2017
DOI: 10.1093/bioinformatics/btx704
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BEAM web server: a tool for structural RNA motif discovery

Abstract: MotivationRNA structural motif finding is a relevant problem that becomes computationally hard when working on high-throughput data (e.g. eCLIP, PAR-CLIP), often represented by thousands of RNA molecules. Currently, the BEAM server is the only web tool capable to handle tens of thousands of RNA in input with a motif discovery procedure that is only limited by the current secondary structure prediction accuracies.ResultsThe recently developed method BEAM (BEAr Motifs finder) can analyze tens of thousands of RNA… Show more

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Cited by 11 publications
(17 citation statements)
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References 19 publications
(22 reference statements)
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“…LIN28A (43,44) has a zinc-finger domain CCHC that has been hypothesized to bind an internal loop in the hairpin containing the sequence motif, at variable distances (45,46). The sequence motif that BEAM identifies is similar to the one found by other methods: the motif found in the data from Cho and colleagues is found in 38% of the RNA, and the structure motif shows an internal loop structure in the hairpin, in 37% of RNAs.…”
Section: Resultsmentioning
confidence: 99%
“…LIN28A (43,44) has a zinc-finger domain CCHC that has been hypothesized to bind an internal loop in the hairpin containing the sequence motif, at variable distances (45,46). The sequence motif that BEAM identifies is similar to the one found by other methods: the motif found in the data from Cho and colleagues is found in 38% of the RNA, and the structure motif shows an internal loop structure in the hairpin, in 37% of RNAs.…”
Section: Resultsmentioning
confidence: 99%
“…It has been well documented that linear representations such as Positional Weight Matrices (PWM) have their limitations in capturing the binding preferences (85,86). A number of methods such as BEAM or GraphProt have improved upon PWMs by adding structural descriptors to each position, i.e., helix, stem, loop, etc, which has showed improvement (16,25). Despite these recent developments, we feel there is still room for improvement.…”
Section: Discussionmentioning
confidence: 99%
“…For example, RNA binding domains can be grouped into single stranded or double stranded RNA binding domains, ssRBD and dsRBD, based on their preference for RNA targets that are either single stranded (unpaired) or double stranded (paired). A number of computational methods had been developed to ascertain the structure properties of these RBP bound RNAs with the aim to incorporate structural information into a predictive model that can help decode mechanisms that regulate protein-RNA interactions (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33). A number of these representative methods are briefly described below.…”
Section: Introductionmentioning
confidence: 99%
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