更新日期：2025年2月27日
个人简介
刘锐，教授、博士生导师、数学学院副院长、长江学者特聘教授。
2001年9月至2010年6月在北京大学数学学院本硕博连读。2010年9月至2012年9月在日本东京大学生产技术研究所做博士后，2014年7月至2015年7月在美国斯坦福大学医学院做博士后，2017年9月至2018年9月在美国加州大学洛杉机分校医学院学术访问。2013年9月晋升副教授，2016年4月晋升教授。2019年起任广州市工业与应用数学学会副理事长、广东省工业与应用数学学会常务理事；2022年起任广东省数字孪生人重点实验室副主任。
工作经历
博士后工作经历：
2010/9 – 2012/9， 日本东京大学， 生产技术研究所， 博士后
2014/6 – 2015/7， 美国斯坦福大学， 医学院， 博士后
教师工作经历：
2010/7 – 2013/8， 华南理工大学， 数学学院， 讲师
2013/9 – 2016/3， 华南理工大学， 数学学院， 副教授
2016/4 – 现在， 华南理工大学， 数学学院， 教授
教育经历
2001/9 - 2005/7，北京大学数学科学学院，应用数学专业，本科；
2005/9 - 2010/7，北京大学数学科学学院，应用数学专业，博士；
获奖、荣誉称号
2024年入选教育部长江学者奖励计划特聘教授；
2023年获得广东省自然科学二等奖。成果名称：生物趋向性运动的数学理论，第二完成人；
2023年第十八届“挑战杯”全国大学生课外学术科技作品竞赛一等奖指导教师；
2023年第十七届“挑战杯”广东大学生课外学术科技作品竞赛特等奖指导教师，获得广东省大学生“挑战杯”学术科技竞赛“优秀指导教师” 称号；
2021年获得上海市自然科学一等奖。成果名称：动力学驱动的数据科学理论和方法研究，第三完成人；
2020年入选教育部长江学者奖励计划青年学者；
2020年获得华南理工大学“教学优秀奖”；
2019年获得广东省杰出青年基金；
2019年获得全国大学生创新创业训练计划“优秀指导教师”奖励；
2019年第十六届“挑战杯”全国大学生课外学术科技作品竞赛一等奖指导教师；
2019年第十五届“挑战杯”广东大学生课外学术科技作品竞赛特等奖指导教师，获得广东省大学生“挑战杯”学术科技竞赛“优秀指导教师” 称号；
2016年获得广州市“珠江科技新星”称号；
社会、学会及学术兼职
广东省数字孪生人重点实验室副主任
广东省工业与应用数学学会常务理事
广州市工业与应用数学学会副理事长
研究领域
主要研究方向：计算生物学与生物信息学、非线性动力系统。
研究内容：主要在非线性动力学分析、高维数据挖掘、时间序列分析的人工智能算法、动力系统的分岔现象、复杂生物过程的临界点分析与预警、生物分子网络的推断与分析等几个方面发展数学理论与数据驱动的计算方法。
招生方向：应用数学、计算数学。
欢迎对数据挖掘与分析、网络模型、机器学习和深度学习方法感兴趣，并具有一定编程基础（例如MATLAB、R或Python等）的同学报考硕士或博士研究生。欢迎已取得和将要取得博士学位的青年学者做博士后研究，博士后待遇及其他详情请见：http://www2.scut.edu.cn/hr/2019/1016/c4457a340019/page.htm 。
科研项目
主持项目：
[9] 主持国家自然科学基金委原创探索项目“基于时空信息转换的异常事件预警理论与模型” (项目号：42450084)。
[8] 主持国家自然科学基金委交叉学部 “未病”状态表征与机制研究专项 (项目号：T2341022)。
[7] 主持国家自然科学基金委面上基金项目“基于动力学和分子组学数据的复杂疾病临界状态研究” (项目编号：62172164)。
[6] 主持国家自然科学基金委“数学与医疗健康交叉”重点专项“典型肺疾病的早期预警、病程演进建模与治疗方案优化” (项目编号：12026608，已结题)。
[5] 主持广东省杰出青年基金人才项目 (项目编号：2019B151502062，已结题)。
[4] 主持国家自然科学基金委面上基金项目“基于高维、大噪声、小样本数据的复杂疾病恶性突变信号的挖掘与利用” (项目编号：11771152，已结题)。
[3] 主持广州市“珠江科技新星”人才项目 (项目编号：201610010029，已结题)。
[2] 主持国家自然科学基金委青年基金项目“预测某些疾病恶性突变的数学生物方法研究” (项目编号：11401222，已结题)。
[1] 主持国家自然科学基金委主任基金项目“动力系统方法与某些复杂疾病恶性突变的早期预警信号” (项目编号：11241002，已结题)。
参与项目：
[3] 参加国家自然科学基金委重点项目“2型糖尿病发生发展过程的临界状态预测理论和生物信息学方法”（项目编号：31930022，已结题）。
[2] 参加国家自然科学基金委重大研发计划集成项目“基于动态网络的复杂疾病分析理论与方法”（项目编号：91530320，已结题）。
[1] 参加国家自然科学基金委重点项目“动脉粥样硬化发生发展过程中关键节点和调控网络的系统生物学研究”（项目编号：91439103，已结题）。
发表论文
[68] Hao Peng, Pei Chen, Rui Liu*, Luonan Chen*. One-core neuron deep learning for time series prediction. National Science Review, 2025, 12(2): nwae441. https://doi.org/10.1093/nsr/nwae441
[67] Renhao Hong, Yuyan Tong, Hui Tang*, Tao Zeng*, Rui Liu*. eMCI: an explainable multimodal correlation integration model for unveiling spatial transcriptomics and intercellular signaling. Research, 2024, 7:0522. https://doi.org/10.34133/research.0522
[66] Hao Peng, Wei Wang, Pei Chen*, Rui Liu*, DEFM: Delay-embedding-based forecast machine for time series forecasting by spatiotemporal information transformation. Chaos, 2024, 34:043112. https://doi.org/10.1063/5.0181791
