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ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data

Overview of attention for article published in BMC Bioinformatics, June 2017
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Title
ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data
Published in
BMC Bioinformatics, June 2017
DOI 10.1186/s12859-017-1695-8
Pubmed ID
Authors

Giorgos Minas, Hiroshi Momiji, Dafyd J. Jenkins, Maria J. Costa, David A. Rand, Bärbel Finkenstädt

Abstract

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 32%
Student > Ph. D. Student 7 28%
Student > Bachelor 3 12%
Student > Master 3 12%
Other 1 4%
Other 3 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 36%
Agricultural and Biological Sciences 3 12%
Medicine and Dentistry 3 12%
Computer Science 3 12%
Mathematics 2 8%
Other 2 8%
Unknown 3 12%
Attention Score in Context

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 27 June 2017.
All research outputs
#18,349,015
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#6,088
of 7,400 outputs
Outputs of similar age
#227,919
of 316,709 outputs
Outputs of similar age from BMC Bioinformatics
#83
of 117 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 117 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.