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RNAdualPF: software to compute the dual partition function with sample applications in molecular evolution theory

Overview of attention for article published in BMC Bioinformatics, October 2016
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Title
RNAdualPF: software to compute the dual partition function with sample applications in molecular evolution theory
Published in
BMC Bioinformatics, October 2016
DOI 10.1186/s12859-016-1280-6
Pubmed ID
Authors

Juan Antonio Garcia-Martin, Amir H. Bayegan, Ivan Dotu, Peter Clote

Abstract

RNA inverse folding is the problem of finding one or more sequences that fold into a user-specified target structure s 0, i.e. whose minimum free energy secondary structure is identical to the target s 0. Here we consider the ensemble of all RNA sequences that have low free energy with respect to a given target s 0. We introduce the program RNAdualPF, which computes the dual partition function Z (∗), defined as the sum of Boltzmann factors exp(-E(a,s 0)/RT) of all RNA nucleotide sequences a compatible with target structure s 0. Using RNAdualPF, we efficiently sample RNA sequences that approximately fold into s 0, where additionally the user can specify IUPAC sequence constraints at certain positions, and whether to include dangles (energy terms for stacked, single-stranded nucleotides). Moreover, since we also compute the dual partition function Z (∗)(k) over all sequences having GC-content k, the user can require that all sampled sequences have a precise, specified GC-content. Using Z (∗), we compute the dual expected energy 〈E (∗)〉, and use it to show that natural RNAs from the Rfam 12.0 database have higher minimum free energy than expected, thus suggesting that functional RNAs are under evolutionary pressure to be only marginally thermodynamically stable. We show that C. elegans precursor microRNA (pre-miRNA) is significantly non-robust with respect to mutations, by comparing the robustness of each wild type pre-miRNA sequence with 2000 [resp. 500] sequences of the same GC-content generated by RNAdualPF, which approximately [resp. exactly] fold into the wild type target structure. We confirm and strengthen earlier findings that precursor microRNAs and bacterial small noncoding RNAs display plasticity, a measure of structural diversity. We describe RNAdualPF, which rapidly computes the dual partition function Z (∗) and samples sequences having low energy with respect to a target structure, allowing sequence constraints and specified GC-content. Using different inverse folding software, another group had earlier shown that pre-miRNA is mutationally robust, even controlling for compositional bias. Our opposite conclusion suggests a cautionary note that computationally based insights into molecular evolution may heavily depend on the software used. C/C++-software for RNAdualPF is available at http://bioinformatics.bc.edu/clotelab/RNAdualPF .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 8%
Unknown 12 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 31%
Student > Master 2 15%
Professor 1 8%
Student > Doctoral Student 1 8%
Researcher 1 8%
Other 0 0%
Unknown 4 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 31%
Computer Science 2 15%
Nursing and Health Professions 1 8%
Agricultural and Biological Sciences 1 8%
Neuroscience 1 8%
Other 0 0%
Unknown 4 31%
Attention Score in Context

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 20 July 2017.
All research outputs
#13,482,115
of 22,896,955 outputs
Outputs from BMC Bioinformatics
#4,208
of 7,299 outputs
Outputs of similar age
#165,889
of 315,872 outputs
Outputs of similar age from BMC Bioinformatics
#57
of 119 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,299 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 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 315,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 119 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 51% of its contemporaries.