彭理

  • 性 别:
  • 职称:副教授
  • 学 历:博士研究生
  • 学院:计算机科学与工程学院
  • 系部所:计算机科学与技术系
  • 执教层次:硕士生导师
  • 电话:
  • 电子邮箱:6521982@qq.com

基本情况

彭理,博士,副教授,硕士生导师,中国计算机学会CCF会员,湖南科技大学高层次人才计划青年创新人才,湖南科技大学区块链与可信安全技术研究所所长。主要研究方向为人工智能、大模型、智能生物医学数据处理等。近年来,在Briefings in BioinformaticsTCBBBioinformatics等国内外重要期刊和会议上发表论文30余篇,申报国家发明专利和软件著作权多项。主持国家自然科学基金、湖南省自然科学基金、湖南省教育厅重点项目、优秀青年项目、湖南省教育厅教学改革研究等项目8项,参与国家重点研发计划、国家自然科学基金面上项目、湖南省自然科学基金等项目10余项。担任国家自然科学基金项目通讯评审专家、教育部学位论文通讯评审专家、湖南省科技计划项目评审专家,担任人工智能、生物信息学顶级期刊IEEE JBHIBIBTCBB等多家SCI期刊审稿人,担任IEEE BIBM等国际会议程序执行委员会委员。

 

研究生招生:

计算机科学与技术(学硕)和软件工程(学硕)、电子信息(专硕)

目前指导研究生9人,欢迎感兴趣的同学加入研究团队,优秀同学可推荐读博。

联系方式:6521982@qq.com



承担课程

人工智能导论、数据库系统、大数据技术与应用

主持课题

主要科研项目:

[1] 主持国家自然科学基金青年项目,61902125miRNA与疾病相互作用预测及其在非小细胞肺癌分析中的应用研究

[2] 主持湖南省自然科学基金面上项目,2023JJ30264,基于人工智能的药物小分子-新靶点计算分析方法研究

[3] 主持湖南省自然科学基金青年项目,2019JJ50187,基于深度学习的肿瘤关联miRNA 挖掘方法研究

[4] 主持湖南省教育厅重点项目,22A0350,基于多源异构数据融合的疾病相关circRNA深度挖掘方法研究

[5] 主持湖南省教育厅优秀青年科研项目,18B209,计算机辅助肿瘤相关 miRNA 识别算法的研究及应用

[6] 主持湖南省教育厅一般科研项目,14C0438,海量传感器网络感知数据的组织与管理研究

[7] 主持湖南省教育厅教学研究与改革项目,HNJG-2022-0786,“产学研用”深度融合的高校数据库课程教学模式研究与实践

[8] 主持湖南科技大学教学研究与改革项目,905-G31118,“市场需求”与“项目管理”双驱动下数据库系统课程教学改革

[9] 参与国家重点研发计划项目,2017YFB0202901,面向E级计算的能源勘探高性能应用软件系统与示范

[10] 参与国家自然科学基金面上项目,61572188,面向数字集成电路知识产权保护的PUF基础理论与实时检测技术研究

[11] 参与湖南省教育厅重点科研项目,14A407,适用于集成电路知识产权保护的鲁棒PUF技术研究

[12] 参与湖南省自然科学基金项目,13JJ3091,基于VLSI的双重芯核水印关键技术研究



代表性论文

[1] Li Peng, Junkai Gao, Zongyi Yang, Xinyi Ai and Wei Liang. Chemistry-Structure Dual-Perception Large Language Models: Advancing Molecular Property Prediction for Precise Disease Treatment. IEEE Journal of Biomedical and Health Informatics, 2026. (SCI)

[2] Li Peng, Wang Wang, Zongyi Yang, Xiangzheng Fu, Wei Liang, Dongsheng Cao. Leveraging explainable multi-scale features for fine-grained circRNA-miRNA interaction prediction. BMC biology, 2025. (SCI)

