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DeepASmRNA: Reference-free prediction of alternative splicing events with a scalable and interpretable deep learning model
Alternative splicing is crucial for a wide range of biological processes. However, limited by the availability of reference genomes, genome-wide patterns of alternative splicing remain unknown in most nonmodel organisms. We present an attention-based convolutional neural network model, DeepASmRNA, f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9619290/ https://www.ncbi.nlm.nih.gov/pubmed/36325068 http://dx.doi.org/10.1016/j.isci.2022.105345 |