Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes

There is growing evidence for the importance of 3’ untranslated region (3’UTR) dependent regulatory processes. However, our current human 3’UTR catalogue is incomplete. Here, we develop a machine learning-based framework, leveraging both genomic and tissue-specific transcriptomic features to predict...

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Detalles Bibliográficos
Autores principales: Sethi, Siddharth, Zhang, David, Guelfi, Sebastian, Chen, Zhongbo, Garcia-Ruiz, Sonia, Olagbaju, Emmanuel O., Ryten, Mina, Saini, Harpreet, Botia, Juan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046390/
https://www.ncbi.nlm.nih.gov/pubmed/35477703
http://dx.doi.org/10.1038/s41467-022-30017-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046390/
https://www.ncbi.nlm.nih.gov/pubmed/35477703
http://dx.doi.org/10.1038/s41467-022-30017-z

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