[3] Li Peng, Huaping Li, Sisi Yuan, Tao Meng, Yifan Chen, Xiangzheng Fu, Dongsheng Cao. metaCDA: A Novel Framework for CircRNA-Driven Drug Discovery Utilizing Adaptive Aggregation and Meta-Knowledge Learning. Journal of Chemical Information and Modeling. 2025. (SCI) 

[4] Li Peng,Cheng Yang, Jiahuai Yang, Yuan Tu, Qingchun Yu, Zejun Li, Min Chen, Wei Liang. Drug repositioning via Multi-view Representation Learning with Heterogeneous Graph Neural Network. IEEE Journal of Biomedical and Health Informatics. 2025. (SCI) 

[5] Li Peng,Wang Wang, Cheng Yang, Wenhui Xiao,Xiangzheng Fu, Yifan Chen. Dual-Stream Heterogeneous Graph Neural Network Based on Zero-Shot Embeddings for Predicting miRNA-Drug Sensitivity. 2024 IEEE International Conference on Bioinformatics and Biomedicine.(CCF B类会议) 

[6] Li Peng, Cheng Yang, Yifan Chen and Wei Liu. Predicting CircRNA-Disease associations via feature convolution learning with heterogeneous graph attention network. IEEE Journal of Biomedical and Health Informatics. 2023. (SCI)

[7] Li Peng, Yuan Tu, Li Huang, Yang Li, Xiangzheng Fu, Xiang Chen. DAESTB: Inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder. Briefings in Bioinformatics. 2022. (SCI)

[8] Li Peng, Cheng Yang, Li Huang, Xiang Chen, Xiangzheng Fu and Wei Liu. RNMFLP: Predicting circRNA–disease associations based on robust nonnegative matrix factorization and label propagation. Briefings in Bioinformatics. 2022. (SCI)

[9] Wei Liu, Ting Tang, Xu Lu, Xiangzheng Fu, Yu Yang, Li Peng(通讯作者). MPCLCDA: Predicting circRNA-disease associations by using automatically selected meta-path and contrastive learning. Briefings in Bioinformatics. 2023. (SCI) 

[10] Wei Liu, Yu Yang, Xu Lu, Xiangzheng Fu, Ruiqing Sun, Li Yang, Li Peng(通讯作者). NSRGRN: a network structure refinement method for gene regulatory network inference, Briefings in Bioinformatics. 2023 May 19;24(3):bbad129. (SCI) 

[11] Yuxun Luo, Shasha Li, Li Peng(通讯作者), Pingjian Ding, Wei Liang. Predicting associations between drugs and G protein-coupled receptors using a multi-graph convolutional network. Computational Biology and Chemistry. 2024. (SCI) 

[12] Yuhui Li, Wei Liang, Li Peng, Dafang Zhang, Cheng Yang, Kuan-Ching Li. Predicting Drug-Target Interactions via Dual-Stream Graph Neural Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2022.(SCI)

[13] Li Peng, Yujie Yang, Cheng Yang, Zejun Li, Ngai Cheong. HRGCNLDA: Forecasting of lncRNA-disease association based on hierarchical refinement graph convolutional neural network. Mathematical Biosciences and Engineering, 2024. (SCI)  

[14] Cheng Yang, Li Peng(通讯作者), Wei Liu, Xiangzheng Fu,Ni Li. Nonnegative Matrix Factorization Framework for disease-related CircRNA prediction. 2022. ICA3PP.

[15] Shuai Zhang, Xiang Chen, Li Peng(通讯作者). scIAMC:Single-Cell Imputation via adaptive matrix completion. IEEE EdgeCom 2023.

[16] Tao Huang, Xiang Chen, Li Peng(通讯作者). ESR:Optimizing Gene Feature Selection for scRNA-seq data. IEEE CSCloud 2023.

[17] Dejiang Wang, Zhuoran Zhai, Ngai Cheong, Li Peng. Script-Generated Picture Book Technology Based on Large Language Models and AIGC. 7th International Conference on Digital Technology in Education. ICDTE 2023. 

[18] Xiang Chen, Junnan Yu, Li Peng, Min Li. A deep graph convolution network with attention for clustering scRNA-seq data. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul, Turkiye, 2023. 

