lanwei163163

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Biography

Wei Lan is a Associate Professor in Guangxi University. I received his Ph.D degree in computer science from Central South University, China. His research interests include Bioinformatics, data mining and machine learning.

Research Grants

  1. Discovering tsRNA-disease association based on Knowledge Graph, $70K, 2025-2028, supported by National Natural Science Foundation of China
  2. Identifying CircRNA-Cancer interactions based on Multiple Omics data fusion, $80K, 2021-2024, supported by National Natural Science Foundation of China
  3. Predicting LncRNA-Disease interactions based on Multiple Networks fusion, $40K, 2018-2020, supported by National Natural Science Foundation of China
  4. Identifying miRNA-Disease interactions based on Marching learning, $20K, 2019-2021, supported by Natural Science Foundation of Guangxi
  5. Research on brain diseases based on medical imaging data and multiple omics data, $30K, 2020-2022, supported by Natural Science Foundation of Guangxi
  6. Research on Cancer-related noncoding RNA Identification based on machine learning method, $10K, 2017-2020, supported by Advanced Technology Key Laboratory of Qinzhou

PUBLICATIONS

Book Chapter:

  1. Wei Lan, Liyu Huang, Dehuan Lai, Qingfeng Chen. Identifying interactions between long non-coding RNAs and diseases based on computational methods. Computational Systems Biology, book edited by Tao Huang, Springer, 2018.

Paper:

