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Home Research Publication Software Links	Publications: (* Correspondence Author) 2021年： 109. Peng Chen, Weilu Li, Sijie Yao, Chun Ma, Chunhou Zheng, Jun Zhang, Chengjun Xie, Bing Wang, Dong Liang, Recognition and Counting of Wheat Mites in Wheat Fields by A Three-Step Deep Learning Method. Neurocomputing 2021, 437: 21-30. (SCI, JCR二区） 108. ShanShan Hu, DeNan Xia, Benyue Su, Peng Chen, Bing Wang and Jinyan Li, A Convolutional Neural Network System to Discriminate Drug-Target Interactions. IEEE/ACM Transactions on Computational Biology and Bioinformatics* 2021, 18(4): 1315 - 1324. in print. (SCI, JCR二区） 107. Bing Wang, Changqing Mei, Yuanyuan Wan, Jun Zhang, Peng Chen, Yan Xiong, Imbalance Data Processing Strategy for Protein Interaction Sites Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2021, 18(3): 985 - 994. in print. (SCI, JCR二区） 106. Wenyan Wang, Yuming Zhou, Mu-Tian Cheng, Yan Wang, Chun-Hou Zheng, Yan Xiong, Peng Chen, Zhiwei Ji, Bing Wang, Potential Pathogenic Genes Prioritization Based on Protein Domain Interaction Network Analysis, IEEE/ACM Transactions on Computational Biology and Bioinformatics* 2021, 18(3): 1026 - 1034. in print. (SCI, JCR二区） 105. Rujing Wang, Lin Jiao, Chengjun Xie, Peng Chen, Du Jianming, Li Rui, S-RPN: Sampling-balanced region proposal network for small crop pest detection. Computers and Electronics in Agriculture* 2021, 187: 106290 104. Cheng Wang, Jun Zhang, Peng Chen, Bing Wang, Predicting Drug-Target Interactions Based on the Ensemble Models of Multiple Feature Pairs. International Journal of Molecular Sciences* 2021, 22(12): 6598 103. Wenyan Wang, Kun Lu, Ziheng Wu, Hongming Long, Jun Zhang, Peng Chen, Bing Wang, Surface Defects Classification of Hot Rolled Strip Based on Improved Convolutional Neural Network. Isij International* 2021, Accepted 102. Huimin Shen, Youzhi Zhang, Chun-Hou Zheng, Bing Wang, *Peng Chen.** A Cascade Graph Convolutional Network for Predicting Protein–Ligand Binding Affinity. International Journal of Molecular Sciences 2021, 22(8), 4023 101. HUANG Jian, CHEN Peng, ZHENG Chunhou, ZHANG Jun, WANG Bing, Few-Shot Metric Transfer Learning Network for Surface Defect Detection. Pattern Recognition and Artificial Intelligence 2021. Accepted 100.ZHANG Han , ZHANG Dexiang, CHEN Peng, ZHANG Jun, WANG Bin, Application of Parallel Attention Mechanism in Image Semantic Segmentation. Computer Engineering and Applications 2020. Accepted 99. Qiang Hu, Jun Zhang, Peng Chen, Bing Wang, Compound identification via deep classification model for electron-ionization mass spectrometry. International Journal of Mass Spectrometry 2021, 463: 116540 98. Wenyan Wang, Jun Zhang, Fang Zhou, Peng Chen, Bing Wang, Paper acceptance prediction at the institutional level based on the combination of individual and network features. Scientometrics* 2021, 126: pages1581–1597 97. Cheng Lin Zhang, You Zhi Zhang, Bing Wang, Peng Chen, Prediction of Drug-Target Binding Affinity by An Ensemble Learning System with Network Fusion Information. Current Bioinformatics* 2021, Accepted. 96. Bing Wang, Lili Peng, Nian Zhou, Peng Chen, Jun Zhang, Inferring Protein-Protein Interaction Sites Using Sequence Profile and Hydrophobic Information, BMC Bioinformatics, 2020, Accepted.(SCI, JCR二区） 2020年：* 96. Xiaofeng Cong, Jie Gui, Kai-Chao Miao, Jun Zhang, Bing Wang, and Peng Chen, Discrete Haze Level Dehazing Network. In 28th ACM International Conference on Multimedia (MM ’20), October 12–16, 2020, Seattle, WA, USA.. