数据挖掘、智能与生物信息处理、大数据存储与挖掘

    本科生课程：数据结构、算法设计与分析

    硕士生课程：高等数据结构与算法、数据挖掘

    博士生课程：智能优化算法

1. 国家自然科学基金：面向单细胞和空间组学数据的细胞异质性分析和药物反应预测方法研究 （62372165），2024-2027，主持。

2. 国家重点研发计划课题：面向多应用场景的高信噪比信号高速均衡电路关键技术，2022-2025，主持。

3. 国家自然科学基金重点项目：基于单细胞多组学数据的癌症模式挖掘理论与方法研究（62032007），2021-2025，合作单位主持。

4. 国家自然科学基金：MicroRNA对基因的调控作用及其与疾病关联关系的计算方法研究（61873089），2019-2022，主持。

5. 国家自然科学基金：基于新一代测序数据的复杂疾病特异共调控网络构建及分析方法研究（61572180），2016-2019，主持。

6. 国家自然科学基金：蛋白质网络动态演化模型及应用算法研究（61240046），2013，主持。

7. 国家自然科学基金：新型表达模式下的功能基因分析算法研究（60873184），2009-2011，主持。

8. 国家发改委重大项目子项：虚拟图书馆系统（计高技[2000]2034号)，2004-2005，主持。

9. 湖南省自然科学基金重点资助：基于蛋白质相互作用演化模型的网络结构分析（13JJ2017），2013-2015，主持。

10. 湖南省财政厅：蛋白质组信息获取和分析方法研究 (湘财教字[2010]163号)，2010-2012，主持。

11. 湖南省自然科学基金：基于聚类的基因功能预测方法(07JJ5086)，2008-2010，主持。

12. 湖南省财政厅：数据挖掘在入侵检测系统中的应用研究 (湘财教字[2006]52号)，2006-2009，主持。

13.湖南省自然科学基金：基于序列图形表示的功能基因分析算法研究 (06JJ4076)，2006-2008，主持。

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 for prioritizing 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 , 19^th Pacific-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)