Predicting microRNA-environmental factor interactions based on bi-random walk and multi-label learning. - Wei Lan; Jianxin Wang 001; Min Li 007; Chengqian Lu; Fang-Xiang Wu; Yi Pan 001 (BIBM, 2016)

Applications of deep learning to MRI images: A survey. - Jin Liu 012; Yi Pan 001; Min Li 007; Ziyue Chen; Lu Tang; Chengqian Lu; Jianxin Wang 001 (Big Data Min. Anal., 2018)

Prediction of lncRNA-disease associations based on inductive matrix completion. - Chengqian Lu; Mengyun Yang; Feng Luo 001; Fang-Xiang Wu; Min Li 007; Yi Pan 001; Yaohang Li; Jianxin Wang 001 (Bioinform., 2018)

LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques. - Min Zeng; Chengqian Lu; Fuhao Zhang; Zhangli Lu; Fang-Xiang Wu; Yaohang Li; Min Li 007 (BIBM, 2019)

Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion. - Chengqian Lu; Mengyun Yang; Min Li 007; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2020)

HGIMC: heterogeneous graph inference with matrix completion for computational drug repositioning. - Mengyun Yang; Lan Huang; Yunpei Xu; Chengqian Lu; Jianxin Wang 001 (Zenodo, 2020)

Improving circRNA-disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks. - Chengqian Lu; Min Zeng; Fang-Xiang Wu; Min Li 007; Jianxin Wang 001 (Bioinform., 2021)

Heterogeneous graph inference with matrix completion for computational drug repositioning. - Mengyun Yang; Lan Huang; Yunpei Xu; Chengqian Lu; Jianxin Wang 001 (Bioinform., 2021)

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations. - Min Zeng; Chengqian Lu; Zhihui Fei; Fang-Xiang Wu; Yaohang Li; Jianxin Wang 001; Min Li 007 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Deep Matrix Factorization Improves Prediction of Human CircRNA-Disease Associations. - Chengqian Lu; Min Zeng; Fuhao Zhang; Fang-Xiang Wu; Min Li 007; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2021)

DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding. - Min Zeng; Yifan Wu 008; Chengqian Lu; Fuhao Zhang; Fang-Xiang Wu; Min Li 007 (Briefings Bioinform., 2022)

GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation. - Min Li 007; Baoying Zhao; Rui Yin 002; Chengqian Lu; Fei Guo 001; Min Zeng (Briefings Bioinform., 2023)

Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network. - Chengqian Lu; Lishen Zhang; Min Zeng; Wei Lan; Guihua Duan; Jianxin Wang 001 (Briefings Bioinform., 2023)

CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features. - Lishen Zhang; Chengqian Lu; Min Zeng; Yaohang Li; Jianxin Wang 001 (Briefings Bioinform., 2023)

LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism. - Min Zeng; Yifan Wu 008; Yiming Li; Rui Yin 002; Chengqian Lu; Junwen Duan; Min Li 007 (Bioinform., 2023)

Sea-land segmentation method based on an improved MA-Net for Gaofen-2 images. - Chengqian Lu; YuanChao Wen; Yangdong Li; Qinghong Mao; Yuehua Zhai (Earth Sci. Informatics, 2024)

CellCircLoc: Deep Neural Network for Predicting and Explaining Cell Line-Specific CircRNA Subcellular Localization. - Min Zeng; Jingwei Lu; Yiming Li; Chengqian Lu; Shichao Kan; Fei Guo 001; Min Li 007 (IEEE J. Biomed. Health Informatics, 2025)