 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 92 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 21%
Student > Ph. D. Student 17 18%
Student > Bachelor 14 15%
Student > Postgraduate 7 8%
Student > Master 7 8%
Other 11 12%
Unknown 17 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 28%
Agricultural and Biological Sciences 19 21%
Computer Science 9 10%
Engineering 6 7%
Neuroscience 3 3%
Other 10 11%
Unknown 19 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 01 March 2018.
All research outputs
#6,382,210
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#2,424
of 7,387 outputs
Outputs of similar age
#132,877
of 447,995 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 94 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 67% 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 447,995 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.