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Duyen Thi Do

Showing results (1-10 of 12) with videos related to

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Genomics|January 29, 2020
Using extreme gradient boosting to identify origin of replication in Saccharomyces cerevisiae via hybrid featuresDuyen Thi Do, Nguyen Quoc Khanh Le
Briefings in Bioinformatics|July 3, 2020
Using deep neural networks and biological subwords to detect protein S-sulfenylation sitesDuyen Thi Do, Thanh Quynh Trang Le, Nguyen Quoc Khanh Le
Gene|April 13, 2021
A sequence-based prediction of Kruppel-like factors proteins using XGBoost and optimized featuresNguyen Quoc Khanh Le, Duyen Thi Do, Trinh-Trung-Duong Nguyen, et al.
Cytotechnology|August 24, 2016
Novel regulations of MEF2-A, MEF2-D, and CACNA1S in the functional incompetence of adipose-derived mesenchymal stem cells by induced indoxyl sulfate in chronic kidney diseaseDuyen Thi Do, Nam Nhut Phan, Chih-Yang Wang, et al.
Scientific Reports|August 4, 2022
Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approachDuyen Thi Do, Ming-Ren Yang, Luu Ho Thanh Lam, et al.
Cancers|July 27, 2022
A Radiomics-Based Machine Learning Model for Prediction of Tumor Mutational Burden in Lower-Grade GliomasLuu Ho Thanh Lam, Ngan Thy Chu, Thi-Oanh Tran, et al.
Computational and Structural Biotechnology Journal|May 6, 2024
Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strainsDuyen Thi Do, Ming-Ren Yang, Tran Nam Son Vo, et al.
Journal of Personalized Medicine|September 18, 2020
XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype GlioblastomaNguyen Quoc Khanh Le, Duyen Thi Do, Fang-Ying Chiu, et al.
Computers in Biology and Medicine|March 18, 2021
Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRINguyen Quoc Khanh Le, Truong Nguyen Khanh Hung, Duyen Thi Do, et al.
International Journal of Molecular Sciences|December 2, 2020
A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes IdentificationNguyen Quoc Khanh Le, Duyen Thi Do, Truong Nguyen Khanh Hung, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Genomics|January 29, 2020
Using extreme gradient boosting to identify origin of replication in Saccharomyces cerevisiae via hybrid featuresDuyen Thi Do, Nguyen Quoc Khanh Le
Briefings in Bioinformatics|July 3, 2020
Using deep neural networks and biological subwords to detect protein S-sulfenylation sitesDuyen Thi Do, Thanh Quynh Trang Le, Nguyen Quoc Khanh Le
Gene|April 13, 2021
A sequence-based prediction of Kruppel-like factors proteins using XGBoost and optimized featuresNguyen Quoc Khanh Le, Duyen Thi Do, Trinh-Trung-Duong Nguyen, et al.
Cytotechnology|August 24, 2016
Novel regulations of MEF2-A, MEF2-D, and CACNA1S in the functional incompetence of adipose-derived mesenchymal stem cells by induced indoxyl sulfate in chronic kidney diseaseDuyen Thi Do, Nam Nhut Phan, Chih-Yang Wang, et al.
Scientific Reports|August 4, 2022
Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approachDuyen Thi Do, Ming-Ren Yang, Luu Ho Thanh Lam, et al.
Cancers|July 27, 2022
A Radiomics-Based Machine Learning Model for Prediction of Tumor Mutational Burden in Lower-Grade GliomasLuu Ho Thanh Lam, Ngan Thy Chu, Thi-Oanh Tran, et al.
Computational and Structural Biotechnology Journal|May 6, 2024
Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strainsDuyen Thi Do, Ming-Ren Yang, Tran Nam Son Vo, et al.
Journal of Personalized Medicine|September 18, 2020
XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype GlioblastomaNguyen Quoc Khanh Le, Duyen Thi Do, Fang-Ying Chiu, et al.
Computers in Biology and Medicine|March 18, 2021
Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRINguyen Quoc Khanh Le, Truong Nguyen Khanh Hung, Duyen Thi Do, et al.
International Journal of Molecular Sciences|December 2, 2020
A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes IdentificationNguyen Quoc Khanh Le, Duyen Thi Do, Truong Nguyen Khanh Hung, et al.
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