ArticleBriefings in bioinformatics2021
CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 31 citations in OpenAlex.
- A ubiquitinated E2-based mRNA vaccine confers complete protection against lethal challenge with classical swine fever virus.Journal of virology · 2026Article
- Benchmarking Software for DDA-PASEF Immunopeptidomics.Molecular & cellular proteomics : MCP · 2026Article
- Article
- The green lacewing venom system and the complex mechanisms underlying its evolution.Molecular biology and evolution · 2026Article
- Newly Evolved Endogenous Retroviruses Prime the Ovarian Reserve for Activation.Research square · 2025Article
- Newly Evolved Endogenous Retroviruses Prime the Ovarian Reserve for Activation.bioRxiv : the preprint server for biology · 2025Article
- Chromosome-Contiguous Reference Genome forInternational journal of molecular sciences · 2025Article
- Building better genome annotations across the tree of life.Genome research · 2025Article
- gymnotoa-db: a database and application to optimize functional annotation in gymnosperms.Database : the journal of biological databases and curation · 2025Article
- Technological breakthroughs and advancements in the application of mRNA vaccines: a comprehensive exploration and future prospects.Frontiers in immunology · 2025Review
- Cell wall modulation by drought and elevated COFrontiers in plant science · 2025Article
- TIdeS: A Comprehensive Framework for Accurate Open Reading Frame Identification and Classification in Eukaryotic Transcriptomes.Genome biology and evolution · 2024Article
- HPC-T-Annotator: an HPC tool for de novo transcriptome assembly annotation.BMC bioinformatics · 2024Article
- Stress-induced nuclear translocation of ONAC023 improves drought and heat tolerance through multiple processes in rice.Nature communications · 2024Article
- A survey of experimental and computational identification of small proteins.Briefings in bioinformatics · 2024Review
- Article
- The Time-Resolved Salt Stress Response ofInternational journal of molecular sciences · 2023Article
- Independent Recruitment of Different Types of Phospholipases A2 to the Venoms of Caenophidian Snakes: The Rise of PLA2-IIE within Pseudoboini (Dipsadidae).Molecular biology and evolution · 2023Article
- Integrative analysis in Pinus revealed long-term heat stress splicing memory.The Plant journal : for cell and molecular biology · 2022Article
- Differences in PLAToxins · 2022Article
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationCharacterization of the coding sequences (CDSs) is an essential step in transcriptome annotation. Incorrect identification of CDSs can lead to the prediction of non-existent proteins that can eventually compromise knowledge if databases are populated with similar incorrect predictions made in different genomes. Also, the correct identification of CDSs is important for the characterization of the untranslated regions (UTRs), which are known to be important regulators of the mRNA translation process. Considering this, we present CodAn (Coding sequence Annotator), a new approach to predict confident CDS and UTR regions in full or partial transcriptome sequences in eukaryote species.
resultsOur analysis revealed that CodAn performs confident predictions on full-length and partial transcripts with the strand sense of the CDS known or unknown. The comparative analysis showed that CodAn presents better overall performance than other approaches, mainly when considering the correct identification of the full CDS (i.e. correct identification of the start and stop codons). In this sense, CodAn is the best tool to be used in projects involving transcriptomic data. AVAILABILITY: CodAn is freely available at https://github.com/pedronachtigall/CodAn. CONTACT: aland@usp.br. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.
Indexed as
Identifiers
What Socratic 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 Socratic graph.