ArticleNAR genomics and bioinformatics2020
RNAsamba: neural network-based assessment of the protein-coding potential of RNA sequences.
Article in NAR genomics and bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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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
67 citing papers in PubMed, 125 citations in OpenAlex.
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- A microprotein atlas of the human frontal cortex in Alzheimer's disease.Nature aging · 2026Article
- PFGPred: a stack ensemble classifier for the identification of fusion genes in plants.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026Article
- Benchmarking reveals the superiority of nucleic acid foundation models in predicting lncRNA coding potential.Genome biology · 2026Article
- The long non-coding RNA landscape of endurance exercise training.Molecular metabolism · 2026Article
- Unraveling lncRNA diversity at a single cell resolution and in a spatial context across different cancer types.Nature methods · 2026Article
- Peptides from the Shadows: Molecular Depth Insights and Clinical Horizons of Circular RNA-encoded Peptides in Gliomas.Neuromolecular medicine · 2026Review
- Computational identification and characterization of noncoding RNA-encoded peptides: tools, databases, and in silico strategies.Amino acids · 2026Review
- Uncertainty-aware benchmarking reveals ambiguous transcripts in mRNA-lncRNA classification.bioRxiv : the preprint server for biology · 2026Article
- Skin Colour in Salamanders Is Modulated by Both Epitranscriptomic Methylation and Gene Expression.Molecular ecology · 2026Article
- Benchmarking methods for genome annotation using nanopore direct RNA in a non-model crop plant.Bioinformatics advances · 2026Article
- LncPlankton: a comprehensive database of candidate lncRNAs from marine microbial eukaryotes.NAR genomics and bioinformatics · 2025Article
- The Long Non-coding RNA Landscape of Endurance Exercise Training.bioRxiv : the preprint server for biology · 2025Article
- Evaluating computational tools for protein-coding sequence detection: Are they up to the task?RNA (New York, N.Y.) · 2025Article
- InfoScan: A New Transcript Identification Tool Based on scRNA-Seq and Its Application in Glioblastoma.International journal of molecular sciences · 2025Article
- Identification and functional analysis of growth rate associated long non-coding RNAs inComputational and structural biotechnology journal · 2025Article
- PSQAN: a pipeline to prioritize novel and biologically relevant transcripts from long-read RNA sequencing.Bioinformatics advances · 2025Article
- Recent Advances in Peptide Drug Discovery: Novel Strategies and Targeted Protein Degradation.Pharmaceutics · 2024Review
- Comparative Tissue Identification and Characterization of Long Non-Coding RNAs in the Globally Distributed Blue SharkLife (Basel, Switzerland) · 2024Article
- LncRNA-encoded peptides in cancer.Journal of hematology & oncology · 2024Review
7 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of high-throughput sequencing technologies made it possible to obtain large volumes of genetic information, quickly and inexpensively. Thus, many efforts are devoted to unveiling the biological roles of genomic elements, being the distinction between protein-coding and long non-coding RNAs one of the most important tasks. We describe RNAsamba, a tool to predict the coding potential of RNA molecules from sequence information using a neural network-based that models both the whole sequence and the ORF to identify patterns that distinguish coding from non-coding transcripts. We evaluated RNAsamba's classification performance using transcripts coming from humans and several other model organisms and show that it recurrently outperforms other state-of-the-art methods. Our results also show that RNAsamba can identify coding signals in partial-length ORFs and UTR sequences, evidencing that its algorithm is not dependent on complete transcript sequences. Furthermore, RNAsamba can also predict small ORFs, traditionally identified with ribosome profiling experiments. We believe that RNAsamba will enable faster and more accurate biological findings from genomic data of species that are being sequenced for the first time. A user-friendly web interface, the documentation containing instructions for local installation and usage, and the source code of RNAsamba can be found at https://rnasamba.lge.ibi.unicamp.br/.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.