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3394171. 95. Peng Chen Qingxin Xiao, Jun Zhang, Chengjun Xie, Bing Wang, Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation. Computers and Electronics in Agriculture 2020, 176: 105612. 94.Aijun Deng, Huan Zhang, Wenyan Wang, Jun Zhang, Dingdong Fan, Peng Chen, and Bing Wang, Developing Computational Model to Predict Protein-Protein Interaction Sites Based on the XGBoost Algorithm. International Journal of Molecular Sciences* 2020, 21(7), 2274. [Full paper] 93.ShanShan Hu, Peng Chen, Jun Zhang, Bing Wang, Jinyan Li, A Deep Learning-Based Chemical System for QSAR Prediction, IEEE Journal of Biomedical and Health Informatics* 2020, 24(10): 3020-3028.[Full paper] (SCI, JCR一区） 92.Kai-chao Miao, Ting-ting Han, Ye-qing Yao, Hui Lu, Peng Chen, Bing Wang and Jun Zhang, Application of LSTM for Short Term Fog Forecasting based on Meteorological Elements, NeuroComputing* 2020, 408: 285-291. online (SCI, JCR二区） 91.Peng Chen, Tong Shen, Youzhi Zhang and Bing Wang, A Sequence-Segment Neighbor Encoding Schema for Protein Hotspot Residue Prediction. Current Bioinformatics 2020, 15: 1-10. 90.Tao Fang, Peng Chen, Jun Zhang, Bing Wang, Crop leaf disease grade identification based on an improved convolutional neural network, Journal of Image Electronics 2020, 29(1): 013004. 2019年：* 89.Ye Wang, Changqing Mei, Yuming Zhou, Yan Wang, Chunhou Zheng, Xiao Zhen, Yan Xiong, Peng Chen, Jun Zhang and Bing Wang, Semi-supervised prediction of protein interaction sites from unlabeled sample information, BMC Bioinformatics* 2019, 20(S25):699.(SCI, JCR二区） 88.ShanShan Hu, Peng Chen, Bing Wang and Jinyan Li, Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks. BMC Bioinformatics* 2019, 20(S25):689.(SCI, JCR二区） 87.Qingxin Xiao, Jun Zhang, Peng Chen, Bing Wang, Prediction of the Occurrence of Pests and Diseases in Cotton on the basis of Weather by Long Short Term Memory Network. BMC Bioinformatics* 2019, 20(S25):688. (SCI, JCR二区） 86. Gaili Guo, Kankan Wang, Shan-Shan Hu, Tian Tian, Peng Liu, Tetsuya Mori, *Peng Chen, Carl Hirschie Johnson, Ximing Qin. Auto-kinase activity of Casein Kinase 1 δ/ε Governs the Period of Mammalian Circadian Rhythms. Journal of Biological Rhythms* 2019, 34(5), 482–496. (SCI, JCR二区） 85. Jie Hang, Dexiang Zhang, Peng Chen, Jun Zhang and Bing Wang, Classification of plant leaf diseases based on improved convolutional neural network. Sensors 2019, 19(19): 4083. 84. Yangyang Wang , Qingxin Xiao, Peng Chen, Bing Wang, In silico Prediction of Drug-Induced Liver Injury Based on Ensemble Classifier Method. International Journal of Molecular Sciences 2019, 20(17), 4106. [Journal paper](SCI, JCR二区, Top期刊） 83. Weilu Li, Peng Chen, Bing Wang, Chengjun Xie, Automatic Localization and Count of Agricultural Crop Pests Based on an Improved Deep Learning-Based Pipeline, Scientific Reports, 2019. (9): 7024. 82. Lin-Wei Ge, Jun Zhang, Yi Xia, Peng Chen, Bing Wang, Chun-Hou Zheng, Deep spatial attention hashing network for image retrieval. *J. Vis. Commun. Image R.* (2019). 63: 102577. 81. Jie Hang, Dexiang Zhang, Peng Chen, Jun Zhang, and Bing Wang, Identification of Apple Tree Trunk Diseases Based on Improved Convolutional Neural Network with Fused Loss Functions. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 274–283. Springer, Cham. 80. Tao Fang, Peng Chen, Jun Zhang, and Bing Wang, Identification of Apple Leaf Diseases Based on Convolutional Neural Network. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 553–564. Springer, Cham. 79. Xiao-Tao Xu, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia, Urine Sediment Detection Based on Deep Learning. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 543–552. Springer, Cham. 78. Panpan Lu, Kun Lu, Wenyan Wang, Jun Zhang, Peng Chen, and Bing Wang, Real-Time Pedestrian Detection in Monitoring Scene Based on Head Model. In: Huang DS., Jo KH., Huang Z.K. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11644, pp. 558–568. Springer, Cham. 77. Guangyu Wang, Bing Dai, Wenyan Wang, Hongming Long, Jun Zhang, Peng Chen, and Bing Wang, An Optimization Regression Model for Predicting Average Temperature of Core Dead Stock Column. In: Huang DS., Huang Z.K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Artifical Intelligence, vol 11645, pp. 468–478. Springer, Cham. 76. Wenyan Wang, Guangyu Wang, Jun Zhang, Peng Chen, and Bing Wang, Ranking Research Institutions Based on the Combination of Individual and Network Features. In: Huang DS., Huang Z.K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Artifical Intelligence, vol 11645, pp. 443–454. Springer, Cham. 2018年：* 75. Chengjun Xie, Rujing Wang, Jie Zhang, Peng Chen, Wei Dong, Rui Li, Jian Yu, Multi-level learning features for automatic classification of field crop insects. Computers and Electronics in Agriculture. In print. (SCI, JCR二区）* 74. 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) 19:14. Online paper (SCI, JCR二区） 73. Quanya Liu, Peng Chen, Jun Zhang, Bing Wang and Jinyan Li, dbMPIKT: A kinetic and thermodynamic database of mutant protein interaction. 2018. BMC Bioinformatics* 2018, 2018. 19: 455. (arXiv e-prints) (SCI, JCR二区） 72. Quanya Liu, Bing Wang, Hot Spot prediction in protein-protein interactions by an ensemble learning. BMC Systems Biology 2018, 12 (Suppl 9): 132. 71.Denan Xia, Peng Chen, Bing Wang, Jun Zhang, Chengjun Xie, Insect detection and classification based on improved convolutional neural network. Sensors, 2018, 18: 4169. 70. Bing Wang, Kun Lu, Xiao Zheng, Benyue Su, Yuming Zhou, Peng Chen and Jun Zhang, Early Stage Identification of Alzheimer’s Disease Using a Two-stage Ensemble Classifier. Current Bioinformatics (2018) 13(5): 529 - 535. 69. MuChun Zhu, Xiaoping Song, Peng Chen, Wenyan Wang and Bing Wang, dbHDPLS: Database of Human Disease Protein-Ligand Structure. Computational Biology and Chemistry* 2018, (2019) 78: 353–358. 68. ShanShan Hu, DeNan Xia, Peng Chen, and Bing Wang, Using Novel Convolutional Neural Networks Architecture to Predict Drug-Target Interactions. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 432-437. Springer, Cham. 67. Qingxin Xiao, Weilu Li, Peng Chen, and Bing Wang, Prediction of Crop Pests and Diseases in Cotton by Long Short Term Memory Network. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 11-16. Springer, Cham. 66. Yan-Zhe Di, *Peng Chen, and Chun-Hou Zheng, Similarity-Based Integrated Method for Predicting Drug-Disease Interactions. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 395-400. Springer, Cham. 65. Jun Zhang, Hui Lu, Yi Xia, Ting-Ting Han, Kai-Chao Miao, Ye-Qing Yao, Cheng-Xiao Liu, Jian-Ping Zhou, Peng Chen, and Bing Wang, Deep Convolutional Neural Network for Fog Detection. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 1-10. Springer, Cham. 64. Nian Zhou, Lingshan Zhou, Lili Peng, Bing Wang, Peng Chen, and Jun Zhang, Verifying TCM Syndrome Hypothesis Based on Improved Latent Tree Model. