2022
1.Jiawei Luo*, Yi Liu, Pei Liu, Zihan Lai, Hao Wu.Data Integration Using Tensor Decomposition for the Prediction of miRNA-Disease Associations.IEEE Journal of Biomedical and Health Informatics, 2022,
26(5):
2370-2378.
2.Jiawei Luo*, Wenjue Ouyang, Cong Shen, Jie Cai. Multi-Relation Graph Embedding for Predicting miRNA-Target Gene Interactions by Integrating Gene Sequence Information.IEEE Journal of Biomedical and Health Informatics, 2022,
26(8):
4345-4353.
3. Zhongyuan Xu,Jiawei Luo*,Zehao Xiong. scSemiGAN: a single-cell semi-supervised annotation and dimensionality reduction framework based on generative adversarial network.Bioinformatics, 2022,38(22):5042–5048.
4. Yahui Long, Yu Zhang, Min Wu, Shaoliang Peng, Chee Keong Kwoh,Jiawei Luo*, Xiaoli Li*. Heterogeneous graph attention networks for drug virus association prediction. Methods, 2022, 198:11-18.
5. Ying Liu, Ruihui Li,Jiawei Luo*, Zhaolei Zhang*. Inferring RNA-binding protein target preferences using adversarial domain adaptation.PLOS Computational Biology, 2022, 18(2): e1009863.
6. Pei Liu,Jiawei Luo*, Xiangtao Chen. miRCom: Tensor Completion Integrating Multi-View Information to Deduce the Potential Disease-Related miRNA-miRNA Pairs.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022,19(3): 1747-1759.
7. 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.Bioinformatics, 2022,38(8):2254–2262.
8. Qiu Xiao, Jianhua Dai,Jiawei Luo*.A survey of circular RNAs in complex diseases: databases, tools and computational methods.Briefings in Bioinformatics, 2022,22(1):bbab444.
2021
1. Xinru Tang,Jiawei Luo*, Cong Shen, Zihan Lai.Multi-view Multichannel Attention Graph
Convolutional Network for miRNA–disease association prediction.Briefings in Bioinformatics, 2021,22(6):bbab174.
2. 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. Bioinformatics, 2021,37(16):2432–2440.
3. Weidun Xie,Jiawei Luo*, Chu Pan, Ying Liu. SG-LSTM-FRAME: a computational frame using sequence and geometrical information via LSTM to predict miRNA–gene associations. Briefings in Bioinformatics, 2021,22(2):2032–2042.
4. Yahui Long,Jiawei Luo*, Yu Zhang, Yan Xia. Predicting human microbe–disease associations via graph attention networks with inductive matrix completion. Briefings in Bioinformatics, 2021,22(3): bbaa146.
5. Qiu Xiao, Ning Zhang,Jiawei Luo*, Jianhua Dai, Xiwei Tang. Adaptive multi-source multi-view latent feature learning for inferring potential disease-associated miRNAs. Briefings in Bioinformatics, 2021,22(2):2043-2057.
6.Jiawei Luo, Cong Shen , Zihan Lai, Jie Cai, Pingjian Ding.Incorporating Clinical, Chemical and Biological Information for Predicting Small Molecule-microRNA Associations Based on Non-Negative Matrix Factorization.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021,18(6): 2535-2545.
7. Pingjian Ding, Cheng Liang, Wenjue Ouyang, Guanghui Li, Qiu Xiao,Jiawei Luo*. Inferring Synergistic Drug Combinations Based on Symmetric Meta-Path in a Novel Heterogeneous Network.IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021,18(4): 1562-1571.
8. Cheng Liang, Mingchao Shang,Jiawei Luo*. Cancer subtype identification by consensus guided graph autoencoders. Bioinformatics, 37(24), 2021, 4779–4786.
9.Jiawei Luo, Zihan Lai, Cong Shen, Pei Liu, Heyuan Shi. Graph AttentionMechanism-based Deep Tensor Factorization for Predicting disease-associatedmiRNA-miRNA pairs. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021: 189-196.