  1. Wei Lan, Haibo Liao, Qingfeng Chen, Lingzhi Zhu, Yi Pan, Yi-Ping Phoebe Chen. DeepKEGG: A multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery. Briefings in Bioinformatics, 2024, DOI: 10.1093/bib/bbae185
  2. Wei Lan, Mingyang Liu, Jianwei Chen, Jin Ye, Ruiqing Zheng, Xiaoshu Zhu, Wei Peng. JLONMFSC: Clustering scRNA-seq data based on joint learning of non-negative matrix factorization and subspace clustering. Methods, 2024, 222:1-9
  3. Wei Lan, Guoxian Zhou, Qingfeng Chen, Wenguang Wang, Shirui Pan, Yi Pan, Shichao Zhang. Contrastive Clustering Learning for Multi-Behavior Recommendation. ACM Transactions on Information Systems, 2024
  4. Wei Lan, Yuan Zhou, Rasmani Hazra. The evolution in RNA: 2023. Frontiers in Genetics, 2024, 15, 1457242
  5. Wei Lan, Guohang He, Mingyang Liu, Qingfeng Chen, Junyue Cao, Wei Peng. Transformer-based single-cell language model: A survey, Big Data Mining and Analytics, 2024
  6. Wei Lan, Shengzu Huang, Xun Sun, Haibo Liao, Qingfeng Chen, Junyue Cao. Single-Cell Multi-omics Clustering Algorithm Based on Adaptive Weighted Hyper-laplacian Regularization. International Symposium on Bioinformatics Research and Applications, 2024, 373-382
  7. Wei Lan, Weihao Zhou, Qingfeng Chen, Ruiqing Zheng, Yi Pan, Yi-Ping Phoebe Chen. Modeling Single-Cell ATAC-Seq Data Based on Contrastive Learning. International Symposium on Bioinformatics Research and Applications, 2024, 473-482
  8. Wei Lan, Chunling Li, Qingfeng Chen, Ning Yu, Yi Pan, Zheng Yun, Yi-Ping Phoebe Chen. LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024.
  9. Wei Lan, Jianwei Chen, Mingyang Liu, Qingfeng Chen, Jin Liu, Jianxin Wang, Yi-Ping Phoebe Chen. Deep Imputation Bi-stochastic Graph Regularized Matrix Factorization for Clustering Single-cell RNA-sequencing Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024.
  10. Yiran Huang, Yufu Lin, Wei Lan, Cuiyu Huang, Cheng Zhong. GloEC: a hierarchical-aware global model for predicting enzyme function. Briefings in Bioinformatics, 2024, 25:(5), bbae365
  11. Wei Peng, Zhichen He, Wei Dai, Wei Lan. MHCLMDA: multihypergraph contrastive learning for miRNA–disease association prediction. Briefings in Bioinformatics, 2024, 25(1): bbad524
  12. Liyu Huang, Qingfeng Chen, Wei Lan. Predicting drug–drug interactions based on multi-view and multichannel attention deep learning. Health Information Science and Systems, 2024, 11:50
  13. Zhixian Liu, Qingfeng Chen, Wei Lan, Huihui Lu, Shichao Zhang. SSLDTI: A novel method for drug-target interaction prediction based on self-supervised learning. Artificial Intelligence in Medicine, 2024, 149: 102778
  14. Qingfeng Chen, Junlai Qiu, Wei Lan, Junyue Cao. Similarity-guided Graph Contrastive Learning for LncRNA-disease Association Prediction. Journal of Molecular Biology, 2024, 168609
  15. Zhanyu Xu, Haibo Liao, Liuliu Huang, Qingfeng Chen, Wei Lan, Shikang Li. IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability. Briefings in Bioinformatics, 2024, 25(3): bbae080
  16. Junyue Cao, Qingfeng Chen, Junlai Qiu, Yiming Wang, Wei Lan, Xiaojing Du, Kai Tan. NGCN: Drug‐target interaction prediction by integrating information and feature learning from heterogeneous network. Journal of Cellular and Molecular Medicine, 2024, 28(7): e18224.
  17. Wei Lan, Yi Dong, Qingfeng Chen, Jin Liu, Jianxin Wang, Yiping Phoebe Chen. Benchmarking of computational methods for predicting circRNA-disease associations. Briefing in Bioinformatics, 2023, bbac613.
  18. Wei Lan, Tianchuan Yang, Qingfeng Chen, Shichao Zhang, Yi Dong, Huiyu Zhou, Yi Pan. Multiview Subspace Clustering via Low-Rank Symmetric Affinity Graph. IEEE Transactions on Neural Networks and Learning Systems, 2023.
  19. Xiaoshu Zhu, Liyuan Pang, Xiaojun Ding, Wei Lan, Shuang Meng, Xiaoqing Peng. A Gene Correlation Measurement Method for Spatial Transcriptome Data Based on Partitioning and Distribution. Journal of Computational Biology, 30(8): 877-888, 2023.