[65] Yunlong Li, Zhiyuan Liu, Ping Wang, Xuerong Gu, Fei Ling, Jiayuan Zhong, Dong Yin*, Rui Liu*, Xueqing Yao*, Chengzhi Huang*. Bioengineered extracellular vesicles delivering siMDM2 sensitize oxaliplatin therapy efficacy in colorectal cancer. Advanced Healthcare Materials, 2024, 2403531. https://doi.org/10.1002/adhm.202403531
[64] Renhao Hong, Yuyan Tong, Huisheng Liu, Pei Chen*, Rui Liu*. Edge-based relative entropy as a sensitive indicator of critical transitions in biological systems. Journal of Translational Medicine, 2024, 22:333. https://doi/org/10.1186/s12967-024-05145-3
[63] Hao Peng, Pei Chen*, Rui Liu*, Luonan Chen*. Spatiotemporal information conversion machine for time-series forecasting. Fundamental Research, 2024, 4(6):1674–1687. https://doi.org/10.1016/j.fmre.2022.12.009
[62] Hui Tang, Jiayuan Zhong, Xiangtian Yu, Hua Chai, Rui Liu*, Tao Zeng*. Exploring structured molecular landscape from single-cell multi-omics data by an explainable multimodal model. iScience, 2024, 27(12):111131. https://doi.org/10.1016/j.isci.2024.111131
[61] Jiayuan Zhong, Hui Tang, Ziyi Huang, Hua Chai, Fei Ling*, Pei Chen*, Rui Liu*. Uncovering the pre-deterioration state during disease progression based on sample-specific causality network entropy (SCNE). Research, 2024, 7:0368. https://doi.org/10.34133/research.0368
[60] Yuyan Tong, Renhao Hong, Ze Zhang, Kazuyuki Aihara, Pei Chen*, Rui Liu*, Luonan Chen*. Earthquake alerting based on spatial geodetic data by spatiotemporal information transformation learning. Proceedings of the National Academy of Sciences, USA, 2023, 120(37):e2302275120. https://doi.org/10.1073/pnas.2302275120
[59] Jiayuan Zhong, Chongyin Han, Pei Chen*, Rui Liu*. SGAE: single-cell gene association entropy for revealing critical states of cell transitions during embryonic development. Briefings in Bioinformatics, 2023, 24(6):bbad366. https://doi.org/10.1093/bib/bbad366
[58] Zhenggang Zhong, Jiabao Li, Jiayuan Zhong, Yilin Huang, Jiaqi Hu, Piao Zhang, Baowen Zhang, Yabin Jin, Wei Luo*, Rui Liu*, Yuhu Zhang*, Fei Ling*. MAPKAPK2, a potential dynamic network biomarker of α-synuclein prior to its aggregation in PD patients. npj Pakinson's Disease, 2023, 9:41. https://doi.org/10.1038/s41531-023-00479-z
[57] Xiaoqi Huang, Chongyin Han, Jiayuan Zhong, Jiaqi Hu, Yabin Jin, Qinqin Zhang, Wei Luo*, Rui Liu*, Fei Ling*. Low expression of the dynamic network markers FOS/JUN in pre-deteriorated epithelial cells is associated with the progression of colorectal adenoma to carcinoma. Journal of Translational Medicine, 2023, 21:45. https://doi.org/10.1186/s12967-023-03890-5
[56] Baoyin Yuan, Rui Liu*, Sanyi Tang*. Assessing the transmissibility of epidemics involving epidemic zoning. BMC Infectious Diseases, 2023, 23:242. https://doi.org/10.1186/s12879-023-08205-z
[55] Jin Liu, Yang Zhou, Haozhang Huang, Rui Liu, Yu Kang et al. Impact of stress hyperglycemia ratio on mortality in patients with critical acute myocardial infarction: insight from american MIMIC-IV and the chinese CIN-II study. Cardiovascular Diabetology, 2023, 22:281. https://doi.org/10.1186/s12933-023-02012-1
