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Network analysis of gene essentiality in functional genomics experiments

Overview of attention for article published in Genome Biology, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

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17 X users

Citations

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49 Dimensions

Readers on

mendeley
184 Mendeley
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8 CiteULike
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Title
Network analysis of gene essentiality in functional genomics experiments
Published in
Genome Biology, November 2015
DOI 10.1186/s13059-015-0808-9
Pubmed ID
Authors

Peng Jiang, Hongfang Wang, Wei Li, Chongzhi Zang, Bo Li, Yinling J. Wong, Cliff Meyer, Jun S. Liu, Jon C. Aster, X. Shirley Liu

Abstract

Many genomic techniques have been developed to study gene essentiality genome-wide, such as CRISPR and shRNA screens. Our analyses of public CRISPR screens suggest protein interaction networks, when integrated with gene expression or histone marks, are highly predictive of gene essentiality. Meanwhile, the quality of CRISPR and shRNA screen results can be significantly enhanced through network neighbor information. We also found network neighbor information to be very informative on prioritizing ChIP-seq target genes and survival indicator genes from tumor profiling. Thus, our study provides a general method for gene essentiality analysis in functional genomic experiments ( http://nest.dfci.harvard.edu ).

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 3 2%
Chile 1 <1%
Netherlands 1 <1%
Brazil 1 <1%
Unknown 175 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 27%
Researcher 40 22%
Student > Master 18 10%
Student > Bachelor 15 8%
Student > Doctoral Student 10 5%
Other 32 17%
Unknown 19 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 36%
Biochemistry, Genetics and Molecular Biology 36 20%
Computer Science 18 10%
Medicine and Dentistry 18 10%
Engineering 8 4%
Other 12 7%
Unknown 26 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 16 January 2016.
All research outputs
#4,659,159
of 25,373,627 outputs
Outputs from Genome Biology
#2,751
of 4,467 outputs
Outputs of similar age
#59,286
of 297,292 outputs
Outputs of similar age from Genome Biology
#59
of 82 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 38th percentile – i.e., 38% 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 297,292 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.