2020
1.Yahui Long, Min Wu, Chee-Keong Kwoh,Jiawei Luo*, Xiaoli Li. Predicting Human Microbe-Drug Associations via Graph Convolutional Network with Conditional Random Field. Bioinformatics, 2020,36(19), 4918-4927.
2.Cong Shen,Jiawei Luo*, Wenjue Ouyang, Pingjian Ding, Xiangtao Chen. IDDkin: network-based influence deep diffusion model for enhancing prediction of kinase inhibitors. Bioinformatics, 2020, 36(22-23): 5481–5491.
3.Yahui Long, Min Wu, Yong Liu, Chee-Keong, Kwoh,Jiawei Luo*, Xiaoli Li. Ensembling graph attention networks for human microbe-drug association prediction. Bioinformatics, 2020,36: i779-i786.
4.Qiu Xiao,Jiawei Luo*, Cheng Liang, Guanghui Li, Jie Cai, Pingjian Ding, Ying Liu. Identifying lncRNA and mRNA Co-Expression Modules from Matched Expression Data in Ovarian Cancer. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020,17(2): 623-634.
5. Pingjian Ding, Wenjue Ouyang,Jiawei Luo*, Chee-Keong Kwoh. Heterogeneous information network and its application to human health and disease. Briefings in Bioinformatics, 2020, 21(4):1327-1346.
6.Cong Shen,Jiawei Luo*, Wenjue Ouyang, Pingjian Ding, Hao Wu. Identification of Small Molecule–miRNA Associations with Graph Regularization Techniques in Heterogeneous Networks. Journal of Chemical Information and Modeling, 2020.60(12): 6709–672.
7.Chu Pan ,Jiawei Luo*, Jiao Zhang. Computational Identification of RNA-Seq Based miRNA-Mediated Prognostic Modules in Cancer. IEEE Journal of Biomedical and Health Informatics, 2020, 24(2): 626-633.
8.Cong Shen,Jiawei Luo*, Zihan Lai, Pingjian Ding. Multiview Joint Learning-Based Method for Identifying Small-Molecule-Associated MiRNAs by Integrating Pharmacological, Genomics, and Network Knowledge. Journal of Chemical Information and Modeling, 2020, 60(8): 4085-4097.
9.Chu Pan,Jiawei Luo*, Jiao Zhang, Xin Li. BiModule: Biclique Modularity Strategy for Identifying Transcription Factor and microRNA Co-Regulatory Modules. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020,17(1):321-326.
10.Yahui Long,Jiawei Luo*. Association mining to identify microbe drug interactions based on heterogeneous network embedding representation. IEEE Journal of Biomedical and Health Informatics, 2020,25(01): 266-275.
11.Ying Liu, Chu Pan, Dehan Kong,Jiawei Luo*, Zhaolei Zhang. A Survey of Regulatory Interactions Among RNA Binding Proteins and MicroRNAs in Cancer. Frontiers in Genetics, 2020, 11:515094.
2019
1. Qiu Xiao, Jianhua Dai,Jiawei Luo*, Hamido Fujita.Multi-view manifold regularized learning-based method forprioritizing candidate disease miRNAs. Knowledge Based Systems, 2019, 175:118-129.
2.Cheng Liang, Shengpeng Yu,Jiawei Luo*. Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs. PLOS Computational Biology, 2019, 15(4): e1006931.
3.Pingjian Ding, Rui Yin,Jiawei Luo*, Chee Keong Kwoh. Ensemble Prediction of Synergistic Drug CombinationsIncorporating Biological, Chemical, Pharmacological and Network Knowledge. IEEE Journal of Biomedical and Health Informatics, 2019,
23(3):
1336-1345.
4.Jiawei Luo, Chu Pan, GenXiang, Ying,Yin. A Novel Cluster-Based Computational Method to Identify miRNA Regulatory Modules. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019,16(2):681-687.
