ArticlePLoS computational biology2016
Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Partners in Silencing: Decoding the Mammalian Argonaute Interactome.Non-coding RNA · 2025Review
- The power of microRNA regulation-insights into immunity and metabolism.FEBS letters · 2025Review
- Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.PLoS computational biology · 2024Article
- Empowering prediction of miRNA-mRNA interactions in species with limited training data through transfer learning.Heliyon · 2024Article
- Review
- MiRNA fine tuning for crop improvement: using advance computational models and biotechnological tools.Molecular biology reports · 2022Review
- Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation.Advances in experimental medicine and biology · 2022Article
- Comprehensive machine-learning-based analysis of microRNA-target interactions reveals variable transferability of interaction rules across species.BMC bioinformatics · 2021Article
- Cross-Linking Ligation and Sequencing of Hybrids (qCLASH) Reveals an Unpredicted miRNA Targetome in Melanoma Cells.Cancers · 2021Article
- Prediction methods for microRNA targets in bilaterian animals: Toward a better understanding by biologists.Computational and structural biotechnology journal · 2021Review
- miRNA Combinatorics and its Role in Cell State Control-A Probabilistic Approach.Frontiers in molecular biosciences · 2021Article
- Article
- Position-wise binding preference is important for miRNA target site prediction.Bioinformatics (Oxford, England) · 2020Article
- MicroRNA Assisted Gene Regulation in Colorectal Cancer.International journal of molecular sciences · 2019Article
- Comprehensive Analysis of Human microRNA-mRNA Interactome.Frontiers in genetics · 2019Article
- Recent computational developments on CLIP-seq data analysis and microRNA targeting implications.Briefings in bioinformatics · 2018Review
- Mapping transcriptome-wide protein-RNA interactions to elucidate RNA regulatory programs.Quantitative biology (Beijing, China) · 2018Article
- mirDIP 4.1-integrative database of human microRNA target predictions.Nucleic acids research · 2018Article
- Association between polymorphisms in microRNA target sites and survival in early-stage non-small cell lung cancer.Thoracic cancer · 2017Article
- Global mapping of miRNA-target interactions in cattle (Bos taurus).Scientific reports · 2017Article
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2 authors.
Funding
Abstract
Recent technologies like AGO CLIP sequencing and CLASH enable direct transcriptome-wide identification of AGO binding and miRNA target sites, but the most widely used miRNA target prediction algorithms do not exploit these data. Here we use discriminative learning on AGO CLIP and CLASH interactions to train a novel miRNA target prediction model. Our method combines two SVM classifiers, one to predict miRNA-mRNA duplexes and a second to learn a binding model of AGO's local UTR sequence preferences and positional bias in 3'UTR isoforms. The duplex SVM model enables the prediction of non-canonical target sites and more accurately resolves miRNA interactions from AGO CLIP data than previous methods. The binding model is trained using a multi-task strategy to learn context-specific and common AGO sequence preferences. The duplex and common AGO binding models together outperform existing miRNA target prediction algorithms on held-out binding data. Open source code is available at https://bitbucket.org/leslielab/chimiric.
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