[54] Jiayuan Zhong, Chongyin Han, Yangkai Wang, Pei Chen*, Rui Liu*. Identifying the critical state of complex biological systems by the directed-network rank score method. Bioinformatics, 2022, 38(24):5398–5405. https://doi.org/10.1093/bioinformatics/btac707
[53] Pei Chen, Jiayuan Zhong, Kun Yang, Xuhang Zhang, Yingqi Chen, Rui Liu*. TPD: a web tool for tipping-point detection based on dynamic network biomarker. Briefings in Bioinformatics, 2022, 23(5):bbac399. https://doi.org/10.1093/bib/bbac399
[52] Hao Peng, Jiayuan Zhong, Pei Chen*, Rui Liu*. Identifying the critical states of complex diseases by the dynamic change of multivariate distribution. Briefings in Bioinformatics, 2022, 23(5):bbac177. https://doi.org/10.1093/bib/bbac177
[51] Baoyin Yuan, Rui Liu*, Sanyi Tang*. A quantitative method to project the probability of the end of an epidemic: Application to the COVID-19 outbreak in Wuhan, 2020. Journal of Theoretical Biology, 2022, 545:111149. https://doi.org/10.1016/j.jtbi.2022.111149
[50] Juntan Liu, Dandan Ding, Jiayuan Zhong*, Rui Liu*. Identifying the critical states and dynamic network biomarkers of cancers based on network entropy. Journal of Translational Medicine, 2022, 20:254. https://doi.org/10.1186/s12967-022-03445-0
[49] Hui Tang, Xiangtian Yu, Rui Liu*, Tao Zeng*. Vec2image: an explainable artificial intelligence model for the feature representation and classification of high-dimensional biological data by vector-to-image conversion. Briefings in Bioinformatics, 2022, 23(2):bbab584. https://doi.org/10.1093/bib/bbab584
[48] Kazuyuki Aihara*, Rui Liu, Keiichi Koizumi, Xiaoping Liu, Luonan Chen*. Dynamical network biomarkers: theory and applications. Gene, 2022, 808:145997. https://doi.org/10.1016/j.gene.2021.145997
[47] Lin Li, Hui Tang, Rui Xia, Dai Hao, Rui Liu, Luonan Chen*. Intrinsic entropy model for feature selection of scRNA-seq data. Journal of Molecular Cell Biology, 2022, 14(2):mjac008. https://doi.org/10.1093/jmcb/mjac008
[46] Rui Liu, Jiayuan Zhong, Renhao Hong, Ely Chen, Kazuyuki Aihara, Pei Chen*, Luonan Chen*. Predicting local COVID-19 outbreaks and infectious disease epidemics based on landscape network entropy. Science Bulletin, 2021, 66(22): 2265–2270. https://doi.org/10.1016/j.scib.2021.03.022
[45] Jiayuan Zhong, Chongyin Han, Xuhang Zhang, Pei Chen*, Rui Liu*. SGE: Predicting cell fate commitment during early embryonic development by single-cell graph entropy. Genomics, Proteomics & Bioinformatics, 2021, 19(3):461–474. https://doi.org/10.1016/j.gpb.2020.11.008
[44] Rui Liu, Kazuyuki Aihara*, Luonan Chen*. Collective fluctuation implies imminent state transition, Comment on "Dynamic and thermodynamic models of adaptation" by AN Gorban et al. Physics of Life Reviews, 2021, 37:103–107. https://doi.org/10.1016/j.plrev.2021.04.002
