Verna l: a tool for mining fuzzy network motifs in RNA
| Autor: | Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Flexibility (engineering) Source code Theoretical computer science Computer science media_common.quotation_subject Framing (World Wide Web) Node (networking) Biochemistry Computer Science Applications Set (abstract data type) Computational Mathematics ComputingMethodologies_PATTERNRECOGNITION Computational Theory and Mathematics Graph (abstract data type) Cluster analysis Molecular Biology media_common Network analysis |
| Zdroj: | Bioinformatics. 38:970-976 |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | Motivation RNA 3D motifs are recurrent substructures, modeled as networks of base pair interactions, which are crucial for understanding structure–function relationships. The task of automatically identifying such motifs is computationally hard, and remains a key challenge in the field of RNA structural biology and network analysis. State-of-the-art methods solve special cases of the motif problem by constraining the structural variability in occurrences of a motif, and narrowing the substructure search space. Results Here, we relax these constraints by posing the motif finding problem as a graph representation learning and clustering task. This framing takes advantage of the continuous nature of graph representations to model the flexibility and variability of RNA motifs in an efficient manner. We propose a set of node similarity functions, clustering methods and motif construction algorithms to recover flexible RNA motifs. Our tool, Vernal can be easily customized by users to desired levels of motif flexibility, abundance and size. We show that Vernal is able to retrieve and expand known classes of motifs, as well as to propose novel motifs. Availability and implementation The source code, data and a webserver are available at vernal.cs.mcgill.ca. We also provide a flexible interface and a user-friendly webserver to browse and download our results. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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