[19] Lijun Cai, Xuanbai Ren, Xiangzheng Fu, Li Peng, Mingyu Gao,Xiangxiang Zeng. iEnhancer-XG: interpretable sequence-based enhancers and their strength predictor. BIOINFORMATICS, 2020. (SCI)

[20] Li Peng, Dong Zhou, Wei Liu, Liqian Zhou, Lei Wang, Bihai Zhao, Jialiang Yang. Prioritizing Human Microbe-Disease Associations Utilizing a Node-Information-Based Link Propagation Method, IEEE Access, vol. 8, 2020.1 (SCI) 

[21] Li Peng, Manman Peng, Bo Liao, Guohua Huang*, Weibiao Li. The Advances and Challenges of Deep Learning Application in Biological Big Data Processing. Current bioinformatics.2018.13:352-359. (SCI)

[22] Li Peng, Manman Peng, Liao Bo, Wei Liang, Keqin Li. Improved low-rank matrix recovery method for predicting miRNA-disease association. Scientific Reports. 2017, 7(1):6007. (SCI)

[23] Li Peng, Manman Peng, Liao Bo, Qiu Xiao, Keqin Li. A novel information fusion strategy based on a regularized framework for identifying disease-related microRNAs. RSC Advance,2017,7(70). (SCI)


奖励荣誉

指导学生获得海峡两岸暨港澳地区大学生创新作品大赛全国总决赛一等奖、最佳创新赛、湖南省特等奖;

指导学生获得湖南省大学生创新创业大赛、人工智能创新大赛等省级奖励;

获评湖南科技大学教学优良榜、优秀硕导团队;


专利成果

专利与软件著作:

(1)     彭理,杨城. 一种基于图注意力的疾病相关环状RNA识别方法.专利号:ZL 2022 10714604.7, 2023

(2)     彭理,杨嘉怀,黎华平,王旺,肖文辉,梁伟. 一种基于多元域异构图聚合学习的药物和靶标相互作用预测方法. 专利号:ZL202410524760.6, 2025  

(3)     彭理,涂嫄,梁伟.  miRNA与疾病关联预测方法、设备及存储介质,专利号:ZL2023 10542486.0, 2025

(4)     彭理,杨雨洁,王旺,黎华平,杨嘉怀,梁伟. 基于层细化图卷积神经网络预测疾病lncRNA的方法.专利号:ZL 202311151750.4, 2026

(5)     彭理,高浚凯.一种基于双重感知大语言模型的分子性质预测方法. 专利号:20251085610.4

(6)     彭理,杨宗益,王振东,廉滋晨,周宇航.一种基于双通道稀疏注意力的抗菌肽预测方法. 专利号:202511378103.6

(7)     梁伟,谢思齐,靳恺,杨策,陈宇翔,彭理,张世文.用于用户注册的去中心化管理方法、系统以及存储介质. 专利号:202510226297.1

(8)     彭理,王旺,林艳柔,梁伟.一种基于多源特征提取的miRNA-circRNA预测方法、设备及介质. 专利号:202410917624.3.

(9)     彭理,黎华平,杨嘉怀,肖文辉,梁伟.一种基于元网络多跳注意力机制的疾病相关circRNA预测方法. 专利号:202410077856.2.

(10)  彭理,张帅.一种基于深度学习的scRNA-seq 缺失值填充方法.专利号:202310128876.3

(11)  大气粉尘远程监控系统软件v1.0,软著登记号:2015SR173767.

(12)  基于FPGA的健身游戏机系统软件v1.0, 软著登记号:2015SR171654.

(13)  基于Leap Motion的可穿戴鼠标模拟系统软件v1.0, 软著登记号:2015SR170475.

(14)  宿舍智能健康打卡监测系统,软著登记号:2022SR0983524.

(15)  胸腔X-ray肺炎检测系统,软著登记号:2023SR1254796

(16)  校园Chat社交软件,软著登记号:2023SR1014596