[43] Huisheng Liu, Jiayuan Zhong, Jiaqi Hu, Chongyin Han, Rui Li, Xueqing Yao, Shiping Liu, Pei Chen, Rui Liu*, Fei Ling*. Single-cell transcriptome analysis reveals DHX9 in mature B cell as a dynamic network biomarker before lymph node metastasis in colorectal adjacent tissues. Molecular Therapy Oncolytics, 2021, 22:495–506. https://doi.org/10.1016/j.omto.2021.06.004
[42] Min Dong, Xuhang Zhang, Kun Yang, Rui Liu*, Pei Chen*. Forecasting the COVID-19 transmission in Italy based on the minimum spanning tree of dynamic region network. PeerJ, 2021, 9:e11603. https://doi.org/10.7717/peerj.11603
[41] Xuhang Zhang, Rong Xie, Zhengrong Liu, Yucong Pan, Rui Liu*, Pei Chen*. Identifying pre-outbreak signals of hand, foot and mouth disease based on landscape dynamic network marker. BMC Infectious Diseases, 2021, 21:6. https://doi.org/10.1186/s12879-020-05709-w
[40] Pei Chen, Rui Liu*, Kazuyuki Aihara, Luonan Chen*. Autoreservoir computing for multistep ahead prediction based on the spatiotemporal information transformation. Nature Communications, 2020, 11(4568). https://doi.org/10.1038/s41467-020-18381-0
[39] Rui Liu, Pei Chen*, Luonan Chen*. Single-sample landscape entropy reveals the imminent phase transition during disease progression. Bioinformatics, 2020, 36(5):1522–1532. https://doi.org/10.1093/bioinformatics/btz758
[38] Chongyin Han, Jiayuan Zhong, Jiaqi Hu, Huisheng Liu, Rui Liu*, Fei Ling*. Single-sample node entropy for molecular transition in pre-deterioration stage of cancer. Frontiers in Bioengineering and Biotechnology, 2020, 8:809. https://doi.org/10.3389/fbioe.2020.00809
[37] Jiayuan Zhong, Rui Liu*, Pei Chen*. Identifying critical state of complex diseases by single-sample Kullback–Leibler divergence, BMC Genomics, 2020, 21(1):87. https://doi.org/10.1186/s12864-020-6490-7
[36] Pei Chen, Shuo Li, Wenyuan Li, Jie Ren, Fengzhu Sun, Rui Liu*, Xianghong Jasmine Zhou*. Rapid diagnosis and comprehensive bacteria profiling of sepsis based on cell-free DNA. Journal of Translational Medicine, 2020, 18(5). https://doi.org/10.1186/s12967-019-02186-x
[35] Tianlong Liu, Hongyan Wen, Hao Li, Haochen Xu, Ning Xiao, Rui Liu, Luonan Chen et al. Oleic acid attenuates Ang II (Angiotensin II)-induced cardiac remodeling by inhibiting FGF23 (fibroblast growth factor 23) expression in mice. Hypertension, 2020, 75(3): 680–692. https://doi.org/10.1161/HYPERTENSIONAHA.119.14167
[34] Jiaopeng Yang, Rui Liu, Yiren Chen. Bifurcations of solitary waves of a simple equation. International Journal of Bifurcation and Chaos, 2020, 30(9), 2050138. https://doi.org/10.1142/S0218127420501382
[33] Zongguang Li, Rui Liu*. Blow-up solutions for a case of b-family equations. Acta Mathematica Scientia, 2020, 40(4): 910-920. https://doi.org/10.1007/s10473-020
[32] Yingqi Chen, Kun Yang, Jialiu Xie, Rong Xie, Zhengrong Liu, Rui Liu*, Pei Chen*. Detecting the outbreak of influenza based on the shortest path of dynamic city network. PeerJ, 2020, 8: e9432. https://doi.org/10.7717/peerj.9432
