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ORCIDChee Keong Kwoh 0001
Chee-Keong Kwoh 0001 – Kwoh Chee Keong 0001
Person information
- affiliation: Nanyang Technological University, School of Computer Engineering, Singapore
- affiliation (PhD 1995): University of London, Imperial College of Science, Technology and Medicine, UK
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2020 – today
- 2024
[j111]Lin-Xuan Hou
, Hai-Cheng Yi, Zhu-Hong You, Shi-Hong Chen, Jia Zheng, Chee Keong Kwoh:
MathEagle: Accurate prediction of drug-drug interaction events via multi-head attention and heterogeneous attribute graph learning. Comput. Biol. Medicine 177: 108642 (2024)- [j110]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
Contrastive Domain Adaptation for Time-Series Via Temporal Mixup. IEEE Trans. Artif. Intell. 5(3): 1185-1194 (2024) - [j109]Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li:
Self-Supervised Autoregressive Domain Adaptation for Time Series Data. IEEE Trans. Neural Networks Learn. Syst. 35(1): 1341-1351 (2024) - 2023
- [j108]Xiaolei Yu, Zhibin Zhao, Xingwu Zhang, Shaohua Tian, Chee-Keong Kwoh, Xiaoli Li, Xuefeng Chen:
A universal transfer network for machinery fault diagnosis. Comput. Ind. 151: 103976 (2023) - [j107]Teng Ann Ng, Shamima Rashid, Chee Keong Kwoh:
Virulence network of interacting domains of influenza a and mouse proteins. Frontiers Bioinform. 3 (2023) - [j106]Bentao Zou, Yuefen Wang, Chee Keong Kwoh, Yonghua Cen:
Directed collaboration patterns in funded teams: A perspective of knowledge flow. Inf. Process. Manag. 60(2): 103237 (2023) - [j105]Rui Yin, Zihan Luo, Pei Zhuang, Min Zeng, Min Li, Zhuoyi Lin, Chee Keong Kwoh:
ViPal: A framework for virulence prediction of influenza viruses with prior viral knowledge using genomic sequences. J. Biomed. Informatics 142: 104388 (2023) - [j104]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan:
Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15604-15618 (2023) - [j103]Shamima Rashid, Suresh Sundaram, Chee Keong Kwoh:
Empirical Study of Protein Feature Representation on Deep Belief Networks Trained With Small Data for Secondary Structure Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 955-966 (2023) - [j102]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li, Cuntai Guan:
ADAST: Attentive Cross-Domain EEG-Based Sleep Staging Framework With Iterative Self-Training. IEEE Trans. Emerg. Top. Comput. Intell. 7(1): 210-221 (2023) - [j101]Zhuoyi Lin, Lei Feng, Xingzhi Guo, Yu Zhang, Rui Yin, Chee Keong Kwoh, Chi Xu:
COMET: Convolutional Dimension Interaction for Collaborative Filtering. ACM Trans. Intell. Syst. Technol. 14(4): 59:1-59:18 (2023) - [j100]Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. ACM Trans. Knowl. Discov. Data 17(8): 106:1-106:18 (2023) - [j99]Zhuoyi Lin, Sheng Zang, Rundong Wang, Zhu Sun, J. Senthilnath, Chi Xu, Chee Keong Kwoh:
Attention Over Self-Attention: Intention-Aware Re-Ranking With Dynamic Transformer Encoders for Recommendation. IEEE Trans. Knowl. Data Eng. 35(8): 7782-7795 (2023) - [c64]Zhang Wan, Zhuoyi Lin, Shamima Rashid, Shaun Yue-Hao Ng, Rui Yin, J. Senthilnath, Chee Keong Kwoh:
PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction. BIBM 2023: 49-56 - [c63]Yubo Hou, Tram Truong-Huu, Zhenghua Chen, Chee-Keong Kwoh, Sin G. Teo:
PROTEUS: Domain Adaptation for Dynamic Features in AI-assisted Windows Malware Detection. ICDM (Workshops) 2023: 1322-1331 - [i20]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