5. Qiu Xiao,Jiawei Luo*, Cheng Liang, Jie Cai, Guanghui Li, Buwen Cao. CeModule: an integrative framework for discovering regulatorypatterns from genomic data in cancer. BMC Bioinformatics, 2019,20:67.
6. Ying Liu,Jiawei Luo*, PingjianDing. Inferring MicroRNA Targets Based on Restricted Boltzmann Machines. IEEE Journal of Biomedical and Health Informatics, 2019. 23(1): 427-436.
7. Yahui Long,Jiawei Luo*.WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network.BMC Bioinformatics, 2019,20:541.
2018
1. Qiu Xiao,Jiawei Luo*, ChengLiang, Jie Cai, Pingjian Ding. A graph regularized non-negative matrix factorizationmethod for identifying microRNA-disease associations. Bioinformatics. 2018. 34(2): 239-248.
2.Jiawei Luo*, Yahui Long. NTSHMDA:Prediction of Human Microbe-Disease Association based on Random Walk byIntegrating Network Topological Similarity. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018. Early Access.
3. Qiu Xiao,Jiawei Luo*, Cheng Liang, Guanghui Li, Jie Cai, Pingjian Ding, Ying Liu. Identifying lncRNA andmRNA co-expression modules from matched expression data in ovarian Cancer. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018. Early Access.
4.Jiawei Luo*, Pingjian Ding,Cheng Liang, Xiangtao Chen. Semi-supervised prediction of human miRNA-diseaseassociation based on graph regularization framework in heterogeneous networks. Neurocomputing.2018. 294(4): 29-38.
5. Pingjian Ding,Jiawei Luo*,Cheng Liang, Qiu Xiao, Buwen Cao, Guanghui Li. Discovering synergistic drugcombination from a computational perspective. Current topics in medicinalchemistry. 2018. 18(12): 965-974.
6.Jiawei Luo*, Ying Yin, Chu Pan,Gen Xiang, Nguyen Hoang Tu. Identifying functional modules in co-regulatorynetworks through overlapping spectral clustering. IEEE Transactions on nanobioscience. 2018. 17(2):134-144.
7. Pingjian Ding,Jiawei Luo*,Cheng Liang, Qiu Xiao, Buwen Cao. Human disease MiRNA inference by combiningtarget information based on heterogeneous manifolds. Journal of biomedical informatics. 2018. 80(6): 26-36.
8.Jiawei Luo*, Wei Huang, BuwenCao. A novel approach to identify the mirna-mrna causal regulatory modules incancer.IEEE/ACM transactions oncomputational biology and bioinformatics.2018. 15(1): 309-315.
9.Jiawei Luo*, Lv Ding, ChengLiang, Nguyen Hoang Tu. An efficient network motif discovery approach forco-regulatory networks. IEEE Access 2018. 6:14151-14158.
10. Guanghui Li*,Jiawei Luo*, QiuXiao, Cheng Liang, Pingjian Ding. Prediction of microRNA–disease associationswith a Kronecker kernel matrix dimension reduction model. RSC Advances. 2018. 8(8):4377-4385.
