Chengqian Lu

Orcid: 0000-0001-9201-6912

Affiliations:
  • Central South University, Changsha, Hunan, China


According to our database1, Chengqian Lu authored at least 15 papers between 2016 and 2023.

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Bibliography

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
Deep Matrix Factorization Improves Prediction of Human CircRNA-Disease Associations.
IEEE J. Biomed. Health Informatics, 2021

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.
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

Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion.
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
Prediction of lncRNA-disease associations based on inductive matrix completion.
Bioinform., 2018

Applications of deep learning to MRI images: A survey.
Big Data Min. Anal., 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


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