DeepEnhancer: Predicting enhancers by convolutional neural networks

By Xu Min, Ning Chen, Ting Chen, Rui Jiang. 2016

40 citations recorded by the source corpus.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Casey S. Greene
2. Yifan Peng
3. Brett K. Beaulieu-Jones
4. G. Way
5. Amr M. Alexandari
6. Zhiyong Lu
7. Avanti Shrikumar
8. S. Joshua Swamidass

Citations in the corpus

• Opportunities and obstacles for deep learning in biology and medicine (2017, methodology): “[179] demonstrated how training on the experimentally validated FANTOM5 permissive enhancer dataset followed by fine-tuning on ENCODE enhancer datasets improved cell type-specific predictions, outperforming state-of-the-art results.”