2017
1.Jiawei Luo*; Pingjian Ding; Cheng Liang; Buwen Cao; Xiangtao Chen, Collective prediction of disease-associated miRNAs based on transduction learning, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017, 14(6): 1468~1475(SCI)
2.Pingjian Ding ;Jiawei Luo*; Cheng Liang; Jie Cai; Ying Liu; Xiangtao Chen, A Novel Group Wise-Based Method for Calculating Human miRNA Functional Similarity , IEEE ACCESS, 2017, 5: 2364~2372(SCI)
3.Luo, Jiawei*; Xiao, Qiu, A novel approach for predicting microRNA-disease associations by unbalanced bi-random walk on heterogeneous network , JOURNAL OF BIOMEDICAL INFORMATICS, 2017, 66: 194~203(SCI)
4.Luo, Jiawei*; Xiang, Gen; Pan, Chu, Discovery of microRNAs and
Transcription Factors Co-Regulatory Modules by Integrating Multiple Types of Genomic Data , IEEE TRANSACTIONS ON NANOBIOSCIENCE, 2017, 16(1): 51~59(SCI)
5.Zhiming Liu ;Jiawei Luo*, Genome-wide predicting disease-related protein complexes by walking on the heterogeneous network based on data integration and laplacian normalization , COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2017, 69: 41~47(SCI)
6.Jiawei Luo*; Qiu Xiao; Cheng Liang; Pingjian Ding,Predicting MicroRNA-Disease Associations Using Kronecker Regularized Least Squares Based on Heterogeneous Omics Data , IEEE ACCESS, 2017, 5: 2503~2513(SCI)
7.Zakouni, Amiyne ;Luo, Jiawei*; Kharroubi, Fouad*, Genetic algorithm and tabu search algorithm for solving the static manycast RWA problem in optical networks , JOURNAL OF COMBINATORIAL OPTIMIZATION, 2017, 33(2): 726~741(SCI)
8.Luo, Jiawei*; Liu, Chengchen,An Effective Method for Identifying Functional Modules in Dynamic PPI Networks , CURRENT BIOINFORMATICS, 2017, 12(1): 66~79(SCI)
9.骆嘉伟;宋丹;蔡洁;王伟胜;刘智明,一种基于功能模块的疾病关联因子识别方法及系统（申请并进入实审）, 2017.1.18,中国, N201710035109.2(发明专利)
2016
1.Liang, Cheng ; Li, Yue;Luo, Jiawei*, A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging , IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2016, 13(3): 549~556(SCI)
2.Cao, Buwen ;Luo, Jiawei*; Liang, Cheng; Wang, Shulin; Ding, Pingjian, PCE-FR: A Novel Method for Identifying Overlapping Protein Complexes in Weighted Protein-Protein Interaction Networks Using Pseudo-Clique Extension Based on Fuzzy Relation , IEEE TRANSACTIONS ON NANOBIOSCIENCE, 2016, 15(7): 728~738(SCI)
3.Jiawei Luo*; Cong Huang; Pingjian Ding, A Meta-Path-Based Prediction Method for Human miRNA-Target Association. , Biomed Res Int, 2016, 2016:7460740(SCI)
4.Luo, Jiawei*; Lin, Dingyu; Cao, Buwen, A cell-core-attachment approach for identifying protein complexes in yeast protein-protein interaction network , JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2016, 31(2): 967~978(SCI)
5.Ding, Pingjian ;Luo, Jiawei*; Xiao, Qiu; Chen, Xiangtao, A path-based measurement for human miRNA functional similarities using miRNA-disease associations , SCIENTIFIC REPORTS, 2016, 6: 32533(SCI)
6.Buwen Cao ;Jiawei Luo*; Cheng Liang; Shulin Wang, Detecting overlapping protein complexes in weighted protein-protein interaction networks using pseudo-clique extension based on fuzzy relation, International Joint Conference on Neural Networks, Vancouver, BC, 2016.7.24-2016.7.29
2015
1.Jiawei Luo*; Yi Qi, Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes , PLos One, 2015, 10(6): e0131418(SCI)
2.Liang, Cheng ; Li, Yue ;Luo, Jiawei*; Zhang, Zhaolei*, A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human , BIOINFORMATICS, 2015, 31(14): 2348~2355(SCI IF=5.481)
3.Cao, Buwen;Luo, Jiawei*; Liang, Cheng; Wang, Shulin; Song, Dan,MOEPGA: A novel method to detect protein complexes in yeast protein-protein interaction networks based on Multi Objective Evolutionary Programming Genetic Algorithm , COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2015, 58: 173~181(SCI)
