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A simple, practical and complete O -time Algorithm for RNA folding using the Four-Russians Speedup

Overview of attention for article published in Algorithms for Molecular Biology, January 2010
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Title
A simple, practical and complete O -time Algorithm for RNA folding using the Four-Russians Speedup
Published in
Algorithms for Molecular Biology, January 2010
DOI 10.1186/1748-7188-5-13
Pubmed ID
Authors

Yelena Frid, Dan Gusfield

Abstract

The problem of computationally predicting the secondary structure (or folding) of RNA molecules was first introduced more than thirty years ago and yet continues to be an area of active research and development. The basic RNA-folding problem of finding a maximum cardinality, non-crossing, matching of complimentary nucleotides in an RNA sequence of length n, has an O(n3)-time dynamic programming solution that is widely applied. It is known that an o(n3) worst-case time solution is possible, but the published and suggested methods are complex and have not been established to be practical. Significant practical improvements to the original dynamic programming method have been introduced, but they retain the O(n3) worst-case time bound when n is the only problem-parameter used in the bound. Surprisingly, the most widely-used, general technique to achieve a worst-case (and often practical) speed up of dynamic programming, the Four-Russians technique, has not been previously applied to the RNA-folding problem. This is perhaps due to technical issues in adapting the technique to RNA-folding.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 17%
Brazil 2 17%
Italy 1 8%
Russia 1 8%
Unknown 6 50%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 50%
Professor 3 25%
Researcher 2 17%
Professor > Associate Professor 2 17%
Student > Master 1 8%
Other 2 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 50%
Computer Science 6 50%
Biochemistry, Genetics and Molecular Biology 1 8%
Business, Management and Accounting 1 8%
Mathematics 1 8%
Other 1 8%

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 25 July 2012.
All research outputs
#9,954,201
of 12,434,464 outputs
Outputs from Algorithms for Molecular Biology
#120
of 181 outputs
Outputs of similar age
#85,889
of 120,416 outputs
Outputs of similar age from Algorithms for Molecular Biology
#1
of 4 outputs
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So far Altmetric has tracked 181 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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