Duc-Hau Le
Orcid: 0000-0002-4951-5916
According to our database1,
Duc-Hau Le
authored at least 27 papers
between 2011 and 2023.
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Bibliography
2023
A Hybrid Model Integrating Multi-Omic and Topological Information of PPI Network for Drug Synergism Prediction.
Proceedings of the International Conference on Computing and Communication Technologies, 2023
2022
Integrating Molecular Graph Data of Drugs and Multiple -Omic Data of Cell Lines for Drug Response Prediction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
2020
Int. J. Intell. Inf. Database Syst., 2020
RWRMTN: a tool for predicting disease-associated microRNAs based on a microRNA-target gene network.
BMC Bioinform., 2020
Proceedings of the 12th International Conference on Knowledge and Systems Engineering, 2020
An investigation of cancer cell line-based drug response prediction methods on patient data.
Proceedings of the 12th International Conference on Knowledge and Systems Engineering, 2020
2018
autoHGPEC: Automated prediction of novel disease-gene and disease-disease associations and evidence collection based on a random walk on heterogeneous network.
F1000Research, 2018
Proceedings of the Ninth International Symposium on Information and Communication Technology, 2018
Multi-Task Regression Learning for Prediction of Response Against a Panel of Anti-Cancer Drugs in Personalized Medicine.
Proceedings of the 1st International Conference on Multimedia Analysis and Pattern Recognition, 2018
2017
HGPEC: a Cytoscape app for prediction of novel disease-gene and disease-disease associations and evidence collection based on a random walk on heterogeneous network.
BMC Syst. Biol., 2017
Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.
BMC Bioinform., 2017
An ensemble learning-based method for prediction of novel disease-microRNA associations.
Proceedings of the 9th International Conference on Knowledge and Systems Engineering, 2017
Meta-analysis of whole-transcriptome data for prediction of novel genes associated with autism spectrum disorder.
Proceedings of the 8th International Conference on Computational Systems-Biology and Bioinformatics, 2017
2016
Vietnam. J. Comput. Sci., 2016
Significant path selection improves the prediction of novel drug-target interactions.
Proceedings of the Seventh Symposium on Information and Communication Technology, 2016
Proceedings of the 2016 IEEE RIVF International Conference on Computing & Communication Technologies, 2016
2015
Comput. Biol. Chem., 2015
A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.
Algorithms Mol. Biol., 2015
Towards more realistic machine learning techniques for prediction of disease-associated genes.
Proceedings of the Sixth International Symposium on Information and Communication Technology, 2015
2014
A Comparative Study of Classification-Based Machine Learning Methods for Novel Disease Gene Prediction.
Proceedings of the Knowledge and Systems Engineering, 2014
2013
Neighbor-favoring weight reinforcement to improve random walk-based disease gene prioritization.
Comput. Biol. Chem., 2013
A coherent feedforward loop design principle to sustain robustness of biological networks.
Bioinform., 2013
2012
GPEC: A Cytoscape plug-in for random walk-based gene prioritization and biomedical evidence collection.
Comput. Biol. Chem., 2012
2011
NetDS: a Cytoscape plugin to analyze the robustness of dynamics and feedforward/feedback loop structures of biological networks.
Bioinform., 2011
Bioinform., 2011