4.Jiawei Luo*; Xiaoshuang Liang, Discovering co-regulated modules based on protein interaction and transcriptional regulatory networks , Journal of Computational Information Systems, 2015, 11(8): 3041~3049(SCI)
5.Jiawei Luo*; Juan Wu,A new algorithm for essential proteins identification based on the integration of protein complex co-expression information and edge clustering coefficient , International Journal of Data Mining and Bioinformatics, 2015, 12(3): 257~274 (SCI)
6.Luo, Jiawei*; Liang, Shiyu, Prioritization of potential candidate disease genes by topological similarity of protein-protein interaction network and phenotype data , JOURNAL OF BIOMEDICAL INFORMATICS, 2015, 53: 229~236(SCI)
7.Luo, Jiawei*; Liu, Chengchen; Hoang Tu Nguyen, A Core-Attach Based Method for Identifying Protein Complexes in Dynamic PPI Networks , 19thPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), John Neumann Inst, Ho Chi Minh City, 2015.5.19-2015.5.22
8.Hisham Albukhaiti;Jiawei Luo*,A Feature Selection Approach for Classifying Diseases Based on Medical Data, 2015 Global Conference on Biological Engineering and Biomedical, Shanghai, Shanghai, 2015.1.17-2015.1.18
2014
1.Jiawei Luo*; Guanghui Li; Dan Song; Cheng Liang,CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks , Physica A: Statistical Mechanics and Its Applications, 2014, 416: 309~320(SCI)
2.Lin, Hongli*; Wang, Weisheng;Luo, Jiawei; Yang, Xuedong, Development of a Personalized Training System Using the Lung Image Database Consortium and Image Database Resource Initiative Database , ACADEMIC RADIOLOGY, 2014, 21 (12): 1614~1622(SCI)
3.Li, Yue*; Liang, Cheng ; Easterbrook, Steve;Luo, Jiawei; Zhang,Zhaolei, Investigating the functional implications of reinforcing feedback loops in transcriptional regulatory networks , MOLECULAR BIOSYSTEMS, 2014, 10(12): 3238~3248(SCI)
4.Li, Yue*; Liang, Cheng; Wong, Ka-Chun;Luo, Jiawei; Zhang, Zhaolei*,Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion , BIOINFORMATICS, 2014, 30(18): 2627~2635(SCI IF=5.481)
5.Liang, Cheng ;Jiawei, Luo*; Song, Dan, Network simulation reveals significant contribution of network motifs to the age-dependency of yeast protein-protein interaction networks , MOLECULAR BIOSYSTEMS, 2014, 10(9): 2277~2288(SCI)
6.Luo, Jiawei*; Wei, Miao, An accelerated network Motif detection algorithm using the structure of basic symmetric subgraph , Journal of Computational Information Systems, 2014, 10(17): 7315~7322(SCI)
7.Luo, Jiawei*; Zhang, Nan, PREDICTION OF ESSENTIAL PROTEINS BASED ON EDGE CLUSTERING COEFFICIENT AND GENE ONTOLOGY INFORMATION , JOURNAL OF BIOLOGICAL SYSTEMS, 2014, 22(3): 1~13(SCI)
8.Luo Jiawei*; Liu Shunmin,A Novel Essential Protein Identification Algorithm Based on the Integration of Local Network Topology and Gene Ontology , JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 2014, 11(3): 619~624(SCI)
9.Luo, Jiawei*; Li, Guanghui; Song, Dan; Liang, Cheng, Integrating Functional and Topological Properties to Identify Biological Network Motif in Protein Interaction Networks , JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 2014, 11(3): 744~750(SCI)
10.Lin, Hongli*; Yang, Xuedong ; Wang, Weisheng;Luo, Jiawei, A Performance Weighted Collaborative Filtering algorithm for personalized radiology education , JOURNAL OF BIOMEDICAL INFORMATICS, 2014, 51: 107~113(SCI)
11.Luo, Jiawei*; Kuang, Ling,A new method for predicting essential proteins based on dynamic network topology and complex information , COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2014, 52: 34~42(SCI)
12.Thi-Thiet Pham ;Luo, Jiawei*; Tzung-Pei Hong; Bay Vo , An efficient method for mining non-redundant sequential rules using attributed prefix-trees , ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 32: 88~99(SCI)
