RactIP protocols

View RactIP computational protocol

RactIP statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left RNA-RNA interaction prediction chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

RactIP specifications

Information


Unique identifier OMICS_09342
Name RactIP
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Two RNA sequences (FASTA format or only a sequence in 5'–3' direction)
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


Add your version

Maintainer


  • person_outline Yuki Kato <>

Information


Unique identifier OMICS_09342
Name RactIP
Interface Web user interface
Restrictions to use None
Input data Two RNA sequences (FASTA format or only a sequence in 5'–3' direction)
Programming languages C++
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline Yuki Kato <>

Publication for RactIP

RactIP in pipeline

2017
PMCID: 5465533
PMID: 28595592
DOI: 10.1186/s13062-017-0183-4

[…] bioconductor []., we previously developed a series of computational pipelines including various computational tools for sequence analysis, such as raccess [], tantan [], last [, ], intarna [], and ractip [], for predicting human lncrna-rna interactions []. furthermore, all predicted human lncrna-rna interactions are available from our database (http://rtools.cbrc.jp/cgi-bin/rnarna/index.pl). […]


To access a full list of citations, you will need to upgrade to our premium service.

RactIP in publications

 (6)
PMCID: 5465533
PMID: 28595592
DOI: 10.1186/s13062-017-0183-4

[…] bioconductor []., we previously developed a series of computational pipelines including various computational tools for sequence analysis, such as raccess [], tantan [], last [, ], intarna [], and ractip [], for predicting human lncrna-rna interactions []. furthermore, all predicted human lncrna-rna interactions are available from our database (http://rtools.cbrc.jp/cgi-bin/rnarna/index.pl). […]

PMCID: 5408919
PMID: 27993777
DOI: 10.1093/bioinformatics/btw728

[…] (internal structure), neglects intramolecular structure or measures the accessibility of the binding region. there are also other machine learning algorithms (; ), and probabilistic approaches like ractip (), which uses the contrafold model () for rna interaction prediction., risearch (), bindigo () and guugle () are examples of alignment-like methods. the risearch algorithm was mainly […]

PMCID: 4895283
PMID: 26818453
DOI: 10.1186/s12864-015-2307-5

[…] by their binding energy in step 5. finally, in step 6 the joint secondary structures of the interaction site with the minimum interaction energy in each pair of rna sequences is predicted using ractip []. fig. 1, first, each rna sequence is screened to find its inaccessible regions and its tandem repeats, which allows us to extract candidate subsequences to form inter-molecule interactions. […]

PMCID: 4838349
PMID: 26673718
DOI: 10.1093/nar/gkv1477

[…] the removal of restrictions often comes at the great expense of runtime performance, so these tools are typically restricted to relatively short input sequences. in this class, we have the program ractip (), made tractable for use on longer sequences by utilizing the technique of integer programming to optimize for runtime performance., in addition to falling into one of the four categories, […]

PMCID: 4122056
PMID: 25114714
DOI: 10.1186/1748-7188-9-17

[…] number of bonds. a statistical sampling algorithm was introduced in [] based on some modifications to the grammars. it calculates the interaction probabilities for any given single region on rna. ractip [] predicts rna-rna interaction using integer programming. accordingly, it uses the approximate information of the internal and external base pairing probabilities of joint structures […]


To access a full list of publications, you will need to upgrade to our premium service.

RactIP institution(s)
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan; Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, Japan; Mizuho Information & Research Institute, Inc, Chiyoda-ku, Tokyo, Japan; Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi, Koto-ku, Tokyo, Japan; Department of Mathematical Sciences, Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto, Japan

RactIP reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review RactIP