ArticleBioinformatics (Oxford, England)2024
Tiberius: end-to-end deep learning with an HMM for gene prediction.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed.
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- A High-Quality Haplotype-Resolved Reference Genome for Drakensberger Cattle (Bos taurus indicus/taurus) Achieved Through Trio-Binned Long-Read Sequencing.Scientific data · 2026Article
- Convergent Functional Genomic Evolution Underlying Repeated Freshwater Colonization in Cetaceans.Journal of molecular evolution · 2026Article
- Dissecting flowering time and flower color in Carum carvi utilizing a long-read draft genome and a GBS-based QTL mapping.Scientific reports · 2026Article
- Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects.Briefings in bioinformatics · 2026Review
- AccuratebioRxiv : the preprint server for biology · 2026Article
- Highly accurate ab initio gene annotation with ANNEVO.Nature methods · 2026Article
- Learning genes deeply.Nature methods · 2026Article
- Helixer: ab initio prediction of primary eukaryotic gene models combining deep learning and a hidden Markov model.Nature methods · 2026Article
- A chromosome-level genome assembly of the South African indigenous, Kolbroek pig, Sus scrofa domesticus.Scientific data · 2026Article
- Annotation of 200 Insect Genomes with BRAKER for Consistent Comparisons across Species.Scientific data · 2026Article
- Cookbook for plant genome sequences.BMC genomics · 2026Review
- Improved reconstruction of transcripts and coding sequences from RNA-seq data.Nucleic acids research · 2026Article
- A high-quality chromosome level genome assembly of the South African indigenous Nguni goat (Capra hircus).Scientific data · 2026Article
- Ensembl 2026.Nucleic acids research · 2026Article
- Improving spliced alignment by modeling splice sites with deep learning.Algorithms for molecular biology : AMB · 2026Article
- Multi-feature fusion for gene prediction and functional peptide identification.Frontiers in microbiology · 2026Article
- CLAP-HMM: a biologically constrained deep learning framework for resistance gene prediction in long DNA sequences.BMC biotechnology · 2025Article
- GeneCAD: Plant Genome Annotation with a DNA Foundation Model.bioRxiv : the preprint server for biology · 2025Article
- Annotating the genome at single-nucleotide resolution with DNA foundation models.Nature methods · 2025Article
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4 authors.
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Abstract
motivationFor more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of ab initio eukaryotic gene prediction can be improved by combining deep learning layers with a separate HMM postprocessor.
resultsWe present Tiberius, a novel deep learning-based ab initio gene predictor that end-to-end integrates convolutional and long short-term memory layers with a differentiable HMM layer. Tiberius uses a custom gene prediction loss and was trained for prediction in mammalian genomes and evaluated on human and two other genomes. It significantly outperforms existing ab initio methods, achieving F1 scores of 62% at gene level for the human genome, compared to 21% for the next best ab initio method. In de novo mode, Tiberius predicts the exon-intron structure of two out of three human genes without error. Remarkably, even Tiberius's ab initio accuracy matches that of BRAKER3, which uses RNA-seq data and a protein database. Tiberius's highly parallelized model is the fastest state-of-the-art gene prediction method, processing the human genome in under 2 hours. AVAILABILITY AND IMPLEMENTATION: https://github.com/Gaius-Augustus/Tiberius.
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