Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings

Deep learning methods have recently become the state-of-the-art in a variety of regulatory genomic tasks(1–6) including the prediction of gene expression from genomic DNA. As such, these methods promise to serve as important tools in interpreting the full spectrum of genetic variation observed in pe...

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Detalles Bibliográficos
Autores principales: Sasse, Alexander, Ng, Bernard, Spiro, Anna E., Tasaki, Shinya, Bennett, David A., Gaiteri, Christopher, De Jager, Philip L., Chikina, Maria, Mostafavi, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055057/
https://www.ncbi.nlm.nih.gov/pubmed/36993652
http://dx.doi.org/10.1101/2023.03.16.532969

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055057/
https://www.ncbi.nlm.nih.gov/pubmed/36993652
http://dx.doi.org/10.1101/2023.03.16.532969

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