黎阮國慶(0 0) 副教授

Email
khanhlee@tmu.edu.tw
現   職
人工智慧醫療碩士在職專班 副教授

學經歷

學 歷

畢業學校與學位[修業時間]
元智大學資訊工程學系博士班 博士
2014/02~2018/01
元智大學資訊工程學系 碩士
2012/02~2014/01
Da Lat UniversityDepartment of Information Technology 學士
2005/09~2010/01

本校學術經歷

任職單位與職稱[起迄時間]
人工智慧醫療碩士在職專班副教授
2023/02/01~
人工智慧醫療碩士在職專班助理教授
2019/08/05~2023/01/31

本校兼職教學行政經歷

服務單位與職稱[起迄時間]
國際醫學研究碩士學位學程助理教授
2020/11/01 ~
國際醫學研究博士學位學程助理教授
2020/11/01 ~

其它經歷

任職單位與職稱[起迄時間]
Nanyang Technological University, SingaporeResearch Fellow
2018/08/06~2019/08/02
VNG Corporation, VietnamAssociate QC Engineer
2010/07/05~2012/02/07

專長與研究領域

學門領域
學術專長

論文著作

清冊下載


1. 2024 Nguyen VN,Ho TT,Doan TD,Le NQK. Using a hybrid neural network architecture for DNA sequence representation: A study on N4-methylcytosine sites . Computers in Biology and Medicine .2024

2. 2024 Tran TO,Le NQK. Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing . Computers in Biology and Medicine .2024 ;(174):108408

3. 2023 Singh S,Le NQK,Wang C. VF-Pred: Predicting virulence factor using sequence alignment percentage and ensemble learning models . Computers in Biology and Medicine .2023 ;(168):107662

4. 2023 Zheng Z,Le NQK,Chua MCH. MaskDNA-PGD: An innovative deep learning model for detecting DNA methylation by integrating mask sequences and adversarial PGD training as a data augmentation method . Chemometrics and Intelligent Laboratory Systems .2023 ;(232):104715

5. 2023 Yuan Y,Chen K,Yu Y,Le NQK,Chua MCH. Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding . Briefings in Bioinformatics .2023 ;(24):1-10

6. 2023 Le VH,Kha QH,Minh TNT,Nguyen VH,Le VL,Le NQK. Development and validation of CT-based radiomics signature for overall survival prediction in multi-organ cancer . Journal of Digital Imaging .2023 ;(36):911-922

7. 2023 Tran TO,Vo TH,Lam LHT,Le NQK. ALDH2 as a potential stem cell-related biomarker in lung adenocarcinoma: Comprehensive multi-omics analysis . Computational and Structural Biotechnology Journal .2023 ;(21):1921-1929

8. 2023 Huynh QTV,Minh TTT,Doan KK,Ho BT,Shen SC,Trinh TH, Vo TH, Le NQK, Nguyen NTK. The Distribution of Autoantibodies by Age Group in Children with Type 1 Diabetes versus Type 2 Diabetes in Southern Vietnam . Journal of Clinical Medicine .2023 ;(12):1420

9. 2023 Kha QH,Le VH,Hung TNK,Nguyen NTK,Le NQK. Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug–Food Interactions from Chemical Structures . Sensors .2023 ;(23):3962

10. 2023 Nguyen HS,Ho DKN,Nguyen NN,Tran HM,Tam KW,Le NQK. Predicting EGFR Mutation Status in Non–Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis . Academic Radiology .2023

11. 2023 Minh TNT,Le VH,Le NQK. Diffusion-tensor imaging and dynamic susceptibility contrast MRIs improve radiomics-based machine learning model of MGMT promoter methylation status in glioblastomas . Biomedical Signal Processing and Control .2023 ;(86):105122

12. 2023 Le NQK. Leveraging transformers-based language models in proteome bioinformatics . Proteomics .2023

13. 2023 Le VH,Minh TNT,Kha QH,Le NQK. A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas . Medical & Biological Engineering & Computing .2023 ;(61):2699-2712

14. 2023 Tran TO,Lam LHT,Le NQK. Hyper-methylation of ABCG1 as an epigenetics biomarker in non-small cell lung cancer . Functional & Integrative Genomics .2023 ;(23)

