ArticleNucleic acids research2021
RNAMotifContrast: a method to discover and visualize RNA structural motif subfamilies.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- ARTEM server: an online tool for nucleic acid 3D motif searches, 3D structure superposition and structure-based alignment.Nucleic acids research · 2026Article
- GINClus: RNA structural motif clustering using graph isomorphism network.NAR genomics and bioinformatics · 2025Article
- RNAMotifProfile: a graph-based approach to build RNA structural motif profiles.NAR genomics and bioinformatics · 2024Article
- A comprehensive survey of long-range tertiary interactions and motifs in non-coding RNA structures.Nucleic acids research · 2023Article
- RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families.Bioinformatics (Oxford, England) · 2023Article
- RNA-NRD: a non-redundant RNA structural dataset for benchmarking and functional analysis.NAR genomics and bioinformatics · 2023Article
- On the predictibility of A-minor motifs from their local contexts.RNA biology · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Understanding the 3D structural properties of RNAs will play a critical role in identifying their functional characteristics and designing new RNAs for RNA-based therapeutics and nanotechnology. While several existing computational methods can help in the analysis of RNA properties by recognizing structural motifs, they do not provide the means to compare and contrast those motifs extensively. We have developed a new method, RNAMotifContrast, which focuses on analyzing the similarities and variations of RNA structural motif characteristics. In this method, a graph is formed to represent the similarities among motifs, and a new traversal algorithm is applied to generate visualizations of their structural properties. Analyzing the structural features among motifs, we have recognized and generalized the concept of motif subfamilies. To asses its effectiveness, we have applied RNAMotifContrast on a dataset of known RNA structural motif families. From the results, we observed that the derived subfamilies possess unique structural variations while holding standard features of the families. Overall, the visualization approach of this method presents a new perspective to observe the relation among motifs more closely, and the discovered subfamilies provide opportunities to achieve valuable insights into RNA's diverse roles.
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Registered trials
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