A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: Focus on pseudoknots identification
Loïc Omnes, Eric Angel, Pierre Bartet, François Radvanyi, Fariza Tahi, Emanuele Paci, Emanuele Paci, Emanuele Paci, Emanuele Paci
TL;DR
This paper introduces DivideFold, a deep learning method that improves the prediction of RNA secondary structures, especially pseudoknots, in long RNA sequences.
Contribution
DivideFold uses a divide-and-conquer strategy to enhance pseudoknot prediction accuracy and scalability for long RNA sequences.
Findings
DivideFold outperforms existing methods in predicting pseudoknots in long RNA sequences.
The method scales effectively by breaking down RNA sequences into manageable fragments.
It maintains high accuracy while handling the computational complexity of long RNA structures.
Abstract
The accurate prediction of RNA secondary structure, and pseudoknots in particular, is of great importance in understanding the functions of RNAs since they give insights into their folding in three-dimensional space. However, existing approaches often face computational challenges or lack precision when dealing with long RNA sequences and/or pseudoknots. To address this, we propose a divide-and-conquer method based on deep learning, called DivideFold, for predicting the secondary structures including pseudoknots of long RNAs. Our approach is able to scale to long RNAs by recursively partitioning sequences into smaller fragments until they can be managed by an existing model able to predict RNA secondary structure including pseudoknots. We show that our approach exhibits superior performance compared to state-of-the-art methods for pseudoknot prediction and secondary structure prediction…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 29
Figure 30Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRNA and protein synthesis mechanisms · RNA modifications and cancer · RNA Research and Splicing