15. 2023 Dang HH,Ta HDK,Nguyen TTT,Wang CY,Lee KH,Le NQK. Identification of a Novel Eight-Gene Risk Model for Predicting Survival in Glioblastoma: A Comprehensive Bioinformatic Analysis . Cancers .2023 ;(15)

16. 2023 Le NQK,Li W,Cao Y. Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection . Briefings in Bioinformatics .2023 ;(24)

17. 2023 Le NQK,Xu L. Optimizing Hyperparameter Tuning in Machine Learning to Improve the Predictive Performance of Cross-Species N6-Methyladenosine Sites . ACS Omega .2023 ;(8):39420-39426

18. 2023 Tran TO,Vo TH,Le NQK. Omics-based deep learning approaches for lung cancer decision-making and therapeutics development . Briefings in Functional Genomics .2023

19. 2022 Le NQK,Ho QT. Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes . Methods .2022 ;(204):199-226

20. 2022 Hung TNK,Le NQK,Le NH,Tuan LV,Nguyen TP,Thi C, Kang JH. An AI-based prediction model for drug-drug interactions in osteoporosis and Paget's diseases from SMILES . Molecular Informatics .2022 ;(41):2100264

21. 2022 Huynh QTV,Le NQK,Huang SY,Ho BT,Vu TH,Pham HTM, Pham AL, Hou JW, Nguyen NTK, Chen YC. Development and Validation of Clinical Diagnostic Model for Girls with Central Precocious Puberty: Machine-learning Approaches . PLOS ONE .2022 ;(17):e0261965

22. 2022 Vo TH,Nguyen NTK,Kha QH,Le NQK. On the road to explainable AI in drug-drug interactions prediction: a systematic review . Computational and Structural Biotechnology Journal .2022 ;(20):2112-2123

23. 2022 Huynh TT,Lin CM,Pham DH,Nguyen NP,Le NQK,Vu MT, Vu VP, Chao F. 4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller . International Journal of Fuzzy Systems .2022 ;(24):pages2946-2968

24. 2022 Vy VPT,Yao MMS,Le NQK,Chan WP. Machine Learning Algorithm for Distinguishing Ductal Carcinoma In Situ from Invasive Breast Cancer . Cancers .2022 ;(14):2437

25. 2022 Hung TNK,Vy VPT,Tri NM,Hoang LN,Tuan LV,Ho QT, Le NQK, Kang JH. Automatic Detection of Meniscus Tears Using Backbone Convolutional Neural Networks on Knee MRI . Journal of Magnetic Resonance Imaging .2022

26. 2022 Lam LHT,Do DT,Diep DTN,Nguyet DLN,Truong QD,Tri TT, Thanh HN, Le NQK. Molecular subtypes classification of low-grade gliomas patients using MRI-based radiomics and machine learning . NMR in Biomedicine .2022 ;(35):e4792

27. 2022 Le NQK,Ho QT,Nguyen VN,Chang JS. BERT-Promoter: an improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection . Computational Biology and Chemistry .2022 ;(99):107732

28. 2022 Lam LHT,Chu NT,Tran TO,Do DT,Le NQK. A radiomics-based machine learning model for prediction of tumor mutational burden in lower-grade gliomas . Cancers .2022 ;(14):3492

29. 2022 Dang HH,Ta HDK,Nguyen TTT,Anuraga G,Wang CY,Lee KH, Le NQK. Prospective role and immunotherapeutic targets of sideroflexin protein family in lung adenocarcinoma: evidence from bioinformatics validation . Functional & Integrative Genomics .2022 ;(22):pages1057-1072

30. 2022 Do DT,Yang MR,Lam LHT,Le NQK,Wu YW. Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach . Scientific Reports .2022 ;(12):13412

31. 2022 Liu CM,Ta VD,Le NQK,Tadesse DA,Shi C. Deep Neural Network Framework Based on Word Embedding for Protein Glutarylation Sites Prediction . Life .2022 ;(12):1213

32. 2022 Lesmana MHS,Le NQK,Chiu WC,Chung KH,Wang CY,Irham LM, Chung MH. Genomic-Analysis-Oriented Drug Repurposing in the Search for Novel Antidepressants . Biomedicines .2022 ;(10):1947

