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RNA-MoIP specifications


Unique identifier OMICS_18500
Alternative name RNA Motifs over Integer Programming
Interface Web user interface
Restrictions to use None
Input data An RNA sequence or a set of RNA sequences.
Input format FASTA
Output data An image of the corrected secondary structure and location of inserted motifs are generated.
Computer skills Basic
Stability Stable
Maintained Yes



  • person_outline Jerome Waldispuhl

Publication for RNA Motifs over Integer Programming

RNA-MoIP citations


Capturing RNA Folding Free Energy with Coarse Grained Molecular Dynamics Simulations

Sci Rep
PMCID: 5385882
PMID: 28393861
DOI: 10.1038/srep45812

[…] late based modeling uses predefined, small motifs to assemble RNA structures from their sequence. Template based models include the MC-Fold/MC-Sym pipeline, BARNACLE, RSIM, 3dRNA, RNAComposer, Vfold, RNA-MoIP and FARNA/FARFAR available in the Rosetta package. Similar to template based modeling, ASSEMBLE and RNA2D3D use homologous RNA structures to predict the new RNA structure (with manual refinem […]


Binding Site Identification and Flexible Docking of Single Stranded RNA to Proteins Using a Fragment Based Approach

PLoS Comput Biol
PMCID: 4729675
PMID: 26815409
DOI: 10.1371/journal.pcbi.1004697
call_split See protocol

[…] taining just over 2,700 ribonucleotides from the large ribosomal subunit from Haloarcula marismortui [1FFK]” [], which is mainly double-stranded. The libraries used by MC-Fold/MC-Sym [] ModeRNA [] or RNA-MoIP [] represent only fragments that are partially or fully double-stranded fragments (“Nucleotide Cyclic Motifs”) [] or internal loops (which limit the backbone conformations sampling by a loop […]


RNA 3D Modules in Genome Wide Predictions of RNA 2D Structure

PLoS One
PMCID: 4624896
PMID: 26509713
DOI: 10.1371/journal.pone.0139900

[…] ly time-consuming and limited to small molecules. Laing and Schlick reviewed these where they explore new ideas towards 3D structure prediction []. Reinharz et al. [] developed an automated pipeline, RNA-MoIP, for combining 2D and 3D information to refine tertiary predictions. In a first step, they use a classical secondary structure predictor to get a set of sub-optimal structures. In a second st […]


Modeling the Structure of RNA Molecules with Small Angle X Ray Scattering Data

PLoS One
PMCID: 3817170
PMID: 24223750
DOI: 10.1371/journal.pone.0078007
call_split See protocol

[…] quence and secondary structure. Of these, MC-SYM uses least-squares minimization of cyclic motif networks, ASSEMBLE allows for hand-picking of the most appropriate motifs using human knowledge, and RNA-MoIP uses an integer programming framework in order to scale to larger RNA molecules.There have also been several attempts to develop conventional sequential fragment assembly, which works by cop […]


Automated identification of RNA 3D modules with discriminative power in RNA structural alignments

Nucleic Acids Res
PMCID: 3905863
PMID: 24005040
DOI: 10.1093/nar/gkt795

[…] putationally less costly secondary structure prediction. For example, () enhances the 3D structure prediction of large RNAs by inserting 3D modules into the secondary structure. Their program, called RNA-MoIP, uses an integer programming framework to remove canonical base pairs from secondary structures to make room for 3D modules (e.g. k-way junctions), which serve as a template for creating a 3D […]


Towards 3D structure prediction of large RNA molecules: an integer programming framework to insert local 3D motifs in RNA secondary structure

PMCID: 3371858
PMID: 22689763
DOI: 10.1093/bioinformatics/bts226
call_split See protocol

[…] t ω be a RNA sequence. First, we use a classical secondary structure predictor (e.g. RNAsubopt) to generate a list of sub-optimal secondary structures. Second, for each structure from the list we use RNA-MoIP to insert RNA 3D motifs in the structure using the sequence information provided by ω. RNA-MoIP works in two steps: Given a database of sequences of RNA 3D motifs (cf. ), the preprocessing st […]


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RNA-MoIP institution(s)
School of Computer Science, McGill University, Montreal, QC, Canada; Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel; Institute for Research in Immunology and Cancer and Department of Computer Science and Operations Research, Université de Montreal, Montreal, QC, Canada
RNA-MoIP funding source(s)
Supported by Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN 2015-03786 & RGPAS 477873- 15]; Canadian Institutes of Health Research (CHIR) [CIHR BOP-149429]; Genome Canada [B/CB 2015]; Natural Sciences and Engineering Research Council of Canada USRA and Fonds de recherche du Quebec, Nature et technologies BRPC fellowships; Azrieli and Fonds de recherche du Quebec Nature et technologies postdoctoral fellowships; Canadian Institutes of Health Research (CIHR) [MT-14604]; National Institutes of Health (NIH) [R01GM088813]; and Natural Sciences and Engineering Research Council of Canada (NSERC) [170165-01].

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