Label-efficient Time Series Representation Learning: A Review. CoRR abs/2302.06433 (2023) - [i19]Gabriel Tjio, Ping Liu, Chee-Keong Kwoh, Joey Tianyi Zhou:
Adaptive Stylization Modulation for Domain Generalized Semantic Segmentation. CoRR abs/2304.09347 (2023) - [i18]Gabriel Tjio, Ping Liu, Yawei Luo, Chee Keong Kwoh, Joey Tianyi Zhou:
Generating Reliable Pixel-Level Labels for Source Free Domain Adaptation. CoRR abs/2307.00893 (2023) - 2022
- [j98]Hai-Cheng Yi, Zhu-Hong You, De-Shuang Huang, Chee Keong Kwoh:
Graph representation learning in bioinformatics: trends, methods and applications. Briefings Bioinform. 23(1) (2022) - [j97]Rui Yin, Xianghe Zhu, Min Zeng, Pengfei Wu, Min Li, Chee Keong Kwoh:
A framework for predicting variable-length epitopes of human-adapted viruses using machine learning methods. Briefings Bioinform. 23(5) (2022) - [j96]Shamima Rashid, Teng Ann Ng, Chee Keong Kwoh:
Jupytope: computational extraction of structural properties of viral epitopes. Briefings Bioinform. 23(6) (2022) - [j95]Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Keong Kwoh, Jinmiao Chen, Jiawei Luo, Xiaoli Li:
Pre-training graph neural networks for link prediction in biomedical networks. Bioinform. 38(8): 2254-2262 (2022) - [j94]Mahdi Pursalim, Kwoh Chee Keong:
An Efficient Multiresolution Clustering for Motif Discovery in Complex Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(1): 284-294 (2022) - [j93]Rui Yin, Nyi Nyi Thwin, Pei Zhuang, Zhuoyi Lin, Chee Keong Kwoh:
IAV-CNN: A 2D Convolutional Neural Network Model to Predict Antigenic Variants of Influenza A Virus. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3497-3506 (2022) - [j92]Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Chee Keong Kwoh:
Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond. IEEE Trans. Cybern. 52(11): 12231-12244 (2022) - [j91]Mohamed Ragab, Zhenghua Chen, Wenyu Zhang, Emadeldeen Eldele, Min Wu, Chee Keong Kwoh, Xiaoli Li:
Conditional Contrastive Domain Generalization for Fault Diagnosis. IEEE Trans. Instrum. Meas. 71: 1-12 (2022) - [c62]Yue Liu, Junfeng Zhang, Shulin Wang, Wei Zhang, Xiangxiang Zeng, Chee Keong Kwoh:
A heterogeneous graph cross-omics attention model for single-cell representation learning. BIBM 2022: 270-275 - [c61]Chenyang Li, Chee Keong Kwoh, Xiaoli Li, Lingfei Mo, Ruqiang Yan:
Rotating Machinery Fault Diagnosis Based on Multi-sensor Information Fusion Using Graph Attention Network. ICARCV 2022: 678-683 - [e2]Hisao Ishibuchi, Chee-Keong Kwoh, Ah-Hwee Tan, Dipti Srinivasan, Chunyan Miao, Anupam Trivedi, Keeley A. Crockett:
IEEE Symposium Series on Computational Intelligence, SSCI 2022, Singapore, December 4-7, 2022. IEEE 2022, ISBN 978-1-6654-8768-9 [contents] - [i17]Zhuoyi Lin, Sheng Zang, Rundong Wang, Zhu Sun, Chi Xu, Chee Keong Kwoh:
Attention over Self-attention: Intention-aware Re-ranking with Dynamic Transformer Encoders for Recommendation. CoRR abs/2201.05333 (2022) - [i16]Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. CoRR abs/2203.08321 (2022) - [i15]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan:
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification. CoRR abs/2208.06616 (2022) - [i14]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation. CoRR abs/2210.06286 (2022) - [i13]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
CoTMix: Contrastive Domain Adaptation for Time-Series via Temporal Mixup. CoRR abs/2212.01555 (2022) - 2021