33. 2022 Ho DKN,Lee YC,Chiu WC,Shen Y,Yao CY,Chu HK, Chu WT, Le NQK, Nguyen HT, Su HY, Chang JS. COVID-19 and Virtual Nutrition: Integrating Digital Food Models for Interactive Portion-Size Education . Nutrients .2022 ;(14):3313

34. 2022 Kha QH,Tran TO,Nguyen TTD,Nguyen VN,Than K,Le NQK. An interpretable deep learning model for classifying adaptor protein complexes from sequence information . Methods .2022 ;(207):90-96

35. 2022 Kha QH,Ho QT,Le NQK. Identifying SNARE Proteins Using an Alignment-Free Method Based on Multiscan Convolutional Neural Network and PSSM Profiles . Journal of Chemical Information and Modeling .2022 ;(62):4820-4826

36. 2022 Zhao Z,Gui J,Yao A,Le NQK,Chua MCH. Improved Prediction Model of Protein and Peptide Toxicity by Integrating Channel Attention into a Convolutional Neural Network and Gated Recurrent Units . ACS Omega .2022 ;(7):40569-40577

37. 2022 Hsu JC,Nguyen PA,Phuc PT,Lo TC,Hsu MH,Hsieh MS, Le NQK, Cheng CT, Chang TH, Chen CY. Development and Validation of Novel Deep-Learning Models Using Multiple Data Types for Lung Cancer Survival . Cancers .2022 ;(14):5562

38. 2021 Le NQK,Ho QT,Nguyen TTD,Ou YY. A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information . Briefings in Bioinformatics .2021 ;(22):bbab005

39. 2021 Ho QT,Nguyen TTD,Le NQK,Ou YY. FAD-BERT: Improved Prediction of FAD Binding Sites Using Pre-training of Deep Bidirectional Transformers . Computers in Biology and Medicine .2021 ;(131):104258

40. 2021 Le NQK,Truong NKH,Do DT,Luu HTL,Luong HD,Huynh TT. Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI . Computers in Biology and Medicine .2021 ;(132):104320

41. 2021 Le NQK,Do DT,Nguyen TTD,Le QA. A sequence-based prediction of Kruppel-like factors proteins using XGBoost and optimized features . Gene .2021 ;(787):145643

42. 2021 Chiu FY,Le NQK,Chen CY. A Multiparametric MRI-Based Radiomics Analysis to Efficiently Classify Tumor Subregions of Glioblastoma: A Pilot Study in Machine Learning . Journal of Clinical Medicine .2021 ;(10):2030

43. 2021 Nguyen TTD,Tran TA,Le NQK,Pham DM,Ou YY. An extensive examination of discovering 5-Methylcytosine Sites in Genome-Wide DNA Promoters using machine learning based approaches . IEEE/ACM Transactions on Computational Biology and Bioinformatics .2021

44. 2021 Huynh TT,Lin CM,Le NQK,Vu MT,Nguyen NP,Chao F. Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems . Applied Intelligence .2021

45. 2021 Le VH,Kha QH,Truong NKH,Le NQK. Risk Score Generated from CT-Based Radiomics Signatures for Overall Survival Prediction in Non-Small Cell Lung Cancer . Cancers .2021 ;(13):3616

46. 2021 Le NQK,Kha QH,Nguyen VH,Chen YC,Cheng SJ,Chen CY. Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer . International Journal of Molecular Sciences .2021 ;(22):9254

47. 2021 Dang HH,Ta HDK,Nguyen TTT,Anuraga G,Wang CY,Lee KH, Le NQK. Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis . Biomedicines .2021 ;(9):1144

48. 2021 Ho QT,Le NQK,Ou YY. 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 in Bioinformatics .2021

49. 2021 Hsu JBK,Lee TY,Cheng SJ,Lee GA,Chen YC,Le NQK, Huang SW, Kuo DP, Li YT, Chang TH, Chen CY. Identification of Differentially Expressed Genes in Different Glioblastoma Regions and Their Association with Cancer Stem Cell Development and Temozolomide Response . Journal of Personalized Medicine .2021 ;(11):1047

50. 2021 Kha QH,Le VH,Hung TNK,Le NQK. Development and Validation of an Efficient MRI Radiomics Signature for Improving the Predictive Performance of 1p/19q Co-Deletion in Lower-Grade Gliomas . Cancers .2021 ;(13):5398

