Nguyen-Quoc-Khanh Le

Orcid: 0000-0003-4896-7926

According to our database1, Nguyen-Quoc-Khanh Le authored at least 39 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
VF-Pred: Predicting virulence factor using sequence alignment percentage and ensemble learning models.
Comput. Biol. Medicine, January, 2024

2023
A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas.
Medical Biol. Eng. Comput., October, 2023

Diffusion-tensor imaging and dynamic susceptibility contrast MRIs improve radiomics-based machine learning model of MGMT promoter methylation status in glioblastomas.
Biomed. Signal Process. Control., September, 2023

Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection.
Briefings Bioinform., September, 2023

Development and Validation of CT-Based Radiomics Signature for Overall Survival Prediction in Multi-organ Cancer.
J. Digit. Imaging, June, 2023

Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding.
Briefings Bioinform., January, 2023

Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug-Food Interactions from Chemical Structures.
Sensors, 2023

Predicting emerging drug interactions using GNNs.
Nat. Comput. Sci., 2023

An MRI-based radiomics signatures for overall survival prediction of gliomas patients.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Predicting Tumor Mutational Burden and Survival in Head and Neck Squamous Cancer Patients Using Machine Learning and Bioinformatics Approaches.
Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

A Sequence-Based Prediction Model of Vesicular Transport Proteins Using Ensemble Deep Learning.
Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

2022
Self-Organizing Double Function-Link Fuzzy Brain Emotional Control System Design for Uncertain Nonlinear Systems.
IEEE Trans. Syst. Man Cybern. Syst., 2022

An Extensive Examination of Discovering 5-Methylcytosine Sites in Genome-Wide DNA Promoters Using Machine Learning Based Approaches.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Identifying SNARE Proteins Using an Alignment-Free Method Based on Multiscan Convolutional Neural Network and PSSM Profiles.
J. Chem. Inf. Model., 2022

4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller.
Int. J. Fuzzy Syst., 2022

BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection.
Comput. Biol. Chem., 2022

mCNN-ETC: identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences.
Briefings Bioinform., 2022

Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems.
Appl. Intell., 2022

Prediction of Protein-Protein Interactions through Deep Learning Based on Sequence Feature Extraction and Interaction Network.
Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2022

2021
Prediction of FMN Binding Sites in Electron Transport Chains Based on 2-D CNN and PSSM Profiles.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels.
Comput. Biol. Medicine, 2021

Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI.
Comput. Biol. Medicine, 2021

FAD-BERT: Improved prediction of FAD binding sites using pre-training of deep bidirectional transformers.
Comput. Biol. Medicine, 2021

A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information.
Briefings Bioinform., 2021

Using deep neural networks and biological subwords to detect protein S-sulfenylation sites.
Briefings Bioinform., 2021

2020
A New Self-Organizing Fuzzy Cerebellar Model Articulation Controller for Uncertain Nonlinear Systems Using Overlapped Gaussian Membership Functions.
IEEE Trans. Ind. Electron., 2020

DeepETC: A deep convolutional neural network architecture for investigating and classifying electron transport chain's complexes.
Neurocomputing, 2020

2019
SNARE-CNN: a 2D convolutional neural network architecture to identify SNARE proteins from high-throughput sequencing data.
PeerJ Comput. Sci., 2019

Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins.
J. Bioinform. Comput. Biol., 2019

Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles.
Comput. Methods Programs Biomed., 2019

ET-GRU: using multi-layer gated recurrent units to identify electron transport proteins.
BMC Bioinform., 2019

2018
Incorporating post translational modification information for enhancing the predictive performance of membrane transport proteins.
Comput. Biol. Chem., 2018

DeepEfflux: a 2D convolutional neural network model for identifying families of efflux proteins in transporters.
Bioinform., 2018

2017
Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.
J. Comput. Chem., 2017

2016
Incorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins.
BMC Bioinform., 2016

Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.
BMC Bioinform., 2016

Using Deep Learning with Position Specific Scoring Matrices to Identify Efflux Proteins in Membrane and Transport Proteins.
Proceedings of the 16th IEEE International Conference on Bioinformatics and Bioengineering, 2016


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