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陈鹏


陈鹏    



职 务: 课题组长(PI)
E-Mail:

 pchen.ustc10@yahoo.com

学科类别: 生物信息学,计算机应用

  个人主页:http://www2.ahu.edu.cn/pchen/

  学术主页:Google scholar

学习经历:

2007.12    中国科学技术大学                模式识别与智能系统     博士

2003.5     昆明理工大学                         控制理论与控制工程     硕士

1997.6     合肥解放军电子工程学院     电气自动化                     学士

工作经历:

2013.11-至今   安徽大学,课题组长/博导

2016.8-2016.9  海外,访问教授

2012-2014       海外,计算生物学博士后研究

2011.1-2013.1 中科院合肥智能机械研究所,副研究员,硕导/副博导

2008.4-2011.12012.6-2014.2 国外进行相关研究工作

2006.1-2006.7 香港城市大学,计算机系进化计算,高级研究助理

学术头衔:

Editorial Board Member:

    Journal of Computational Biology and Bioinformatics Research, JCBBR   (2013.5 - present);

    International   Journal on Data Mining and Intelligent Information Technology Applications,   IJMIA (2011 - present); 

    Journal   of Intelligent Learning Systems and Applications, JILSA (2012.11-present).

主要研究领域:

1.  机器学习与生物信息学

2.  药物筛选及系统生物学

3.  生物大数据分析

4.  深度学习及机器视觉应用


承担科研项目情况:

1.  2017年度安徽省留学人员科技活动项目择优资助(重点),2018.01-2019.12

2.  国家自然科学基金面上项目;蛋白质-配体相互作用的深度学习自动编码和随机映射研究(61672305)2017.01-2020.12

3.  国家自然科学基金青年基金;基于氨基酸序列协同进化编码的蛋白质热点残基预测(61300058)2014.01-2016.12

4.  安徽大学高层次人才引进科研启动资金;多态集成器及其基于蛋白质结构的药物靶点设计方法研究


代表论著:

近年来一直致力于机器学习算法设计及其在生物信息学上的应用,从蛋白质序列信息出发,提出了协同进化残基编码模式并成功应用到蛋白质-蛋白质相互作用位点识别、蛋白质热点残基识别以及蛋白质-配体结合位点的识别上,进一步推动了“序列-结构-功能”的研究进展。曾经在ProteinsIEEE/ACM TCBB FEBS LettersBMC Bioinfo Amino Acids等刊物上发表了50多篇学术论文,其中50余篇被SCI/EI检索,单篇引用次数最高达到137(Google Scholar Citation)。近年来发表的主要论文如下:

  1. Yanhua Qiao, Yi Xiong, Hongyun Gao, Xiaolei Zhu and Peng Chen*. Protein-Protein Interface Hot Spots Prediction Based on a Hybrid Feature Selection Strategy. BMC Bioinformatics. 2018;19(1):14

  2. Quanya Liu, Peng Chen*, Chun-Hou Zheng, Bing Wang. dbMPIKT: A kinetic and thermodynamic database of mutant protein interaction. BMC Bioinformatics. 2018;19(1):455

  3. Shanshan Hu, Peng Chen*, Bing Wang and Jinyan Li. Protein binding hot spots prediction from sequence only by a new ensemble learning method. Amino Acids. 2017; 49:1773-1785co-first author

  4. Jinjian Jiang, Nian Wang, Peng Chen*, Chun-Hou Zheng, Bing Wang. Prediction of protein hot spots from whole sequences by a random projection ensemble system. International Journal of Molecular Sciences. 2017; 18(7):1543

  5. Jun Zhang, Muchun Zhu, Peng Chen*, Bing Wang, DrugRPE: random projection ensemble approach to drug-target interaction prediction, Neurocomputing 2017, 228: 256-262

  6. Jun Zhang, Chun-Hou Zheng, Yi Xia, Bing Wang, Peng Chen*, Optimization Enhanced Genetic Algorithm-Support Vector Regression for the Prediction of Compound Retention Indices in Gas Chromatography, Neurocomputing. 2017; 240:183-190