51. 2021 Le NQK. Potential of deep representative learning features to interpret the sequence information in proteomics . PROTEOMICS .2021 ;(22):1-2

52. 2021 Dang LH,Dung NT,Quang LX,Hung LQ,Le NH,Le NTN, Diem NT, Nga NTT, Hung SH, Le NQK. Machine learning-based prediction of drug-drug interactions for histamine antagonist using hybrid chemical features . Cells .2021 ;(10):3092

53. 2021 Tng SS,Le NQK,Yeh HY,Chua MCH. Improved Prediction Model of Protein Lysine Crotonylation Sites Using Bidirectional Recurrent Neural Networks . Journal of Proteome Research .2021 ;(21):256-273

54. 2021 Nguyen TTD,Trinh VN,Le NQK,Ou YY. Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model . Plant Molecular Biology .2021 ;(107):533-542

55. 2021 Nguyen TTD,Le NQK,Tran TA,Pham DM,Ou YY. Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels . Computers in Biology and Medicine .2021 ;(130):104212

56. 2020 Do DT,Le NQK. Using extreme gradient boosting to identify origin of replication in Saccharomyces cerevisiae via hybrid features . Genomics .2020 ;(112):2445-2451

57. 2020 Do DT,Le TQT,Le NQK. Using deep neural networks and biological sub-words to detect protein S-sulfenylation sites . Briefings in Bioinformatics .2020 ;(22)

58. 2020 Nguyen TTD,Le NQK,Phan DV,Ho QT,Ou YY. Using language representation learning approach to efficiently identify protein complex categories in electron transport chain . Molecular Informatics .2020 ;(39):2000033

59. 2020 Nguyen TTD,Ho QT,Le NQK,Phan DV,Ou YY. Use Chou's 5-steps rule with different word embedding types to boost performance of electron transport protein prediction model . IEEE/ACM Transactions on Computational Biology and Bioinformatics .2020

60. 2020 Le NQK,Do DT,Chiu FY,Yapp EKY,Yeh HY,Chen CY. XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma . Journal of Personalized Medicine .2020 ;(10)

61. 2020 Sua JN,Lim SY,Yulius MH,Su X,Yapp EKY,Le NQK, Yeh HY, Chua MCH. Incorporating convolutional neural networks and sequence graph transform for identifying multilabel protein Lysine PTM sites . Chemometrics and Intelligent Laboratory Systems .2020 ;(206):104171

62. 2020 Luu HTL,Le NH,Le VT,Ho TB,Truong NKH,Nguyen NTK, Luong HD, Le NQK. Machine Learning Model for Identifying Antioxidant Proteins Using Features Calculated from Primary Sequences . Biology .2020 ;(9(10))

63. 2020 Hsu JBK,Lee GA,Chang TH,Huang SW,Le NQK,Chen YC, Kuo DP, Li YT, Chen CY. Radiomic Immunophenotyping of GSEA-Assessed Immunophenotypes of Glioblastoma and Its Implications for Prognosis: A Feasibility Study . Cancers .2020 ;(12(10))

64. 2020 Nguyen TTD,Le NQK,Ho QT,Phan DV,Ou YY. TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings . BMC Medical Genomics .2020 ;(13)

65. 2020 Le NQK,Do DT,Truong NKH,Luu HTL,Huynh TT,Nguyen NTK. A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification . International Journal of Molecular Sciences .2020 ;(21(23))

66. 2020 Huynh TT,Lin CM,Le TL,Le NQK,Vu VP,Chao F. Self-Organizing Double Function-Link Fuzzy Brain Emotional Control System Design for Uncertain Nonlinear Systems . IEEE Transactions on Systems, Man, and Cybernetics: Systems .2020

67. 2019 Le NQK,Nguyen BP. Prediction of FMN Binding Sites in Electron Transport Chains based on 2-D CNN and PSSM Profiles . IEEE/ACM Transactions on Computational Biology and Bioinformatics .2019

68. 2019 Le NQK. Fertility-GRU: Identifying Fertility-Related Proteins by Incorporating Deep-Gated Recurrent Units and Original Position-Specific Scoring Matrix Profiles . Journal of Proteome Research .2019 ;(18):3503-3511

69. 2019 Le NQK,Yapp EKY,Yeh HY. ET-GRU: using multi-layer gated recurrent units to identify electron transport proteins . BMC Bioinformatics .2019 ;(20):377-377

