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BioMed Research International
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2017
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Article
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Tab 3
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Review Article
A Review on Recent Computational Methods for Predicting Noncoding RNAs
Table 3
De novo ncRNA prediction methods using RNA structure features.
Name
URL
Feature
Prediction algorithm
RNAfold [
33
]
Base-pair probabilities and MFE
Partition function and dynamic programming
Mfold [
34
]
http://unafold.rna.albany.edu/?q=mfold
MFE
Dynamic programming
Afold [
35
]
ftp://ftp.ncbi.nlm.nih.gov/pub/ogurtsov/Afold
Sets of conditionally optimal multibranch loop free structures
Dynamic programming
Sfold [
41
]
http://sfold.wadsworth.org/cgi-bin/index.pl
Internal loops, sets of conditionally optimal MLF structures
Nearest-neighbour model (NNM)
Nussinov [
42
]
http://www.pnas.org/content/77/11/6309
Individual base pairs and loop structure with the lowest free energy
Dynamic programming
Partition function method [
43
]
http://www.ncbi.nlm.nih.gov/pubmed/1695107
Full equilibrium partition for secondary structure and the probabilities of various substructures
Dynamic programming
Zhang [
44
]
http://www.ncbi.nlm.nih.gov/pubmed/16395542/
MFE and GC content
Dynamic programming
ptRNApred [
45
]
http://www.ptrnapred.org/
91 features including (1) 7 selected dinucleotide properties as well as their dinucleotide values, (2) 52 properties derived from the secondary structure, for example, the number of loops, and (3) 32 triplet element properties
Random forest and SVM
incRNA [
46
]
http://incrna.gersteinlab.org/
9 genomic features including 4 expression features, 3 sequence information, and 2 RNA structure features
Random forest