  20. Yiran Huang, Yongjin Bin, Pingfan Zeng, Wei Lan, Cheng Zhong. NetPro: Neighborhood Interaction-based Drug Repositioning via Label Propagation. IEEE/ACM Transactions on Computational Biology and Bioinformatics,2023.
  21. Wei Peng, Tielin Chen, Hancheng Liu, Wei Dai, Ning Yu, Wei Lan. Improving drug response prediction based on two-space graph convolution. Computers in Biology and Medicine, 2023, 158: 106859.
  22. Yiran Huang, Zhihong Wu, Wei Lan, Cheng Zhong. Predicting disease-associated N7-methylguanosine (m7G) sites via random walk on heterogeneous network. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023.
  23. Wei Lan, Hongyu Zhang, Yi Dong, Qingfeng Chen, Wei Peng, Jin Liu, Min Li. DRGCNCDA: Predicting circRNA-disease interactions based on knowledge graph and disentangled relational graph convolutional network. Methods, 2022, 208, 35-41.
  24. Wei Lan, Xun Sun, Qingfeng Chen, Jin Ye, Xiaoshu Zhu, Yi Pan. scIAC: clustering scATAC-seq data based on Student’s t-distribution similarity imputation and denoising autoencoder. BIBM, 2022
  25. Wei Lan, Wenguang Wang. Dual Channel Hybrid Messaging-Passing Graph Convolutional Network. IEEE DSAA, 2022
  26. Chengqian Lu, Lishen Zhang, Min Zeng, Wei Lan, Guihua Duan, Jianxin Wang. Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network. Briefing in Bioinformatics, 2022.
  27. Wei Peng, Zicheng Che, Wei Dai, Shoulin Wei, Wei Lan. Predicting miRNA-disease associations from miRNA-gene-disease heterogeneous network with multi-relational graph convolutional network model. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022.
  28. Junbin Mao, Yu Sheng, Wei Lan, Xu Tian, Jin Liu, Yi Pan. Graph Convolutional Networks Based on Relational Attention Mechanism for Autism Spectrum Disorders Diagnosis. 15th International Conference Intelligent Robotics and Applications, 341-348, 2022
  29. Jin Ye, Menglan Wu, Wenjie Qiu, Juan Yang, Wei Lan. Polyphyletic Loss: Litchi Flower Detection with Occlusion. Journal of Physics: Conference Series 2171 (1), 012041
  30. Xiaoshu Zhu, Liyuan Pang, Wei Lan, Shuang Meng and Xiaoqing Peng. STgcor: A Distribution-based Correlation Measurement Method for Spatial Transcriptome Data. ISBRA 2022.
  31. Wei Lan, Yi Dong, Qingfeng Chen, Ruiqing Zheng, Jin Liu, Yi Pan, Yiping Phoebe Chen. KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network. Briefing in Bioinformatics, 2022. bbab494.
  32. Wei Lan, Mingrui Zhu, Qingfeng Chen, Jianwei Chen, Jin Ye, Jin Liu, Wei Peng, Shirui Pan. Prediction of circRNA-miRNA Associations Based on Network Embedding. Complexity, 6659695, 2021.
  33. Wei Lan, Qingfeng Chen, Yi-Ping Phoebe Chen, Wilson Wen Bin Goh. Graph Embedding Methods for Multiple-Omics Data Analysis. Frontiers in Genetics, 2021.
  34. Wei Lan, Ximin Wu, Qingfeng Chen, Wei Peng, Jianxin Wang, Yiping Phoebe Chen. GANLDA: Graph attention network for lncRNA-disease associations prediction. Neurocomputing, 2021, https://doi.org/10.1016/j.neucom.2020.09.094.
  35. Wei Lan, Yi Dong, Qingfeng Chen, Jin Liu, Jianxin Wang, Yiping Phoebe Chen, Shirui Pan. IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021, 10.1109/TCBB.2021.3111607.
  36. Yi Pan, Jin Liu, Tian Xu, Wei Lan, Rui Guo. Hippocampal Segmentation in Brain MRI Images Using Machine Learning Methods: A Survey. Chinese Journal of Electronics, 2021, 30(5): 793-814. doi: 10.1049/cje.2021.06.002
  37. Wei Peng, Jielin Du, Wei Dai, Wei Lan. Predicting miRNA-disease association based on modularity preserving heterogeneous network embedding. Frontiers in Cell and Developmental Biology, 2021, doi:10.3389/fcell.2020.603758
  38. Zhixian Liu, Qingfeng Chen, Wei Lan, Haiming Pan, Xinkun Hao, Shirui Pan. GADTI: Graph Autoencoder Approach for Drug-Target Interaction Prediction from Heterogeneous Network. Frontiers in Genetics, 2021
