Tiberius: end-to-end deep learning with an HMM for gene prediction.
Journal:
Bioinformatics (Oxford, England)
PMID:
39558581
Abstract
MOTIVATION: For 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.