[31] Kun Yang, Jialiu Xie, Rong Xie, Yucong Pan, Rui Liu*, Pei Chen*. Real-time forecast of influenza outbreak using dynamic network marker based on minimum spanning tree. BioMed Research International, 2020, 2020:7351398, 1–11. https://doi.org/10.1155/2020/7351398
[30] Zongguang Li, Rui Liu*. Bifurcations and exact solutions in a nonlinear wave equation. International Journal of Bifurcation and Chaos, 2019, 29(7):1950098. https://doi.org/10.1142/S0218127419500986
[29] Rui Liu, Jinzeng Wang, Masao Ukai, Ki Sewon, Pei Chen, Yutaka Suzuki, Haiyun Wang*, Kazuyuki Aihara*, Mariko Okada-Hatakeyama*, Luonan Chen*. Hunt for the tipping point during endocrine resistance process in breast cancer by dynamic network biomarkers. Journal of Molecular Cell Biology, 2019, 11(8): 649–664. https://doi.org/10.1093/jmcb/mjy059
[28] Pei Chen, Ely Chen, Luonan Chen, Xianghong Jasmine Zhou*, Rui Liu*. Detecting early-warning signals of influenza outbreak based on dynamic network marker. Journal of Cellular and Molecular Medicine, 2019, 23(1): 395–404. https://doi.org/10.1111/jcmm.13943
[27] Rui Liu, Jiayuan Zhong, Xiangtian Yu, Yongjun Li, Pei Chen*. Identifying critical state of complex diseases by single-sample-based hidden Markov model. Frontiers in Genetics, 2019, 10:285. https://doi.org/10.3389/fgene.2019.00285
[26] Pei Chen, Yongjun Li, Xiaoping Liu, Rui Liu*, Luonan Chen*. Detecting the tipping points in a three-state model of complex diseases by temporal differential networks. Journal of Translational Medicine, 2017, 15:217. https://doi.org/10.1186/s12967-017-1320-7
[25] Xiaoping Liu, Xiao Chang, Rui Liu, Xiangtian Yu, Luonan Chen, Kazuyuki Aihara. Quantifying critical states of complex diseases using single-sample dynamic network biomarkers. PLoS Computational Biology, 2017, 13(7): e1005633. https://doi.org/10.1371/journal.pcbi.1005633
[24] Bo Jin, Rui Liu, Shiying Hao, et al. Defining and characterizing the critical transition state prior to the type 2 diabetes disease. PLoS ONE, 2017, 12(7): e0180937. https://doi.org/10.1371/journal.pone.0180937
[23] Pei Chen, Rui Liu, Yongjun Li, Luonan Chen. Detecting critical state before phase transition of complex biological systems by hidden Markov model. Bioinformatics, 2016, 32(14): 2143–2150. https://doi.org/10.1093/bioinformatics/btw154
[22] Yiren Chen, Weibo Ye, Rui Liu*. The explicit periodic wave solutions and their limit forms for a generalized b-equation. Acta Mathematicae Applicatae Sinica, 2016, 32(2): 513–528. https://doi.org/10.1007/s10255-016-0581-x
[21] Pei Chen, Rui Liu, Kazuyuki Aihara, Luonan Chen. Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers. Frontiers in Genetics, 2015, 6:252. https://doi.org/10.3389/fgene.2015.00252
[20] Rui Liu, Pei Chen, Kazuyuki Aihara, Luonan Chen. Identifying early-warning signals of critical transitions with strong noise by dynamical network markers. Scientific Reports, 2015, 5:17501. https://doi.org/10.1038/srep17501
[19] Zhou Tan, Rui Liu, Le Zheng, et al. Cerebrospinal fluid protein dynamic driver network: At the crossroads of brain tumorigenesis. Methods, 2015, 83: 36–43. https://doi.org/10.1016/j. ymeth.2015.05.004