  39. Zicheng Che, Wei Peng, Wei Dai, Shoulin Wei, Wei Lan. A Heterogeneous Graph Convolutional Network-Based Deep Learning Model to Identify miRNA-Disease Association. International Symposium on Bioinformatics Research and Applications, 130-141, 2021.
  40. Xiujuan Lei, Thosini Bamunu Mudiyanselage, Yuchen Zhang, Chen Bian, Wei Lan, Ning Yu, Yi Pan. A comprehensive survey on computational methods of non-coding RNA and disease association prediction. Briefings in Bioinformatics, 2020, bbaa350, https://doi.org/10.1093/bib/bbaa350
  41. Wei Lan, Dehuan Lai, Qingfeng Chen, Ximin Wu, Baoshan Chen, Jin Liu, Jianxin Wang, Yiping Pheobe Chen. LDICDL: LncRNA-disease association identification based on Collaborative Deep Learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, DOI: 10.1109/TCBB.2020.3034910.
  42. Wei Lan, Ximin Wu, Qingfeng Chen, Wei Peng, Jianxin Wang, Yiping Phoebe Chen. GANLDA: Graph attention network for lncRNA-disease associations prediction. Neurocomputing. 2020
  43. Wei Lan, Mingrui Zhu, Qingfeng Chen, Baoshan Chen, Jin Liu, Min Li and Yi-ping Phoebe Chen. CircR2Cancer: A manually curated database of associations between circRNAs and cancers. Database, baaa085, 2020.
  44. Jin Liu, Guanxin Tan, Wei Lan, Jianxin Wang. Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks. BMC bioinformatics, 2020, 21 (6), 1-12.
  45. Jin Liu, Yu Sheng, Wei Lan, Rui Guo, Yufei Wang, Jianxin Wang. Improved ASD Classification using Dynamic Functional Connectivity and Multi-Task Feature Selection. Pattern Recognition Letters. 2020, 138, 82-87.
  46. Ximin Wu, Wei Lan*, Qingfeng Chen, Yi Dong, Jin Liu, Wei Peng. Inferring LncRNA-disease Associations Based On Graph Autoencoder Matrix Completion. Computational Biology and Chemistry. 2020, 107282.
  47. Wei Peng, Jielin Du, Lun Li, Wei Dai, Wei Lan. Predicting protein functions by using non-negative matrix factorisation with multi-networks co-regularisation. International Journal of Data Mining and Bioinformatics. 2020, 23(4) :318-342.
  48. Zhixian Liu, Qingfeng Chen, Wei Lan, Jiahai Liang, Yiping Pheobe Chen, Baoshan Chen. A Survey of Network Embedding for Drug Analysis and Prediction. Current protein & peptide science. 2020, DOI: 10.2174/1389203721666200702145701.
  49. Wei Peng, Lun Li, Wei Dai, Jielin Du, Wei Lan. Predicting protein functions through non-negative matrix factorization regularized by protein-protein interaction network and gene functional information. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 86-89.
  50. Qingfeng Chen, Zhe Zhao, Wei Lan*, Ruchang Zhang, Zhiqiang Wang, Cheng Luo, Yiping Pheobe Chen. Identifying MiRNA-disease association based on integrating miRNA topological similarity and functional similarity. Quantitative Biology. 2019, 1-8.
  51. Qingfeng Chen, Dehuan Lai, Wei Lan*, Ximin Wu, Jianxin Wang. ILDMSF: Inferring Associations between Long non-coding RNA and Disease Based on Multi-similarity Fusion. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019, PP(99):1-1.
  52. Qingfeng Chen, Zhe Zhao, Wei Lan*, Ruchang Zhang, Jiahai Liang. Predicting miRNA-disease interaction based on recommend method. Information Discovery and Delivery. 48(1) 35-40.
  53. Qingfeng Chen, Canshang Deng, Wei Lan*, Zhixian Liu, Ruiqing Zheng, Jin Liu, Jianxin Wang. Identifying Interactions Between Kinases and Substrates Based on Protein–Protein Interaction Network. Journal of Computational Biology. 2019, doi.org/10.1089/cmb.2019.0048.
  54. Jingzhong Gan, Jie Qiu, Canshang Deng, Wei Lan*, Qingfeng Chen, Yanling Hu. KSIMC: Predicting Kinase–Substrate Interactions Based on Matrix Completion. International Journal of Molecular Sciences. 2019, 20, 302.
  55. Canshang Deng, Qingfeng Chen, Zhixian Liu, Ruiqing Zheng, Jin Liu, Jianxin Wang, Wei Lan*. KSIBW: Predicting Kinase-Substrate Interactions Based on Bi-random Walk. In International Symposium on Bioinformatics Research and Applications, 151-162, 2018.
