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ORCIDChengqian Lu
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- affiliation: Central South University, Changsha, Hunan, China
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2020 – today
- 2024
[j13]Chengqian Lu, YuanChao Wen, Yangdong Li
, Qinghong Mao, Yuehua Zhai:
Sea-land segmentation method based on an improved MA-Net for Gaofen-2 images. Earth Sci. Informatics 17(5): 4115-4129 (2024)- 2023
- [j12]Min Li, Baoying Zhao, Rui Yin, Chengqian Lu, Fei Guo, Min Zeng:
GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation. Briefings Bioinform. 24(1) (2023) - [j11]Chengqian Lu, Lishen Zhang, Min Zeng, Wei Lan, Guihua Duan, Jianxin Wang:
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network. Briefings Bioinform. 24(1) (2023) - [j10]Lishen Zhang, Chengqian Lu, Min Zeng, Yaohang Li, Jianxin Wang:
CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features. Briefings Bioinform. 24(1) (2023) - [j9]Min Zeng, Yifan Wu, Yiming Li, Rui Yin, Chengqian Lu, Junwen Duan, Min Li:
LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism. Bioinform. 39(12) (2023) - 2022
- [j8]Min Zeng, Yifan Wu, Chengqian Lu, Fuhao Zhang, Fang-Xiang Wu, Min Li:
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding. Briefings Bioinform. 23(1) (2022) - 2021
- [j7]Mengyun Yang, Lan Huang, Yunpei Xu, Chengqian Lu, Jianxin Wang:
Heterogeneous graph inference with matrix completion for computational drug repositioning. Bioinform. 36(22-23): 5456-5464 (2021) - [j6]Chengqian Lu, Min Zeng, Fang-Xiang Wu, Min Li, Jianxin Wang:
Improving circRNA-disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks. Bioinform. 36(24): 5656-5664 (2021) - [j5]Min Zeng, Chengqian Lu, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Jianxin Wang, Min Li:
DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2353-2363 (2021) - [j4]Chengqian Lu, Min Zeng, Fuhao Zhang, Fang-Xiang Wu, Min Li, Jianxin Wang:
Deep Matrix Factorization Improves Prediction of Human CircRNA-Disease Associations. IEEE J. Biomed. Health Informatics 25(3): 891-899 (2021) - 2020
- [j3]Chengqian Lu, Mengyun Yang, Min Li, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion. IEEE J. Biomed. Health Informatics 24(8): 2420-2429 (2020) - [d1]Mengyun Yang, Lan Huang, Yunpei Xu, Chengqian Lu, Jianxin Wang:
HGIMC: heterogeneous graph inference with matrix completion for computational drug repositioning. Zenodo, 2020
2010 – 2019
- 2019
- [c2]Min Zeng, Chengqian Lu, Fuhao Zhang, Zhangli Lu, Fang-Xiang Wu, Yaohang Li, Min Li:
LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques. BIBM 2019: 577-582 - 2018
- [j2]Jin Liu, Yi Pan, Min Li, Ziyue Chen, Lu Tang, Chengqian Lu, Jianxin Wang:
Applications of deep learning to MRI images: A survey. Big Data Min. Anal. 1(1): 1-18 (2018) - [j1]Chengqian Lu, Mengyun Yang, Feng Luo, Fang-Xiang Wu, Min Li, Yi Pan, Yaohang Li, Jianxin Wang:
Prediction of lncRNA-disease associations based on inductive matrix completion. Bioinform. 34(19): 3357-3364 (2018) - 2016
- [c1]Wei Lan, Jianxin Wang, Min Li, Chengqian Lu, Fang-Xiang Wu, Yi Pan:
Predicting microRNA-environmental factor interactions based on bi-random walk and multi-label learning. BIBM 2016: 27-32
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