Chromatin accessibility prediction via a hybrid deep convolutional neural network. - Qiao Liu 008; Fei Xia 002; Qijin Yin; Rui Jiang 001 (Bioinform., 2018)

DeepHistone: a deep learning approach to predicting histone modifications. - Qijin Yin; Mengmeng Wu; Qiao Liu 008; Hairong Lv; Rui Jiang 001 (BMC Genom., 2019)

An efficient curriculum learning-based strategy for molecular graph learning. - Yaowen Gu; Si Zheng 001; Zidu Xu; Qijin Yin; Liang Li; Jiao Li 001 (Briefings Bioinform., 2022)

scGraph: a graph neural network-based approach to automatically identify cell types. - Qijin Yin; Qiao Liu 008; Zhuoran Fu; Wanwen Zeng; Boheng Zhang; Xuegong Zhang; Rui Jiang 001; Hairong Lv (Bioinform., 2022)

REDDA: Integrating multiple biological relations to heterogeneous graph neural network for drug-disease association prediction. - Yaowen Gu; Si Zheng 001; Qijin Yin; Rui Jiang 001; Jiao Li 001 (Comput. Biol. Medicine, 2022)

HiChIPdb: a comprehensive database of HiChIP regulatory interactions. - Wanwen Zeng; Qiao Liu 008; Qijin Yin; Rui Jiang 001; Wing Hung Wong (Nucleic Acids Res., 2023)

DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction. - Qijin Yin; Rui Fan; Xusheng Cao; Qiao Liu 008; Rui Jiang 001; Wanwen Zeng (Quant. Biol., 2023)

TrinityDNA: A Bio-Inspired Foundational Model for Efficient Long-Sequence DNA Modeling. - Qirong Yang; Yucheng Guo; Zicheng Liu 006; Yujie Yang; Qijin Yin; Siyuan Li 002; Shaomin Ji; Linlin Chao; Xiaoming Zhang; Stan Z. Li (CoRR, 2025)