  56. Hui Jiang, Jianxin Wang, Min Li, Wei Lan, Fangxiang Wu, Yi Pan. miRTRS: A Recommendation Algorithm for Predicting miRNA Targets. IEEE/ACM transactions on computational biology and bioinformatics. PP(99):1-1, 2018.
  57. Haiqiong Luo, Wei Lan*, Qingfeng Chen, Zhiqiang Wang, Zhixian Liu, Xxiaofeng Yue, Lingzhi Zhu . Inferring microRNA-Environmental Factor Interactions Based on Multiple Biological Information Fusion. Molecules 23 (10), 2439.
  58. Wei Lan, Min Li, Kaijie Zhao, Jin Liu, Fangxiang Wu, Yi Pan, Jianxin Wang. LDAP: a web server for lncRNA-disease association prediction. Bioinformatics, 33 (3): 458-460, 2017.
  59. Cheng Yan, Jianxin Wang, Wei Lan, Fang-xiang Wu, Yi Pan.SDTRLS: Predicting Drug-Target Interactions for Complex Diseases Based on Chemical Substructures. Complexity, 2017(99):1-10.
  60. Cheng Yan, Jianxin Wang, Peng Ni, Wei Lan, Fang-xiang Wu, Yi Pan. DNRLMF-MDA: Predicting microRNA-disease associations based on similarities of microRNAs and disease. IEEE/ACM Transactions on Computational Biology and Bioinformatics PP(99):1-1, 2017.
  61. Jin Liu, Min Li, Yi Pan, Wei Lan, Ruiqing Zheng, Fang-Xiang Wu, Jianxin Wang. Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey. Complexity, 2017(2):1-27, 2017.
  62. Wei Peng, Wei Lan, Jiancheng Zhong, Jianxin Wang, Yi Pan. A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks. Methods, 124, 69-77, 2017.
  63. Wei Peng, Wei Lan, Jianxin Wang, Yi Pan. A Framework for integrating multiple biological networks to predict microRNA-disease associations. IEEE Transactions on NanoBioscience. 16(2), 100-107, 2017.
  64. Wei Lan, Jianxin Wang, Min Li, Jin Liu, Fangxiang Wu, Yi Pan. Predicting drug-target interaction using positive-unlabeled learning. Neurocomputing, 206, 50-57, 2016.
  65. Wei Lan, Jianxin Wang, Min Li, Jin Liu, Fangxiang Wu, Yi Pan. Predicting microRNA-disease associations based on improve miRNA and disease similarities. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016, doi: 10.1109/TCBB.2016.2586190
  66. Jin Liu, Min Li, Wei Lan, Fangxiang Wu, Yi Pan, Jianxin Wang. Classification of Alzheimer’s Disease based on Hierarchical Anatomical Whole Brain Network Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2016.
  67. Wei Lan, Jianxin Wang, Min Li, Chengqian Lu, Fangxiang Wu, Yi Pan. Predicting microRNA-environmental factor interactions based on multi-label learning. BIBM2016.
  68. Wei Peng, Wei Lan, Jianxin Wang, Yi Pan. Predicting MicroRNA-disease associations by walking on four biological networks. BIBM2016.
  69. Wei Peng, Wei Lan, Jianxin Wang, Yi Pan. Predicting MicroRNA-disease associations by random walking on multiple networks. ISBRA2016.
  70. Wei Lan, Jianxin Wang, Min Li, Wei Peng, Fangxiang Wu. Computational Approaches for Prioritizing Candidate Disease Genes Based on PPI Networks. Tsinghua Science and Technology, 20(5), 500-512, 2015.
  71. Wei Lan, Jianxin Wang, Min Li, Jin Liu, Fangxiang Wu, Yi Pan. Predicting microRNA-disease associations by integrating multiple biological information. In Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on, pp. 277-280. IEEE, 2015.
  72. Wei Lan, Jianxin Wang, Min Li, Ruiqing Zheng, Fangxiang Wu, Yi Pan. Predicting drug-target interaction based on sequence and structure information. 17th IFAC Symposium on System Identification SYSID 2015, IFAC-PapersOnLine , 48 (28): 12-16.
  73. Wei Lan, Qingfeng Chen, Taoshen Li, Changan Yuan, Scott Mann, Baoshan Chen. Identification of Important Positions within miRNAs by Integrating Sequential and Structural Features. Current Protein and Peptide Science, 15(6), 591-597, 2014.
  74. Qingfeng Chen, Wei Lan, Jianxin Wang. Mining Featured Patterns of MiRNA Interaction Based on Sequence and Structure Similarity. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(2), 415-422, 2013.
  75. Wei Lan, Qingfeng Chen, Taoshen Li. Discovery of MicroRNA conservative sites in drosophila melanogaster. Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on. Vol. 3. IEEE, 2011.

