ArticlePloS one2013
RNA-CODE: a noncoding RNA classification tool for short reads in NGS data lacking reference genomes.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Noncoding RNA family classification based on multifeature fusion and convolutional block attention residual network.Briefings in bioinformatics · 2025Article
- A Glimpse of Noncoding RNAs: Secondary Structure, Emerging Trends, and Potential Applications in Human Diseases.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Comparison and benchmark of deep learning methods for non-coding RNA classification.PLoS computational biology · 2024Article
- Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets.Functional & integrative genomics · 2023Review
- nRC: non-coding RNA Classifier based on structural features.BioData mining · 2017Article
- Integrating Epigenomics into the Understanding of Biomedical Insight.Bioinformatics and biology insights · 2016Review
- Reconstructing 16S rRNA genes in metagenomic data.Bioinformatics (Oxford, England) · 2015Article
- Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques.Frontiers in bioengineering and biotechnology · 2015Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The number of transcriptomic sequencing projects of various non-model organisms is still accumulating rapidly. As non-coding RNAs (ncRNAs) are highly abundant in living organism and play important roles in many biological processes, identifying fragmentary members of ncRNAs in small RNA-seq data is an important step in post-NGS analysis. However, the state-of-the-art ncRNA search tools are not optimized for next-generation sequencing (NGS) data, especially for very short reads. In this work, we propose and implement a comprehensive ncRNA classification tool (RNA-CODE) for very short reads. RNA-CODE is specifically designed for ncRNA identification in NGS data that lack quality reference genomes. Given a set of short reads, our tool classifies the reads into different types of ncRNA families. The classification results can be used to quantify the expression levels of different types of ncRNAs in RNA-seq data and ncRNA composition profiles in metagenomic data, respectively. The experimental results of applying RNA-CODE to RNA-seq of Arabidopsis and a metagenomic data set sampled from human guts demonstrate that RNA-CODE competes favorably in both sensitivity and specificity with other tools. The source codes of RNA-CODE can be downloaded at http://www.cse.msu.edu/~chengy/RNA_CODE.
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Registered trials
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