bioRxivBioinformaticsPreprint
CPLfold: Chimeric and Pseudoknot-capable almost Linear-time RNA Secondary Structure Prediction
Abstract
Motivation RNA structure plays a central role in how transcripts function, but inferring it reliably remains difficult, especially when pseudoknots need to be part of the prediction. Chemical probing experiments provide additional signals, yet these signals do not directly identify base pairing partners. RNA proximity ligation provides direct evidence of base pairing, but balancing this evidence with pseudoknot prediction accuracy and scalability of structure prediction for long sequences remains challenging. Results We present CPLfold, a fast and flexible RNA folding method that combines thermodynamic modeling with chimeric evidence from RNA cross-linking and ligation experiments, while naturally supporting pseudoknots. CPLfold scales to long sequences and recovers more accurate global structures and long-range interactions than existing approaches across multiple benchmarks such as COMRADES and IRIS. By tuning two simple trade-off parameters (, {beta}) the method allows flexibility in the level of incorporating chimeric evidence and asserting pseudoknots. Availability and Implementation Source code and scripts are available at https://github.com/Vicky-0256/CPLfold. ContactK.Wang-72@sms.ed.ac.uk
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- rpcFold: residual parallel convolutional neural network to decipher RNA folding from RNA sequence
Nandita Sharma, Pralay Mitra·bioRxiv·Aug 26, 2024
- Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials
Tiansu Gong, Fusong Ju, Dongbo Bu·bioRxiv·Sep 19, 2022
- RNA structure prediction including pseudoknots through direct enumeration of states
O. Kimchi, T. Cragnolini, … L. J. Colwell·bioRxiv·Jun 4, 2018
- A divide-and-conquer approach based on deep learning for long RNA secondary structure prediction: focus on pseudoknots identification
Loïc Omnes, Éric Angel, … Fariza Tahi·PLoS ONEPeer-reviewed·Apr 25, 2025
- RNA secondary structure prediction with Convolutional Neural Networks
Mehdi Saman Booy, Alexander Ilin, Pekka Orponen·BMC BioinformaticsPeer-reviewed·Feb 2, 2022
- UFold: Fast and Accurate RNA Secondary Structure Prediction with Deep Learning
Laiyi Fu, Yingxin Cao, … Xiaohui S. Xie·Nucleic Acids ResearchPeer-reviewed·Oct 20, 2021