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A straightforward method to compute average stochastic oscillations from data samples

Overview of attention for article published in BMC Bioinformatics, October 2015
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  • Above-average Attention Score compared to outputs of the same age (59th percentile)
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16 Mendeley
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Title
A straightforward method to compute average stochastic oscillations from data samples
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/s12859-015-0765-z
Pubmed ID
Authors

Jorge Júlvez

Abstract

Many biological systems exhibit sustained stochastic oscillations in their steady state. Assessing these oscillations is usually a challenging task due to the potential variability of the amplitude and frequency of the oscillations over time. As a result of this variability, when several stochastic replications are averaged, the oscillations are flattened and can be overlooked. This can easily lead to the erroneous conclusion that the system reaches a constant steady state. This paper proposes a straightforward method to detect and asses stochastic oscillations. The basis of the method is in the use of polar coordinates for systems with two species, and cylindrical coordinates for systems with more than two species. By slightly modifying these coordinate systems, it is possible to compute the total angular distance run by the system and the average Euclidean distance to a reference point. This allows us to compute confidence intervals, both for the average angular speed and for the distance to a reference point, from a set of replications. The use of polar (or cylindrical) coordinates provides a new perspective of the system dynamics. The mean trajectory that can be obtained by averaging the usual cartesian coordinates of the samples informs about the trajectory of the center of mass of the replications. In contrast to such a mean cartesian trajectory, the mean polar trajectory can be used to compute the average circular motion of those replications, and therefore, can yield evidence about sustained steady state oscillations. Both, the coordinate transformation and the computation of confidence intervals, can be carried out efficiently. This results in an efficient method to evaluate stochastic oscillations.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 13%
Unknown 14 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 31%
Researcher 4 25%
Other 1 6%
Student > Master 1 6%
Student > Bachelor 1 6%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 25%
Mathematics 2 13%
Environmental Science 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Chemical Engineering 1 6%
Other 3 19%
Unknown 4 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 October 2015.
All research outputs
#2,399,484
of 6,496,325 outputs
Outputs from BMC Bioinformatics
#1,696
of 3,157 outputs
Outputs of similar age
#80,556
of 207,786 outputs
Outputs of similar age from BMC Bioinformatics
#73
of 133 outputs
Altmetric has tracked 6,496,325 research outputs across all sources so far. This one has received more attention than most of these and is in the 61st percentile.
So far Altmetric has tracked 3,157 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 43rd percentile – i.e., 43% 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 207,786 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 59% of its contemporaries.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.