ArticleRNA (New York, N.Y.)2006
RNA secondary structure prediction from sequence alignments using a network of k-nearest neighbor classifiers.
Article in RNA (New York, N.Y.), 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Artificial Intelligence-Driven Nanoarchitectonics for Smart Targeted Drug Delivery.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Transformers in RNA structure prediction: A review.Computational and structural biotechnology journal · 2025Review
- Design and Prediction of Aptamers Assisted by In Silico Methods.Biomedicines · 2023Review
- Review
- Review of machine learning methods for RNA secondary structure prediction.PLoS computational biology · 2021Review
- PlncRNA-HDeep: plant long noncoding RNA prediction using hybrid deep learning based on two encoding styles.BMC bioinformatics · 2021Article
- Artificial Intelligence in Aptamer-Target Binding Prediction.International journal of molecular sciences · 2021Review
- Detecting genetic interactions using parallel evolution in experimental populations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- Genetic variants in mRNA untranslated regions.Wiley interdisciplinary reviews. RNA · 2018Review
- DECIPHER: harnessing local sequence context to improve protein multiple sequence alignment.BMC bioinformatics · 2015Article
- Computational detection of abundant long-range nucleotide covariation in Drosophila genomes.RNA (New York, N.Y.) · 2013Article
- Effective classification of microRNA precursors using feature mining and AdaBoost algorithms.Omics : a journal of integrative biology · 2013Article
- Evolutionary evidence for alternative structure in RNA sequence co-variation.PLoS computational biology · 2013Article
- Predicting pseudoknotted structures across two RNA sequences.Bioinformatics (Oxford, England) · 2012Article
- Article
- Multistrand RNA secondary structure prediction and nanostructure design including pseudoknots.ACS nano · 2011Article
- RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences.Bioinformatics (Oxford, England) · 2011Article
- A conditional random fields method for RNA sequence-structure relationship modeling and conformation sampling.Bioinformatics (Oxford, England) · 2011Article
- Exonic DNA sequencing of ERBB4 in bipolar disorder.PloS one · 2011Article
- Disease-associated mutations that alter the RNA structural ensemble.PLoS genetics · 2010Article
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2 authors.
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Abstract
We present a machine learning method (a hierarchical network of k-nearest neighbor classifiers) that uses an RNA sequence alignment in order to predict a consensus RNA secondary structure. The input to the network is the mutual information, the fraction of complementary nucleotides, and a novel consensus RNAfold secondary structure prediction of a pair of alignment columns and its nearest neighbors. Given this input, the network computes a prediction as to whether a particular pair of alignment columns corresponds to a base pair. By using a comprehensive test set of 49 RFAM alignments, the program KNetFold achieves an average Matthews correlation coefficient of 0.81. This is a significant improvement compared with the secondary structure prediction methods PFOLD and RNAalifold. By using the example of archaeal RNase P, we show that the program can also predict pseudoknot interactions.
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