70. 2019 Le NQK,Huynh TT,Yapp EKY,Yeh HY. Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles . Computer Methods and Programs in Biomedicine .2019 ;(177):81-88

71. 2019 Do DT,Le NQK. A sequence-based approach for identifying recombination spots in Saccharomyces cerevisiae by using hyper-parameter optimization in FastText and support vector machine . Chemometrics and Intelligent Laboratory Systems .2019 ;(194):103855-103855

72. 2019 Le NQK,Ho QT,Yapp EKY,Ou YY,Yeh HY. DeepETC: A deep convolutional neural network architecture for investigating and classifying electron transport chain's complexes . Neurocomputing .2019 ;(375):71-79

73. 2019 Le NQK,Yapp EKY,Nagasundaram N,Chua MCH,Yeh HY. Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture . Computational and Structural Biotechnology Journal .2019 ;(17):1245-1254

74. 2019 Le NQK,Yapp EKY,Nagasundaram N,Yeh HY. Classifying Promoters by Interpreting the Hidden Information of DNA Sequences via Deep Learning and Combination of Continuous FastText N-Grams . Frontiers in Bioengineering and Biotechnology .2019 ;(7)

75. 2019 Le NQK,Huynh TT. Identifying SNAREs by Incorporating Deep Learning Architecture and Amino Acid Embedding Representation . Frontiers in Physiology .2019

76. 2019 Nguyen QH,Nguyen-Vo TH,Le NQK,Do TTT,Rahardja S,Nguyen BP. iEnhancer-ECNN: Identifying enhancers and their strength using Ensemble of Convolutional Neural Networks . BMC Genomics .2019 ;(20):951

77. 2019 Le NQK,Nguyen QH,Chen X,Rahardja S,Nguyen BP. Classification of Adaptor Proteins using Recurrent Neural Networks and PSSM Profiles . BMC Genomics .2019 ;(20):966

78. 2019 Huynh TT,Lin CM,Le TL,Cho HY,Pham TTT,Le NQK, Chao Fei. A New Self-Organizing Fuzzy Cerebellar Model Articulation Controller for Uncertain Nonlinear Systems Using Overlapped Gaussian Membership Functions . IEEE Transactions on Industrial Electronics .2019

79. 2019 Nagarajan N,Yapp EKY,Le NQK,Kamaraj B,Al-Subaie AM,Yeh HY. Application of computational biology and artificial intelligence technologies in cancer precision drug discovery . BioMed Research International .2019 ;(2019)

80. 2019 Tan KK,Le NQK,Yeh HY,Chua MCH. Ensemble of Deep Recurrent Neural Networks for Identifying Enhancers via Dinucleotide Physicochemical Properties . Cells .2019 ;(8):767

81. 2019 Nguyen TTD,Le NQK,Kusuma RMI,Ou YY. Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network . Journal of Molecular Graphics and Modelling .2019 ;(92):86-93

82. 2019 Le NQK. iN6-methylat (5-step): Identifying DNA N6-methyladenine sites in rice genome using continuous bag of nucleobases via Chou's 5-step rule . Molecular Genetics and Genomics .2019 ;(294):1173-1182

83. 2019 Nguyen TTD,Le NQK,Ho QT,Phan DV,Ou YY. Using word embedding technique to efficiently represent protein sequences for identifying substrate specificities of transporters . Analytical Biochemistry .2019 ;(577):73-81

84. 2019 Nagasundaram N,Yapp EKY,Le NQK,Yeh HY. In silico screening of sugar alcohol compounds to inhibit viral matrix protein VP40 of Ebola virus . Molecular Biology Reports .2019 ;(46):3315-3324

85. 2019 Le NQK,Yapp EKY,Ou YY,Yeh HY. iMotor-CNN: Identifying molecular functions of cytoskeleton motor proteins using 2D convolutional neural network via Chou's 5-step rule . Analytical Biochemistry .2019 ;(575):17-26

86. 2019 Le NQK,Yapp EKY,Ho QT,Nagasundaram N,Ou YY,Yeh HY. iEnhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding . Analytical Biochemistry .2019 ;(571):53-61

87. 2019 Le NQK,Ho QT,Ou YY. Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins . Journal of Bioinformatics and Computational Biology .2019 ;(17):195005

