ArticleFrontiers in genetics2022
i5hmCVec: Identifying 5-Hydroxymethylcytosine Sites of
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
- Deep learning based prediction of RNA 5hmC modifications using composite feature representations and comparative benchmarking with transformer models.BioData mining · 2026Article
- RNADSN: Transfer-Learning 5-Methyluridine (mInternational journal of molecular sciences · 2022Article
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2 authors at 1 institution in 1 country.
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Abstract
5-Hydroxymethylcytosine (5hmC), one of the most important RNA modifications, plays an important role in many biological processes. Accurately identifying RNA modification sites helps understand the function of RNA modification. In this work, we propose a computational method for identifying 5hmC-modified regions using machine learning algorithms. We applied a sequence feature embedding method based on the dna2vec algorithm to represent the RNA sequence. The results showed that the performance of our model is better that of than state-of-art methods. All dataset and source codes used in this study are available at: https://github.com/liu-h-y/5hmC_model.
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