[18] Yiren Chen, Rui Liu*. Some new nonlinear wave solutions for two (3+1)-dimensional equations. Applied Mathematics and Computation, 2015, 260: 397–411. https://doi.org/10.1016/j.amc.2015.03.098
[17] Weifang Yan, Rui Liu. Traveling wave solutions in n-dimensional delayed nonlocal diffusion system with mixed quasimonotonicity. Analysis and Applications, 2015, 13(1): 23–43. https://doi.org/10.1142/S0219530514500055
[16] Yue Wang, Jin Luo, Shiying Hao, Haihua Xu, Andrew Young Shin, Bo Jin, Rui Liu et al. NLP based congestive heart failure case finding: A prospective analysis on statewide electronic medical records. International journal of medical informatics, 2015, 84(12): 1039–1047. https://doi.org/10.1016/j.ijmedinf.2015.06.007
[15] Rui Liu, Xiangtian Yu, Xiaoping Liu, Dong Xu, Kazuyuki Aihara, Luonan Chen. Identifying critical transitions of complex diseases based on a single sample. Bioinformatics, 2014, 30(11): 1579–1586. https://doi.org/10.1093/bioinformatics/btu084
[14] Rui Liu, Xiangdong Wang, Kazuyuki Aihara, Luonan Chen. Early diagnosis of complex diseases by molecular biomarkers, network biomarkers, and dynamical network biomarkers. Medicinal Research Reviews, 2014, 34(3): 455–478. https://doi.org/10.1002/med.21293
[13] Meiyi Li, Tao Zeng, Rui Liu, Luonan Chen. Detecting tissue-specific early warning signals for complex diseases based on dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis. Briefings in Bioinformatics, 2014, 15(2): 229–243. https://doi.org/10.1093/bib/bbt027
[12] Tao Zeng, Wanwei Zhang, Xiangtian Yu, Xiaoping Liu, Meiyi Li, Rui Liu, Luonan Chen. Edge biomarkers for classification and prediction of phenotypes. Science China Life Sciences, 2014, 57(11): 1103–1114. https://doi.org/10.1007/s11427-014–4757-4
[11] Tao Zeng, Chuanchao Zhang, Wanwei Zhang, Rui Liu, Juan Liu, Luonan Chen. Deciphering early development of complex diseases by progressive module network. Methods, 2014, 67(3): 334–343. https://doi.org/10.1016/j.ymeth.2014.01.021
[10] Xiaoping Liu, Rui Liu, Xingming Zhao, Luonan Chen. Detecting early-warning signals of type 1 diabetes and its leading biomolecular networks by dynamical network biomarkers. BMC Medical Genomics, 2013, S6. https://doi.org/10.1186/1755-8794-6-S2-S8
[9] Rui Liu, Weifang Yan. Some common expressions and new bifurcation phenomena for nonlinear waves in a generalized mKdV equation. International Journal of Bifurcation and Chaos, 2013, 23(3): 13330007. https://doi.org/10.1142/S0218127413300073
[8] Rui Liu. The explicit nonlinear wave solutions of the generalized b-equation. Communications on Pure and Applied Analysis, 2013, 12(2): 1029–1047. DOI:10.3934/cpaa.2013.12.1029
[7] Rui Liu, Kazuyuki Aihara, Luonan Chen. Dynamical network biomarkers for identifying critical transitions and their driving networks of biologic processes. Quantitative Biology, 2013, 1(2):105–114. https://doi.org/10.1007/s40484-013-0008-0
