Chengqian Lu
Orcid: 0000-0001-9201-6912Affiliations:
- Central South University, Changsha, Hunan, China
According to our database1,
Chengqian Lu
authored at least 16 papers
between 2016 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on orcid.org
On csauthors.net:
Bibliography
2024
Earth Sci. Informatics, October, 2024
2023
LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism.
Bioinform., December, 2023
CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features.
Briefings Bioinform., January, 2023
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network.
Briefings Bioinform., January, 2023
GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation.
Briefings Bioinform., January, 2023
2022
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding.
Briefings Bioinform., 2022
2021
IEEE J. Biomed. Health Informatics, 2021
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Heterogeneous graph inference with matrix completion for computational drug repositioning.
Bioinform., 2021
Improving circRNA-disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks.
Bioinform., 2021
2020
HGIMC: heterogeneous graph inference with matrix completion for computational drug repositioning.
Dataset, November, 2020
IEEE J. Biomed. Health Informatics, 2020
2019
LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
Bioinform., 2018
2016
Predicting microRNA-environmental factor interactions based on bi-random walk and multi-label learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016