A comprehensive benchmark and guide for sequence-function interpretable deep learning models in genomics
Canzhuang Sun, Yu Sun, Kang Xu, Zhijie He, Zhengwei Li, Yaru Li, YU Zong-yuan, Yuyang Wang, Xuanwei Lin, Xiang Shang Xu, Pengzhen Hu, Xiaochen Bo, Mingzhi Liao, Hebing Chen
This paper benchmarks sequence-function deep learning models using ATAC-seq data, showing that different models and interpretability methods are better suited to specific tasks.
bioRxiv · Jan 6, 2025 · PreprintBioinformatics