<ul data-eligibleForWebStory="false"><li>Terrier is a deep learning model designed to classify repetitive DNA sequences using a curated repeat sequence library trained under the RepeatMasker schema.</li><li>The model overcomes challenges in accurate classification of repetitive DNA sequences by leveraging deep learning, providing improved accuracy compared to current methods.</li><li>Terrier, trained on Repbase with over 100,000 repeat families, maps 97.1% of Repbase sequences to RepeatMasker categories, offering a comprehensive classification system.</li><li>Benchmarked against other models, Terrier demonstrated superior accuracy in model organisms and non-model species, facilitating research on repeat-driven evolution and genomic instability.</li></ul>

Terrier: A Deep Learning Repeat Classifier

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