Evaluating the informativeness of deep learning annotations for human complex diseases
oleh: Kushal K. Dey, Bryce van de Geijn, Samuel Sungil Kim, Farhad Hormozdiari, David R. Kelley, Alkes L. Price
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2020-09-01 |
Deskripsi
Deep learning models have shown great promise in predicting regulatory effects from DNA sequence. Here the authors evaluate sequence-based epigenomic deep learning models and conclude that these models are not yet ready to inform our knowledge of human disease.