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BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells

Overview of attention for article published in Genome Biology, September 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

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13 X users

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Title
BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells
Published in
Genome Biology, September 2017
DOI 10.1186/s13059-017-1297-9
Pubmed ID
Authors

Mariana Gómez-Schiavon, Liang-Fu Chen, Anne E. West, Nicolas E. Buchler

Abstract

Single-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled resolution in the measurement of the abundance and localization of nascent and mature RNA transcripts in fixed, single cells. We developed a computational pipeline (BayFish) to infer the kinetic parameters of gene expression from smFISH data at multiple time points after gene induction. Given an underlying model of gene expression, BayFish uses a Monte Carlo method to estimate the Bayesian posterior probability of the model parameters and quantify the parameter uncertainty given the observed smFISH data. We tested BayFish on synthetic data and smFISH measurements of the neuronal activity-inducible gene Npas4 in primary neurons.

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X Demographics

The data shown below were collected from the profiles of 13 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 33%
Researcher 20 24%
Student > Bachelor 7 9%
Student > Postgraduate 6 7%
Student > Master 4 5%
Other 10 12%
Unknown 8 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 34%
Agricultural and Biological Sciences 21 26%
Medicine and Dentistry 5 6%
Engineering 5 6%
Physics and Astronomy 4 5%
Other 10 12%
Unknown 9 11%
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 05 October 2018.
All research outputs
#4,789,904
of 25,382,440 outputs
Outputs from Genome Biology
#2,782
of 4,468 outputs
Outputs of similar age
#76,759
of 323,619 outputs
Outputs of similar age from Genome Biology
#49
of 55 outputs
Altmetric has tracked 25,382,440 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 4,468 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 37th percentile – i.e., 37% 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 323,619 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 76% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.