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Citations per year

Number of citations per year for the bioinformatics software tool RNAcompete

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This map represents all the scientific publications referring to RNAcompete per scientific context
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RNAcompete specifications


Unique identifier OMICS_18668
Name RNAcompete
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Timothy Hughes
  • person_outline Quaid Morris

Publication for RNAcompete

RNAcompete citations


Inferring RNA sequence preferences for poorly studied RNA binding proteins based on co evolution

BMC Bioinformatics
PMCID: 5848454
PMID: 29529991
DOI: 10.1186/s12859-018-2091-8

[…] lt, we got an average PCC = 0.417 which was much closer to DeepBind (no statistically significant difference) and RCK (still significantly stronger), with much less training time. When trained on one RNAcompete experiment (using set A only) on the same machine, KNN-RCK took < 1 hr (53min on average over a subset of 14 experiments); RCK took 3–4 hrs (220min on average), both with the hyper-paramete […]


Finding RNA structure in the unstructured RBPome

BMC Genomics
PMCID: 5819699
PMID: 29463232
DOI: 10.1186/s12864-018-4540-1
call_split See protocol

[…] We explored the overall statistic of structural binding preferences amongst the set of RNA-binding proteins in the RNAcompete dataset []. We used the set of learned models from the RCK website []. We identified for each protein the k-mer w and structural context a with the highest binding score. We calculated the […]


The combinatorial control of alternative splicing in C. elegans

PLoS Genet
PMCID: 5697891
PMID: 29121637
DOI: 10.1371/journal.pgen.1007033

[…] between direct and indirect splicing regulation–we consider that any AS event that is affected by a SF but that has no consensus binding site is indirectly affected by that SF. We previously used the RNAcompete method [,] to define the in vitro binding specificities of our SFs of interest. We were able to obtain 7-mer binding motifs for each SF, reproducing both known [,,] as well as novel consens […]


An RRM–ZnF RNA recognition module targets RBM10 to exonic sequences to promote exon exclusion

Nucleic Acids Res
PMCID: 5499739
PMID: 28379442
DOI: 10.1093/nar/gkx225

[…] understand whether the motifs deduced for RBM10 in vivo targets related to intrinsic sequence specificity of this protein, we analyzed the binding preference of its main RNA interacting region using RNAcompete (,) (Figure ). Briefly, purified proteins were incubated with a 75-fold excess of a non-randomized RNA pool, RBM10-selected RNAs were identified using microarray analysis and RNA-binding pr […]


RNA protein binding motifs mining with a new hybrid deep learning based cross domain knowledge integration approach

BMC Bioinformatics
PMCID: 5331642
PMID: 28245811
DOI: 10.1186/s12859-017-1561-8

[…] eferred as binding motifs. Detecting them can facilitate the deeper insights into post-transcriptional regulation.Although there are many genome-wide RNA-binding protein detection techniques, such as RNAcompete [], PAR-CLIP [], they are still cost-heavy and time-intensive. Fortunately, with the advent of these high-throughput techniques, many useful genome-wide data associated with RBPs are genera […]


Efficient Design of Compact Unstructured RNA Libraries Covering All k mers

J Comput Biol
PMCID: 4752187
PMID: 26713687
DOI: 10.1089/cmb.2015.0179

[…] tary information to protein RNA-binding preferences.Toward this aim, high-throughput in vitro methods have been developed to study the binding preferences of RBPs (Ray et al., ; Lambert et al., ). In RNAcompete (Ray et al., ), a specific protein binds to a set of predesigned oligos, and binding is measured using a florescence tag. The binding of the protein to a set of more than 200,000 probe sequ […]

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RNAcompete institution(s)
Banting and Best Department of Medical Research, University of Toronto, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
RNAcompete funding source(s)
Supported by grants to from CIHR (MOP-49451, MOP-14609, MOP-93671), by Natural Sciences and Engineering Research Council operating and Canadian Foundation of Innovation grants, Genome Canada through the Ontario Genomics Institute and the Ontario Research Fund, and by a National Science and Engineering Research Council of Canada (NSERC) postdoctoral fellowship.

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