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Systematic review of next-generation sequencing simulators: computational tools, features and perspectives

Overview of attention for article published in Briefings in Functional Genomics, April 2016
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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6 X users

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113 Mendeley
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1 CiteULike
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Article details
Title
Systematic review of next-generation sequencing simulators: computational tools, features and perspectives
Published in
Briefings in Functional Genomics, April 2016
DOI 10.1093/bfgp/elw012
Pubmed ID
Authors

Min Zhao, Di Liu, Hong Qu

Abstract

High-throughput next-generation sequencing (NGS) technologies have rapidly generated a large volume of genomic data. To aid the development and evaluation of new statistical models and computational methods, NGS-based simulators have been proposed to construct better experimental workflows. However, the comparative performance of these NGS simulators remains unclear. In this review, we conducted a comprehensive investigation of NGS simulators for various sequencing techniques, including DNA sequencing, metagenomic sequencing, RNA-seq, ChIP-seq and bisulfite sequencing for methylation.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

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.
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Geographical breakdown

Geographical breakdown
Country Count As %
Brazil 2 2%
United States 1 <1%
Turkey 1 <1%
United Kingdom 1 <1%
France 1 <1%
Spain 1 <1%
Unknown 106 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 31 27%
Student > Ph. D. Student 24 21%
Student > Master 12 11%
Student > Doctoral Student 9 8%
Student > Bachelor 8 7%
Other 15 13%
Unknown 14 12%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 36 32%
Biochemistry, Genetics and Molecular Biology 27 24%
Computer Science 12 11%
Medicine and Dentistry 5 4%
Engineering 4 4%
Other 12 11%
Unknown 17 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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
#9,219,214
of 28,008,529 outputs
Outputs from Briefings in Functional Genomics
#232
of 622 outputs
Outputs of similar age
#113,033
of 318,364 outputs
Outputs of similar age from Briefings in Functional Genomics
#5
of 14 outputs
Altmetric has tracked 28,008,529 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 622 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 62% 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 318,364 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 64% of its contemporaries.
We're also able to compare this research output to 14 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 64% of its contemporaries.