  7. Z Wang, H Wang, J Tan, P Chen*, C Xie, Robust object tracking via multi-scale patch based sparse coding histogram. Multimedia Tools and Applications. 2017; 76:12181-12203

  8. Di Zhang, Peng Chen*, Chun-Hou Zheng, and Junfeng Xia, Identification of ovarian cancer subtype specific network modules and candidate drivers through an integrative genomics approach, Oncotarget. 2016, 7(4):4298-4309co-first author

  9. Peng Chen, B Wang, J Zhang, X Gao, J Li, and J Xia, A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2016, 13(5):901-912

  10. Bing Wang, Hao Shen, Aiqin Fang, De-shuang Huang, Changjun Jiang, Jun Zhang, Peng Chen*. A regression model for calculating the second dimension retennsion index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry, Journal of Chromatography A. 2016; 1451(17):127-134

  11. Chengjun Xie, Jie Zhang, Rui Li, Jinyan Li, Peilin Hong, Junfeng Xia, Peng Chen*, Automatic classification for field crop insects via multiple-task sparse representation and multiple-kernel learning. Computers and Electronics in Agriculture. 2015; 119:123-132

  12. Peng Chen, Jianhua Huang, Xin Gao, LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone. BMC bioinformatics 2014; 15(S15): S4

  13. Chengjun Xie, Jieqing Tan, Peng Chen*, Jie Zhang, Lei He. Multi-scale patch-based sparse appearance model for robust object tracking. Machine Vision and Applications. 2014; 25 (7), 1859-1876

  14. Chengjun Xie, Jieqing Tan, Peng Chen*, Jie Zhang, Lei He. Collaborative object tracking model with local sparse representation. Journal of Visual Communication and Image Representation. 2014;25 (2), 423-434.

  15. Chuan-Xi Li, Ru-Jing Wang, Peng Chen*, He Huang, Ya-Ru Su. Interaction Relation Ontology Learning. Journal of Computational Biology. 2014;21(1) ,80-88

  16. Peng Chen, Jinyan Li, Limsoon Wong, Hiroyuki Kuwahara, Jianhua Huang, Xin Gao. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences. Proteins. 2013; 81(8) ,1351-1362

  17. Chengjun Xie, Jieqing Tan, Peng Chen*, Jie Zhang, Lei He. A Multiple Instance Learning Tracking Method with Local Sparse Representation. IET Computer Vision. 2013; 7(5), 320-334

  18. 胡宜敏,宋良图,陈鹏*,魏圆圆,苏雅茹.一种基于Markov逻辑网的中文地理名称实体解析方法. 模式识别与人工智能. 201326(1):114-122

  19. Peng Chen, Limsoon Wong, Jinyan Li, Detection of Outlier Residues for Improving Interface Prediction in Protein Heterocomplexes. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2012; 9(4) :1155-1165

  20. Peng Chen, Jinyan Li, Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information. BMC bioinformatics. 2010;11 (1) :402

  21. Peng Chen, Chunmei Liu, Legand Burge, Jinyan Li, Mahmood Mohammad, William Southerland, Clay Gloster, Bing Wang, DomSVR: domain boundary prediction with support vector regression from sequence information alone. Amino Acids. 2010;39(3) :713-726

  22. Peng Chen, Jinyan Li, Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers. BMC structural biology. 2010;10(S1) : S2

  23. Bing Wang, Peng Chen*, De-Shuang Huang, Jing-jing Li, Tat-Ming Lok, Michael R Lyu, Predicting protein interaction sites from residue spatial sequence profile and evolution rate. FEBS letters.2006;580(2):380-384 co-first author

专利

  1. 基于数据挖掘的农田肥力数据采集分析系统。中国发明,授权号:CN201110344176.5,排名第1

  2. 一种用于农田多种气体实时在线监测装置。中国发明,授权号:CN201110418607.8,排名第5

  3. 土壤养分传感器。中国发明,授权号:CN201110344035.3,排名第7

  4. 车载拉曼光谱土壤检测仪。国家实用新型专利,授权号:CN201120523504.3,排名第5

  5. 车载农田土壤重金属激光诱导击穿光谱检测仪。国家实用新型专利,授权号:CN201120523461.9,排名第5






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