罗凌云，中科院软件所博士，凯斯西储大学博士后、访问学者，湖南省青年骨干教师，南华大学副教授、硕士研究生导师、十佳优秀教师。主要研究方向为人工智能及大数据技术在生物医学领域的应用，现任中文信息学会医疗知识图谱工作组执行委员，中国计算机学会会员。近年来，主持国家自然科学基金、湖南省自然科学基金、湖南省教育规划课题、湖南省教研教改课题等项目10余项，发表SCI收录论文30余篇。研究生招生要求：具备科研热情，有较强的逻辑思维能力、编程能力及英文写作能力，有自主学习的积极性，专业背景不限。联系方式：luoly<at>usc<dot>edu<dot>cn

近年主持项目（课题）

1. 湖南省自然科学基金面上项目，2025JJ50383，基于语义关系预测的生物医学本体质量评估理论与方法研究

2. 国家自然科学基金青年基金项目，61502221，大型复杂医学领域本体质量评估理论研究

3. 湖南省自然科学基金青年项目，2019JJ50520，医药本体中层次语义关系平衡度问题研究

4. 国家留学基金委地方合作项目，201708430227，“访问学者”计划

近3年发表论文

1. Luo H, Tang L, Zeng M, Yin R, Ding P, Luo L*, Li M*.  BertSNR: an interpretable deep learning framework for single nucleotide resolution identification of transcription factor binding sites based on DNA language model. Bioinformatics 2024. doi:10.1093/bioinformatics/btae461 (SCI)

2. Wu Z, Li S, Luo L, Ding P. HKFGCN: A novel multiple kernel fusion framework on graph convolutional network to predict microbe-drug associations. Comput. Biol. Chem. 110: 108041 . 2024 (SCI)

3. Hou A, Luo H, Liu H, Luo L*, Ding P. Multi-scale DNA language model improves 6 mA binding sites prediction. Comput. Biol. Chem. 112: 108129 . 2024 (SCI)

4. Luo Y,  Shan W, Peng L, Luo L, Ding P, Liang W. A Computational Framework for Predicting Novel Drug Indications Using Graph Convolutional Network With Contrastive Learning. IEEE J. Biomed. Health Informatics 28(8): 4503-4511. 2024 (SCI)

5. Zhong Y, Xi X, Shen C, Luo Y, Ding P, Luo L*. Multitask Joint Learning with Graph Autoencoders for Predicting Potential MiRNA-Drug Associations. Artificial Intelligence In Medicine. November 2023(145): 102665. (SCI)

6. Shan W, Shen C, Luo L, Ding P*. Multi-task Learning for Predicting Synergistic Drug Combinations based on Auto-Encoding Multi-Relational Graphs. iScience 26, 108020, October 20, 2023  (SCI)

7. Chen C, Luo L*, Zheng C, Ding P*, Liu H, Luo H. Self-prediction of relations in GO facilitates its quality auditing. J Biomed Inform. 2023 Aug;144:104441. doi: 10.1016/j.jbi.2023.104441. (SCI)

8. Luo H, Li Y, Liu H, Ding P, Yu Y, Luo L*. SENet: A deep learning framework for discriminating super- and typical enhancers by sequence information, Computational Biology and Chemistry, Volume 105, 2023,107905.107905. (SCI)

9. Luo Y, Peng L, Shan W, Sun M, Luo L, Liang W. Machine learning in the development of targeting microRNAs in human disease. Frontiers in Genetics, January 2023.  (SCI)

10. Luo H, Shan W, Chen C, Ding P, Luo L*. Improving language model of human genome for DNA-protein binding prediction based on task-specific pre-training. Interdisciplinary Sciences: Computational Life Sciences. 2023 Mar;15(1):32-43.doi: 10.1007/s12539-022-00537-9. PMID: 36136096. (SCI)

11. Luo H, Chen C, Shan W, Ding P, Luo L*. iEnhancer-BERT: A novel transfer learning architecture based on DNA-language model for identifying enhancers and their strength. International Conference on Intelligent Computing August 7-11, 2022, Xi’an, China (CCF)

12. Zhong Y, Shen C, Wu H, Xu T, Luo L*. Improving the prediction of potential kinase inhibitors with feature learning on multisource knowledge. Interdisciplinary Sciences: Computational Life Sciences. 2022 Sep;14(3):775-785. doi: 10.1007/s12539-022-00523-1. PMID: 35536538.  (SCI)