ArticleScientific reports2016
lncScore: alignment-free identification of long noncoding RNA from assembled novel transcripts.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed, 52 citations in OpenAlex.
- Computational identification and characterization of noncoding RNA-encoded peptides: tools, databases, and in silico strategies.Amino acids · 2026Review
- Metamorphosis and lncRNAs: A Close Relationship.Genesis (New York, N.Y. : 2000) · 2026Review
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- Long noncoding RNA study: Genome-wide approaches.Genes & diseases · 2023Review
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- A large-scale benchmark study of tools for the classification of protein-coding and non-coding RNAs.Nucleic acids research · 2022Article
- LncDC: a machine learning-based tool for long non-coding RNA detection from RNA-Seq data.Scientific reports · 2022Article
- pHisPred: a tool for the identification of histidine phosphorylation sites by integrating amino acid patterns and properties.BMC bioinformatics · 2022Article
- Deep learning tools are top performers in long non-coding RNA prediction.Briefings in functional genomics · 2022Article
- Advances in Computational Methodologies for Classification and Sub-Cellular Locality Prediction of Non-Coding RNAs.International journal of molecular sciences · 2021Review
- LncRNA Ctcflos orchestrates transcription and alternative splicing in thermogenic adipogenesis.EMBO reports · 2021Article
- Incorporating Machine Learning into Established Bioinformatics Frameworks.International journal of molecular sciences · 2021Review
- Differential RNA splicing as a potentially important driver mechanism in multiple myeloma.Haematologica · 2021Article
- A systematic evaluation of bioinformatics tools for identification of long noncoding RNAs.RNA (New York, N.Y.) · 2021Article
- Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa.Antioxidants (Basel, Switzerland) · 2020Article
- RNAsamba: neural network-based assessment of the protein-coding potential of RNA sequences.NAR genomics and bioinformatics · 2020Article
- The computational approaches of lncRNA identification based on coding potential:Computational and structural biotechnology journal · 2020Review
- LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property.Briefings in bioinformatics · 2019Review
- Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.DNA research : an international journal for rapid publication of reports on genes and genomes · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
RNA-Seq based transcriptome assembly has been widely used to identify novel lncRNAs. However, the best-performing transcript reconstruction methods merely identified 21% of full-length protein-coding transcripts from H. sapiens. Those partial-length protein-coding transcripts are more likely to be classified as lncRNAs due to their incomplete CDS, leading to higher false positive rate for lncRNA identification. Furthermore, potential sequencing or assembly error that gain or abolish stop codons also complicates ORF-based prediction of lncRNAs. Therefore, it remains a challenge to identify lncRNAs from the assembled transcripts, particularly the partial-length ones. Here, we present a novel alignment-free tool, lncScore, which uses a logistic regression model with 11 carefully selected features. Compared to other state-of-the-art alignment-free tools (e.g. CPAT, CNCI, and PLEK), lncScore outperforms them on accurately distinguishing lncRNAs from mRNAs, especially partial-length mRNAs in the human and mouse datasets. In addition, lncScore also performed well on transcripts from five other species (Zebrafish, Fly, C. elegans, Rat, and Sheep). To speed up the prediction, multithreading is implemented within lncScore, and it only took 2 minute to classify 64,756 transcripts and 54 seconds to train a new model with 21,000 transcripts with 12 threads, which is much faster than other tools. lncScore is available at https://github.com/WGLab/lncScore.
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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.