PROFESSIONAL ACTIVITY

Associate Editor

Frontiers in Genetics (2020-present)

Heliyon (2022-present)

Editorial Board Member

BMC Bioinformatics (2024-present)

BMC Medical Genomics (2022-present)

BMC Digital Health (2022-present)

BMC Medical Informatics and Decision Making (2021-present)

Frontiers in Bioscience-Landmark (2021-present)

BioMed Research International (2020-present)

Current Chinese Science (2020-present)

International Journal of Bioinformatics and Computational Biology (2018-present)

International Journal of Genetics and Genomics (2018-present)

Journal of Autonomous Intelligence (2017-present)

Guest Editor

Big Data Mining and Analytics (2024)

Frontiers in Bioscience-Landmark (2021）

Frontiers in Genetics (2020, 2023)

BMC Medical Genomics (2023)

BMC Medical Genomics (2023)

Publication Committee Chair

ICBSP (2023)

ICBBS (2022)

Poster Chair

ISBRA2024

Area Chair

CBC2024

Local organizing Committee Chair

ATAITS (2018)

Program committee member

BIBM2023, BIIP2023, CBC2023, IHB2023, NCCBB2023, ICAI2023, ECT2023, BIBM2022, BIIP2022, CBC2022, IHB2022, NCCBB2022, BIBM2021, BIIP2021, CBC2021, BIBM 2020, CBC2020, ICYCSEE 2020, BIBM 2019, CBC2019, ICYCSEE 2019, CBC2018, BIBM 2018, ISBRA2018, ICYCSEE2018

Reviewer

Briefings in Bioinformatics, PLOS Computational Biology, Bioinformatics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on cybernetics, ACM/IEEE Transactions on Computational Biology and Bioinformatics, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Nanobioscience, BMC Bioinformatics, Computational and Structural Biotechnology Journal, Cellular Physiology and Biochemistry, International Journal of Data Mining and Bioinformatics, Current bioinformatics, Interdisciplinary Sciences - Computational Life Sciences, Journal of Computer Science and Technology

Group

Current members

Cong Peng (2022)

Tongsheng Ling (2022)

Guoxian Zhou (2022)

Shengzu Huang (2022)

Wenhao Li (2023)

Zhentao Tang (2023)

Guohang He (2023)

Zekang Geng (2023)

Wenyi Chen (2023)

Dali Wang (2024)

Xiao Deng (2024)

Yasen Wang (2024)

Dong Wang (2024)

Tian Huang (2024)

Yinghao Guo (2024)

Yinhao Liu (2024)

Former members

Mingyang Liu (2021)

Weihao Zhou (2021)

Haibo Liao (2021)

Chunling Li (2021)

Wenguang Wang (2020)

Hongyu Zhang(2020)

Tianchuan Yang(2020)

Xun Sun (2020)

Jianwei Chen (2019)

Yi Dong (2019)

Mingrui Zhu (2018)

Ximin Wu (2018)

Contact

Email:lanwei@gxu.edu.cn