[6] Weifang Yan, Rui Liu. Existence and critical speed of traveling wave fronts in a modified vector disease model with distributed delay. Journal of Dynamical and Control Systems, 2012, 18(3): 355–378. https://doi.org/10.1007/s10883-012-9148-1
[5] Luonan Chen, Rui Liu, Zhi-Ping Liu, Meiyi Li, Kazuyuki Aihara. Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers. Scientific Reports, 2012, 2:342. https://doi.org/10.1038/srep00342
[4] Rui Liu, Meiyi Li, Zhi-Ping Liu, Jiarui Wu, Luonan Chen, Kazuyuki Aihara. Identifying critical transitions and their leading biomolecular networks in complex diseases. Scientific Reports, 2012, 2:813. https://doi.org/10.1038/srep00813
[3] Rui Liu. Coexistence of multifarious exact nonlinear wave solutions for generalized b-equation. International Journal of Bifurcation and Chaos, 2010, 20(10): 3193–3208. https://doi.org/10.1142/S0218127410027623
[2] Rui Liu. Some new results on explicit traveling wave solutions of k(m, n) equation. Discrete and Continuous Dynamical Systems-Series B, 2010, 13(3): 633–646. https://doi.org/10.3934/dcdsb.2010.13.633
[1] Rui Liu. Several new types of solitary wave solutions for the generalized Camassa- Holm-Degasperis-Procesi equation. Communications on Pure and Applied Analysis, 2010, 9(1): 77–90. https://doi.org/10.3934/cpaa.2010.9.77
出版专著和教材
[3] 动力学刻画的数据科学理论与方法。陈洛南，刘锐，马欢飞，史际帆，动力学刻画的数据科学理论与方法，科学出版社，北京，2024年，ISBN 978-7-5088-6449-5。
[2] 雷锦志，易鸣，杨凌，刘锐，祁宏。系统生物学，科学出版社，北京，2024年，ISBN 978-7-03-077449-1。
[1] Phase Plane Analysis and Numerical Simulation of Wave Equations. 刘锐，陈培，科学出版社，北京，2022年，ISBN 978-7-03-073046-6。
科研创新
[8] 授权中国发明专利，专利名称：基于单样本sKLD指标检测复杂生物系统相变临界点的方法；授权时间：2023年4月21日；授权专利号：ZL201911142801.0 。
[7] 授权中国发明专利，专利名称：一种基于相对熵指标检测复杂生物系统相变临界点的方法；授权时间：2023年4月21日；授权专利号：ZL202010025627.8
[6] 授权中国发明专利，专利名称：基于最小生成树动态网络标志物的城市流感爆发预测方法；授权时间：2022年9月7日；授权专利号：ZL202010730222.4。
[5] 美国授权专利，专利名称：Detection device, method, and program for as-sisting network entropy-based detection of pre-cursor to state transition of biological object；授权时间：2019年10月1日；授权专利号：US 10,431,341B2；
[4] 授权中国发明专利，专利名称：用于对前疾病状态进行检测的检测装置；授权时间：2018年11月9日；授权专利号：ZL201410027769.2。
[3] 软件著作权，软件名称：利用隐马尔可夫模型算法监测生物过程的临界点软件V1.0；登记证书颁发日期：2018年7月10日；证书编号：软著登字第2865696号；
[2] 日本授权专利，专利名称： ネットワークエントロピーに基づく生体の状態遷移の予兆の検出を支援する検出装置、検出方法及び検出プログラム；発行日：2017.7.19；特許番号（专利号）：特許第6164678号 (P6164678)；
[1] 日本授权专利，专利名称： 動的ネットワークバイオマーカーの検出装置、検出方法及び検出プログラム；発行日：2016.7.8；特許番号（专利号）：特許第5963198号(P5963198)；
教学活动
主讲过《常微分方程》、《微分方程定性方法与数值模拟（全英课程）》、《线性代数与解析几何（全英课程）》、《数据结构课程设计》等本科生课程；
开设了《计算生物学导论》、《微分方程定性理论》、《现代数学基础》、《数据挖掘技术在数学生物学中的应用》、《数学生物学中的某些理论、方法及应用》等研究生课程。
指导学生情况
已毕业学生：吕欣（2015级硕士）；易培元（2015级硕士）；黄煜林（2016级硕士）；王年赢（2016级硕士）；关小玲（2016级硕士）；王阳开（2017级硕士）；邹玲玲（2017级硕士）；沈子凡（2018级硕士）；朱赟（2018级硕士）；王俊霞（2018级硕士）；马硕（2019级硕士）；钟佳元（2019级博士）；李明章（2020级硕士）；梁鑫（2020级硕士）；熊家逸（2021级硕士）。
在校学生：彭昊（2020级博士）；童宇燕（2019级硕士，2021级博士）；洪仁豪（2019级硕士，2021级博士）；杨娜（2022级博士）；张奇彬（2024级博士）；刘晓贝（2024级博士）；庄晓晴（2022级硕士）；黎俊贤（2022级硕士）；王葳（2022级硕士）；蔡思花（2023级硕士）；杨茜然（2023级硕士）；宋丽仪（2024级硕士）。
我的团队
数学学院 陈培 教授