88. 2019 Le NQK,Nguyen VN. SNARE-CNN: a 2D convolutional neural network architecture to identify SNARE proteins from high-throughput sequencing data . PeerJ Computer Science .2019 ;(5):e177

89. 2018 Le NQK,Sandag GA,Ou YY. Incorporating post translational modification information for enhancing the predictive performance of membrane transport proteins . Computational Biology and Chemistry .2018 ;(77):251-260

90. 2018 Le NQK,Ho QT,Ou YY. Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks . Analytical Biochemistry .2018 ;(555):33-41

91. 2018 Taju SW,Nguyen TTD,Le NQK,Kusuma RMI,Ou YY. DeepEfflux: a 2D convolutional neural network model for identifying families of efflux proteins in transporters . Bioinformatics .2018 ;(34):3111-3117

92. 2017 Le NQK,Ho QT,Ou YY. Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins . Journal of Computational Chemistry .2017 ;(38):2000-2006

93. 2017 Le NQK,Nguyen TTD,Ou YY. Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties . Journal of Molecular Graphics and Modelling .2017 ;(73):166-178

94. 2016 Le NQK,Ou YY. Incorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins . BMC Bioinformatics .2016 ;(17)

95. 2016 Le NQK,Ou YY. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs . BMC Bioinformatics .2016 ;(17):298-298


1. 2022 Le NQK,Kha QH. Prediction of Protein-Protein Interactions through Deep Learning Based on Sequence Feature Extraction and Interaction Network . 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) .2022

研究計畫

計畫名稱
113 運用圖變換器和深度表示學習預測基於序列的蛋白質功能(3/3)
補助單位
國家科學及技術委員會

計畫名稱
113 貴機構依本會「補助國內研究生出席國際學術會議」申請費用補助案(研究生:細胞治療與再生醫學國際博士學位學程博士班Tran Thi Oanh君),業經核定,請查照辦理。
補助單位
國家科學及技術委員會

計畫名稱
112 貴機構依本會「補助國內研究生出席國際學術會議」申請費用補助案(研究生:細胞治療與再生醫學國際博士學位學程博士班Nguyen Mai Hanh君),業經核定,請查照辦理。
補助單位
國家科學及技術委員會

計畫名稱
112 貴機構依本會「補助國內研究生出席國際學術會議」申請費用補助案(研究生:國際醫學研究博士學位學程博士班LE HUU NHAT MINH君),業經核定,請查照辦理。
補助單位
國家科學及技術委員會

計畫名稱
112 運用圖變換器和深度表示學習預測基於序列的蛋白質功能(2/3)
補助單位
國家科學及技術委員會

計畫名稱
112 貴機構依本會「補助國內研究生出席國際學術會議」申請費 用補助案(研究生:國際醫學研究博士學位學程博士班KHA QU ANG HIEN君),業經核定,請查照辦理。
補助單位
科技部

計畫名稱
112 貴機構依本會「補助國內研究生出席國際學術會議」申請費用補助案(研究生:國際醫學研究博士學位學程博士班KHA QUANG HIEN君),業經核定,請查照辦理。
補助單位
國家科學及技術委員會

計畫名稱
111 DeepNLP-DNA:運用深度編解碼架構及二維卷積神經網路以分析去氧核糖核酸序列表現之預先訓練自然語言處理模型研究(2/2)
補助單位
國家科學及技術委員會

計畫名稱
111 運用圖變換器和深度表示學習預測基於序列的蛋白質功能(1/3)
補助單位
國家科學及技術委員會

計畫名稱
111 貴機構依本部「補助國內研究生出席國際學術會議」申請 費用補助案(研究生:細胞治療與再生醫學國際博士學位學 程Tran Thi Oanh君),業經核定,請查照辦理。
補助單位
科技部

計畫名稱
111 貴機構依本會「補助國內研究生出席國際學術會議」申請費用補助案(研究生:國際醫學研究博士學位學程LE HUU NHAT MINH君)
補助單位
國家科學及技術委員會

計畫名稱
110 DeepNLP-DNA:運用深度編解碼架構及二維卷積神經網路以分析去氧核糖核酸序列表現之預先訓練自然語言處理模型研究(1/2)
補助單位
科技部

計畫名稱
108 新聘教師研究補助
補助單位
臺北醫學大學