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Citations per year

Number of citations per year for the bioinformatics software tool Rfold
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This map represents all the scientific publications referring to Rfold per scientific context
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Rfold specifications

Information


Unique identifier OMICS_15807
Name Rfold
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++
Computer skills Advanced
Stability Stable
Source code URL https://www.ncrna.org/download/365/
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Hisanori Kiryu

Publication for Rfold

Rfold citations

 (8)
library_books

TurboFold II: RNA structural alignment and secondary structure prediction informed by multiple homologs

2017
Nucleic Acids Res
PMCID: 5714223
PMID: 29036420
DOI: 10.1093/nar/gkx815

[…] .1.9) (), a method that reads aligned RNA sequences and computes minimum free energy conserved structures as allowed by the input alignment; MXSCARNA (2.1) (), which predicts a consensus structure by Rfold and input from ClustalW (2.1) (); and TurboFold (). MaxExpect (,), a single sequence structure prediction method, is used as a control calculation because it also predicts structure with the max […]

library_books

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures

2016
Evol Bioinform Online
PMCID: 5140013
PMID: 27980384
DOI: 10.4137/EBO.S40912

[…] rule states that 1/5 of the total mutations in every t iterations φ(t) should be successful mutations. According to the number of successes φ(t), the value of RF is adjusted according to RFnew(it+1)={RFold(t)*0.85ifφ(t)<1/5RFold(t)/0.85ifφ(t)>1/5RFold(t)ifφ(t)=1/5(13)The pseudocode is briefly described in . […]

library_books

The rules and impact of nonsense mediated mRNA decay in human cancers

2016
Nat Genet
PMCID: 5045715
PMID: 27618451
DOI: 10.1038/ng.3664

[…] in ‘phyloP46way’ downloaded from the UCSC Genome Browser website was used to create the sequence conservation features. A basewise probability score for the mRNA secondary structure was computed with Rfold 0.1-2. Optimal codon usage was used as a proxy for the translation efficiency and was computed by dividing the amount of optimal in-frame codons over the codon count. Optimal codons were defined […]

library_books

Identification and Characterization of MicroRNAs in Small Brown Planthopper (Laodephax striatellus) by Next Generation Sequencing

2014
PLoS One
PMCID: 4109989
PMID: 25057821
DOI: 10.1371/journal.pone.0103041

[…] nt downstream of the miRNA and the sequences 100 nt upstream and 20 nt downstream of the miRNA were extracted to predict the RNA secondary structure, and folded stem-loop structures were detected by Rfold (http://www.tbi.univie.ac.at/~ivo/RNA/RNAfold.html) and analyzed by Mireap (http://sourceforge.net/projects/mireap/) under the default settings. There are three characteristics in the structure […]

library_books

Bioinformatics of Cancer ncRNA in High Throughput Sequencing: Present State and Challenges

2012
Front Genet
PMCID: 3523245
PMID: 23251139
DOI: 10.3389/fgene.2012.00287

[…] ing a new or a known ncRNA.There are several folding algorithms to predict RNA secondary structure (Table ). Among the most well known are the ViennaRNA package (Lorenz et al., ), Mfold (Zuker, ) and Rfold (Kiryu et al., ). The ViennaRNA package uses thermodynamic parameters and dynamic programming to predict the secondary structure. It also provides information about centroid and maximum expected […]

library_books

Molecular Characterization of Chronic Lymphocytic Leukemia Patients with a High Number of Losses in 13q14

2012
PLoS One
PMCID: 3496725
PMID: 23152777
DOI: 10.1371/journal.pone.0048485

[…] The analysis of miRNA expression in 13q-H and 13q-L CLL patients revealed that fifteen miRNAs were deregulated in 13q-H CLL patients: hsa-miR-155 was the most highly upregulated miRNA (Rfold = 3.70), while hsa-miR-223 was the most significantly downregulated (Rfold = 0.10). Four of the deregulated miRNAs (miR-15a, miR-29a, miR-155 and miR- 223) were further assayed by quantitative R […]


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Rfold institution(s)
Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan; Department of Computational Biology, Faculty of Frontier Science, The University of Tokyo, Kashiwa, Chiba, Japan
Rfold funding source(s)
This work was partially supported by the ‘Functional RNA Project’ funded by the New Energy and Industrial Technology Development Organization (NEDO) of Japan.

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