ArticleBioinformatics (Oxford, England)2017
A comprehensive benchmark of RNA-RNA interaction prediction tools for all domains of life.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- An encyclopedic regulatory and functional atlas of RNA interactomes.Nature methods · 2026Article
- SUPER: Upcycling Genetic Parts for Precise Gene Expression Control, Leakage Minimization, and Genetic Circuit Stability.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The role of low-complexity repeats in RNA-RNA interactions and a deep learning framework for duplex prediction.Nature communications · 2026Article
- MiRInter-Trans: a transformer-based framework for microRNA interaction prediction.Bioinformatics advances · 2026Article
- Computational understanding of non-coding RNA pairwise interactions.Frontiers in artificial intelligence · 2026Article
- Hybrid MPI/OpenMP Implementation of RIblast for Transcriptome-Scale lncRNA-RNA Interaction Prediction.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Benchmarking the methods for predicting base pairs in RNA-RNA interactions.Bioinformatics (Oxford, England) · 2025Article
- GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions.BMC bioinformatics · 2025Article
- Advancing microRNA target site prediction with transformer and base-pairing patterns.Nucleic acids research · 2024Article
- Foundation models in molecular biology.Biophysics reports · 2024Article
- Experimental and computational methods for studying the dynamics of RNA-RNA interactions in SARS-COV2 genomes.Briefings in functional genomics · 2024Review
- CheRRI-Accurate classification of the biological relevance of putative RNA-RNA interaction sites.GigaScience · 2024Article
- TargetRNA3: predicting prokaryotic RNA regulatory targets with machine learning.Genome biology · 2023Article
- A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools.Briefings in bioinformatics · 2023Review
- The expression landscape and pangenome of long non-coding RNA in the fungal wheat pathogenMicrobial genomics · 2023Article
- LinearCoFold and LinearCoPartition: linear-time algorithms for secondary structure prediction of interacting RNA molecules.Nucleic acids research · 2023Article
- sInterBase: a comprehensive database of Escherichia coli sRNA-mRNA interactions.Bioinformatics (Oxford, England) · 2023Article
- Web Services for RNA-RNA Interaction Prediction.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Fast RNA-RNA Interaction Prediction Methods for Interaction Analysis of Transcriptome-Scale Large Datasets.Methods in molecular biology (Clifton, N.J.) · 2023Review
- A Comprehensive Computational Investigation into the Conserved Virulent Proteins ofMolecules (Basel, Switzerland) · 2022Article
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2 authors.
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Abstract
Motivation: The aim of this study is to assess the performance of RNA-RNA interaction prediction tools for all domains of life. Results: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. Availability and Implementation: We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. Contact: sinan.umu@pg.canterbury.ac.nz. Supplementary information: Supplementary data are available at Bioinformatics online.
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