- [j90]Yu Zhang, Cangzhi Jia, Melissa Jane Fullwood, Chee Keong Kwoh:
DeepCPP: a deep neural network based on nucleotide bias information and minimum distribution similarity feature selection for RNA coding potential prediction. Briefings Bioinform. 22(2): 2073-2084 (2021) - [j89]Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiaoli Li:
Recent advances in network-based methods for disease gene prediction. Briefings Bioinform. 22(4) (2021) - [j88]Yu Zhang, Cangzhi Jia, Chee Keong Kwoh:
Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach. Briefings Bioinform. 22(4) (2021) - [j87]Yu Zhang, Yichao Cai, Xavier Roca, Chee Keong Kwoh, Melissa Jane Fullwood:
Chromatin loop anchors predict transcript and exon usage. Briefings Bioinform. 22(6) (2021) - [j86]Rui Yin, Zihan Luo, Pei Zhuang, Zhuoyi Lin, Chee Keong Kwoh:
VirPreNet: a weighted ensemble convolutional neural network for the virulence prediction of influenza A virus using all eight segments. Bioinform. 37(6): 737-743 (2021) - [j85]Yahui Long, Min Wu, Yong Liu, Jie Zheng, Chee Keong Kwoh, Jiawei Luo, Xiaoli Li:
Graph contextualized attention network for predicting synthetic lethality in human cancers. Bioinform. 37(16): 2432-2440 (2021) - [j84]Yu Zhang, Yahui Long, Chee Keong Kwoh:
Class similarity network for coding and long non-coding RNA classification. BMC Bioinform. 22(1): 609 (2021) - [j83]Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li:
Attention-based sequence to sequence model for machine remaining useful life prediction. Neurocomputing 466: 58-68 (2021) - [j82]Zhuoyi Lin, Lei Feng, Rui Yin, Chi Xu, Chee Keong Kwoh:
GLIMG: Global and local item graphs for top-N recommender systems. Inf. Sci. 580: 1-14 (2021) - [j81]Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li:
Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction. IEEE Trans. Ind. Informatics 17(8): 5239-5249 (2021) - [j80]Mohamed Ragab, Zhenghua Chen, Min Wu, Haoliang Li, Chee-Keong Kwoh, Ruqiang Yan, Xiaoli Li:
Adversarial Multiple-Target Domain Adaptation for Fault Classification. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j79]Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiaoli Li:
Multi-View Collaborative Network Embedding. ACM Trans. Knowl. Discov. Data 15(3): 39:1-39:18 (2021) - [j78]Dong Huang, Chang-Dong Wang, Hongxing Peng, Jianhuang Lai, Chee-Keong Kwoh:
Enhanced Ensemble Clustering via Fast Propagation of Cluster-Wise Similarities. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 508-520 (2021) - [c60]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan:
Time-Series Representation Learning via Temporal and Contextual Contrasting. IJCAI 2021: 2352-2359 - [i12]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan:
Time-Series Representation Learning via Temporal and Contextual Contrasting. CoRR abs/2106.14112 (2021) - [i11]Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan:
Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification. CoRR abs/2107.04470 (2021) - [i10]Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li:
Self-supervised Autoregressive Domain Adaptation for Time Series Data. CoRR abs/2111.14834 (2021) - 2020
- [j77]Yu Zhang, Yahui Long, Rui Yin, Chee Keong Kwoh:
DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation. IEEE Access 8: 76610-76617 (2020) - [j76]Pingjian Ding, Wenjue Ouyang, Jiawei Luo, Chee-Keong Kwoh:
Heterogeneous information network and its application to human health and disease. Briefings Bioinform. 21(4): 1327-1346 (2020) - [j75]Rui Yin, Emil Luusua, Jan Dabrowski, Yu Zhang, Chee Keong Kwoh:
Tempel: time-series mutation prediction of influenza A viruses via attention-based recurrent neural networks. Bioinform. 36(9): 2697-2704 (2020) - [j74]Yahui Long, Min Wu, Chee Keong Kwoh, Jiawei Luo, Xiaoli Li:
Predicting human microbe-drug associations via graph convolutional network with conditional random field. Bioinform. 36(19): 4918-4927 (2020) - [j73]Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, Chee Keong Kwoh, Peng Li, Jinke Wang:
A random forest based computational model for predicting novel lncRNA-disease associations. BMC Bioinform. 21(1): 126 (2020) - [j72]Yu Zhang, Yahui Long, Chee Keong Kwoh:
Deep learning based DNA: RNA triplex forming potential prediction. BMC Bioinform. 21(1): 522 (2020) - [j71]Rui Yin, Yu Zhang, Xinrui Zhou, Chee Keong Kwoh:
Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks. J. Bioinform. Comput. Biol. 18(1): 2040002:1-2040002:17 (2020) - [j70]Dong Huang, Chang-Dong Wang, Jian-Sheng Wu, Jian-Huang Lai, Chee-Keong Kwoh:
Ultra-Scalable Spectral Clustering and Ensemble Clustering. IEEE Trans. Knowl. Data Eng. 32(6): 1212-1226 (2020) - [c59]Yahui Long, Yu Zhang, Min Wu, Shaoliang Peng, Chee Keong Kwoh, Jiawei Luo, Xiaoli Li:
Predicting Drugs for COVID-19/SARS-CoV-2 via Heterogeneous Graph Attention Networks. BIBM 2020: 455-459 - [c58]Yu Zhang, Zhuoyi Lin, Chee Keong Kwoh:
Information Theory-Based Feature Selection: Minimum Distribution Similarity with Removed Redundancy. ICCS (5) 2020: 3-17 - [c57]Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li:
Adversarial Transfer Learning for Machine Remaining Useful Life Prediction. ICPHM 2020: 1-7 - [c56]Xiaosha Cai, Dong Huang, Chang-Dong Wang, Chee-Keong Kwoh:
Spectral Clustering by Subspace Randomization and Graph Fusion for High-Dimensional Data. PAKDD (1) 2020: 330-342 - [i9]Sezin Kircali Ata, Yuan Fang, Min Wu, Jiaqi Shi, Chee Keong Kwoh, Xiaoli Li:
Multi-View Collaborative Network Embedding. CoRR abs/2005.08189 (2020) - [i8]Mohamed Ragab, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Ruqiang Yan, Xiaoli Li:
Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction. CoRR abs/2007.09868 (2020) - [i7]Sezin Kircali Ata, Min Wu, Yuan Fang, Le Ou-Yang, Chee Keong Kwoh, Xiaoli Li:
Recent Advances in Network-based Methods for Disease Gene Prediction. CoRR abs/2007.10848 (2020) - [i6]Zhuoyi Lin, Lei Feng, Rui Yin, Chi Xu, Chee-Keong Kwoh:
GLIMG: Global and Local Item Graphs for Top-N Recommender Systems. CoRR abs/2007.14018 (2020) - [i5]Zhuoyi Lin, Lei Feng, Xingzhi Guo, Rui Yin, Chee Keong Kwoh, Chi Xu:
COMET: Convolutional Dimension Interaction for Deep Matrix Factorization. CoRR abs/2007.14129 (2020)
2010 – 2019
- 2019
- [j69]Xinrui Zhou, Rui Yin, Jie Zheng, Chee Keong Kwoh:
An Encoding Scheme Capturing Generic Priors and Properties of Amino Acids Improves Protein Classification. IEEE Access 7: 7348-7356 (2019) - [j68]Ali Ezzat, Min Wu, Xiaoli Li, Chee Keong Kwoh:
Computational prediction of drug-target interactions using chemogenomic approaches: an empirical survey. Briefings Bioinform. 20(4): 1337-1357 (2019) - [j67]Meng Zhang, Fuyi Li, Tatiana T. Marquez-Lago, André Leier, Cunshuo Fan, Chee Keong Kwoh, Kuo-Chen Chou, Jiangning Song, Cangzhi Jia:
MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters. Bioinform. 35(17): 2957-2965 (2019) - [j66]Dengju Yao, Xiaojuan Zhan, Chee-Keong Kwoh:
An improved random forest-based computational model for predicting novel miRNA-disease associations. BMC Bioinform. 20(1): 624 (2019) - [j65]Mohan R. Pradhan, Minh N. Nguyen, Srinivasaraghavan Kannan, Stephen J. Fox, Chee Keong Kwoh, David P. Lane, Chandra S. Verma:
Characterization of Hydration Properties in Structural Ensembles of Biomolecules. J. Chem. Inf. Model. 59(7): 3316-3329 (2019) - [j64]Pingjian Ding, Rui Yin, Jiawei Luo, Chee Keong Kwoh:
Ensemble Prediction of Synergistic Drug Combinations Incorporating Biological, Chemical, Pharmacological, and Network Knowledge. IEEE J. Biomed. Health Informatics 23(3): 1336-1345 (2019) - [c55]Zhuoyi Lin, Lei Feng, Chee-Keong Kwoh, Chi Xu:
Fast Top-N Personalized Recommendation on Item Graph. IEEE BigData 2019: 3903-3908 - [r4]Rui Yin, Chee Keong Kwoh, Jie Zheng:
Whole Genome Sequencing Analysis. Encyclopedia of Bioinformatics and Computational Biology (3) 2019: 176-183 - [r3]Fransiskus Xaverius Ivan, Chee-Keong Kwoh, Vincent T. K. Chow, Jie Zheng:
Genome Analysis - Identification of Genes Involved in Host-Pathogen Protein-Protein Interaction Networks. Encyclopedia of Bioinformatics and Computational Biology (3) 2019: 410-424 - [r2]Liangzhen Zheng, Amr Alhossary, Chee-Keong Kwoh, Yuguang Mu:
Molecular Dynamics and Simulation. Encyclopedia of Bioinformatics and Computational Biology (2) 2019: 550-566 - [r1]Xu Han, Chee Keong Kwoh:
Natural Language Processing Approaches in Bioinformatics. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 561-574 - [i4]Dong Huang, Chang-Dong Wang, Jian-Sheng Wu, Jian-Huang Lai, Chee-Keong Kwoh:
Ultra-Scalable Spectral Clustering and Ensemble Clustering. CoRR abs/1903.01057 (2019) - 2018
- [j63]Xinrui Zhou, Jie Zheng, Fransiskus Xaverius Ivan, Rui Yin, Shoba Ranganathan, Vincent T. K. Chow, Chee-Keong Kwoh:
Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses. BMC Genom. 19(S2) (2018) - [j62]Amr Alhossary, Yaw Awuni, Chee Keong Kwoh, Yuguang Mu:
Proposing drug fragments for dengue virus NS5 protein. J. Bioinform. Comput. Biol. 16(3): 1840017:1-1840017:20 (2018) - [j61]Rui Yin, Xinrui Zhou, Jie Zheng, Chee Keong Kwoh:
Computational identification of physicochemical signatures for host tropism of influenza A virus. J. Bioinform. Comput. Biol. 16(6): 1840023:1-1840023:21 (2018) - [i3]Dong Huang, Chang-Dong Wang, Hongxing Peng, Jianhuang Lai, Chee-Keong Kwoh:
Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities. CoRR abs/1810.12544 (2018) - 2017
- [j60]Ali Ezzat, Peilin Zhao, Min Wu, Xiaoli Li, Chee Keong Kwoh:
Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 646-656 (2017) - [c54]Fransiskus Xaverius Ivan, Xinrui Zhou, Akhila Deshpande, Rui Yin, Jie Zheng, Chee Keong Kwoh:
Phylogenetic Tree based Method for Uncovering Co-mutational Site-pairs in Influenza Viruses. BCB 2017: 21-26 - [c53]Chee Keong Kwoh:
AI and Big Data Analytics for Health and Bioinformatics. CSBio 2017: 1 - [c52]Rui Yin, Xinrui Zhou, Fransiskus Xaverius Ivan, Jie Zheng, Vincent T. K. Chow, Chee Keong Kwoh:
Identification of Potential Critical Virulent Sites Based on Hemagglutinin of Influenza a Virus in Past Pandemic Strains. ICBBS 2017: 30-36 - [i2]Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Chee-Keong Kwoh:
Toward Multi-Diversified Ensemble Clustering of High-Dimensional Data. CoRR abs/1710.03113 (2017) - 2016
- [j59]Xu Han, Jung-Jae Kim, Chee Keong Kwoh:
Active learning for ontological event extraction incorporating named entity recognition and unknown word handling. J. Biomed. Semant. 7: 22 (2016) - [j58]Ali Ezzat, Min Wu, Xiaoli Li, Chee Keong Kwoh:
Drug-target interaction prediction via class imbalance-aware ensemble learning. BMC Bioinform. 17(S-19): 267-276 (2016) - [j57]Hong Pan, Joanna D. Holbrook, Neerja Karnani, Chee Keong Kwoh:
Gene, Environment and Methylation (GEM): a tool suite to efficiently navigate large scale epigenome wide association studies and integrate genotype and interaction between genotype and environment. BMC Bioinform. 17: 299 (2016) - [j56]Swamidoss Issac Niwas, Vinit Jakhetiya, Weisi Lin, Chee Keong Kwoh, Chelvin C. Sng, Maria Cecilia Aquino, Victor Koh, Paul T. K. Chew:
Complex wavelet based quality assessment for AS-OCT images with application to Angle Closure Glaucoma diagnosis. Comput. Methods Programs Biomed. 130: 13-21 (2016) - [j55]Swamidoss Issac Niwas, Weisi Lin, Xiaolong Bai, Chee Keong Kwoh, C.-C. Jay Kuo, Chelvin C. Sng, Maria Cecilia Aquino, Paul T. K. Chew:
Automated anterior segment OCT image analysis for Angle Closure Glaucoma mechanisms classification. Comput. Methods Programs Biomed. 130: 65-75 (2016) - [j54]Xiaolong Bai, Swamidoss Issac Niwas, Weisi Lin, Bing-Feng Ju, Chee Keong Kwoh, Lipo Wang, Chelvin C. Sng, Maria Cecilia Aquino, Paul T. K. Chew:
Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis. J. Medical Syst. 40(4): 78:1-78:10 (2016) - [j53]Swamidoss Issac Niwas, Weisi Lin, Chee Keong Kwoh, C.-C. Jay Kuo, Chelvin C. Sng, Maria Cecilia Aquino, Paul T. K. Chew:
Cross-Examination for Angle-Closure Glaucoma Feature Detection. IEEE J. Biomed. Health Informatics 20(1): 343-354 (2016) - [c51]Xu Han, Chee Keong Kwoh, Jung-Jae Kim:
Clustering based active learning for biomedical Named Entity Recognition. IJCNN 2016: 1253-1260 - 2015
- [j52]Amr Alhossary, Stephanus Daniel Handoko, Yuguang Mu, Chee Keong Kwoh:
Fast, accurate, and reliable molecular docking with QuickVina 2. Bioinform. 31(13): 2214-2216 (2015) - [j51]Fan Zhang, Min Wu, Xuejuan Li, Xiaoli Li, Chee Keong Kwoh, Jie Zheng:
Predicting essential genes and synthetic lethality via influence propagation in signaling pathways of cancer cell fates. J. Bioinform. Comput. Biol. 13(3): 1541002:1-1541002:14 (2015) - [j50]S. Issac Niwas, Weisi Lin, Xiaolong Bai, Chee Keong Kwoh, Chelvin C. Sng, Maria Cecilia Aquino, Paul T. K. Chew:
Reliable Feature Selection for Automated Angle Closure Glaucoma Mechanism Detection. J. Medical Syst. 39(3): 21 (2015) - [j49]Thuy-Diem Nguyen, Bertil Schmidt, Zejun Zheng, Chee-Keong Kwoh:
Efficient and Accurate OTU Clustering with GPU-Based Sequence Alignment and Dynamic Dendrogram Cutting. IEEE ACM Trans. Comput. Biol. Bioinform. 12(5): 1060-1073 (2015) - [i1]Jian-Ping Mei, Chee Keong Kwoh, Peng Yang, Xiaoli Li:
Classification and its application to drug-target interaction prediction. CoRR abs/1502.04469 (2015) - 2014
- [j48]Peng Yang, Min Wu, Jing Guo, Chee Keong Kwoh, Teresa M. Przytycka, Jie Zheng:
LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphisms. BMC Bioinform. 15: 48 (2014) - [j47]Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li:
Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots. BMC Bioinform. 15: 57 (2014) - [j46]Chinh Tran To Su, Thuy-Diem Nguyen, Jie Zheng, Chee Keong Kwoh:
IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking. BMC Bioinform. 15(S-16): S9 (2014) - [j45]