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 461-469. Springer, Cham. 63. Run-xu Tan, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia. Cells Counting with Convolutional Neural Network. In: Huang DS., Gromiha M.M., Han K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science, vol 10956, pp. 102-111. Springer, Cham. 62. Ting-ting Han, Kai-chao Miao, Ye-qing Yao, Cheng-xiao Liu, Jian-ping Zhou, Hui Lu, Peng Chen, Xia Yi, Bing Wang, Convolutional Neural Network for Short Term Fog Forecasting Based on Meteorological Elements and Jun Zhang. In: Huang DS., Gromiha M.M., Han K., Hussain A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science, vol 10956, pp. 143-148. Springer, Cham. 61. Lili Peng, Fang Chen, Nian Zhou, Peng Chen, Jun Zhang,and Bing Wang, Prediction of Protein-Protein Interaction Sites Combing Sequence Profile and Hydrophobic Information. In: Huang DS., Premaratne V.B.P., Gupta P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10954, pp. 697-702. Springer, Cham. 60. Wei-wei Gao, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia. In: Huang DS., Chinese Text Detection Using Deep Learning Model and Synthetic Data. Premaratne V.B.P., Gupta P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10954, pp. 503-512. Springer, Cham. 2016-2017年：* 59. 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) 49:1773–1785, Online paper. (SCI, JCR二区） 58. 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. [Journal paper] 57. Jinjian Jiang, Nian Wang, Peng Chen, Jun Zhang, Bing Wang, DrugECs: ensemble system with feature subspaces to accurate drug-target interaction prediction. BioMed Research International* 2017(2017). [Journal paper] 56. 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. (SCI, JCR二区）* 55. Jun Zhang, Muchun Zhu, Peng Chen, Bing Wang, DrugRPE: random projection ensemble approach to drug-target interaction prediction, Neurocomputing* 2017, 228: 256–262. (SCI, JCR二区） 54. Sen Xia, *Peng Chen, Jun Zhang, Xiaoping Li, Bing Wang, Utilization of rotation-invariant uniform LBP histogram distribution and statistics of connected regions in automatic image annotation based on multi-label learning. NeuroComputing, 2017, 228: 11-18. (SCI, JCR二区）* 53. Wenyan Wang, Kun Lu, Rui Hong, *Peng Chen, Jun Zhang and Bing Wang, A Machine Vision Method for Automatic Circular Parts Detection Based on Optimization Algorithm. In: Huang DS., Jo KH., Figueroa-García J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science, vol 10361, pp. 600–611. Springer, Cham. 52. Feng-Lin DuJia-Xing LiZhi YangPeng ChenBing WangJun Zhang, Captcha recognition based on faster R-CNN. In: Huang DS., Jo KH., Figueroa-García J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science, vol 10362. Springer, Cham. 51. 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):4298-309. (SCI, JCR一区）Co-first author 50. Bing Wang, Hao Shen, Aiqin Fang, De-shuang Huang, Changjun Jiang, Jun Zhang, Peng Chen, A regression model for calculating the second dimension retention index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry, Journal of Chromatography A, 2016, 1451(17): 127–134. (SCI, JCR二区）* 49. 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.(SCI) 48. *Peng Chen, Bing Wang, Jun Zhang, Xin Gao, Jinyan Li, and Jun-feng Xia, A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction, ACM/IEEE Transactions on Computational Biology and Bioinformatics, 2016, 13(5):901-912,(SCI)* 47. Jun Zhang, Yi Xia, Chun-Hou Zheng, Bing Wang, Xiang Zhang, Peng Chen, Combine multiple mass spectral similarity measures for compound identification, International Journal of Data Mining and Bioinformatics* 2016 ,15 (1), 84-100. (SCI) 46. Jun Zhang, Xiao-Li Wei, Chun-Hou Zheng, Bing Wang, Feng Wang, *Peng Chen, Compound identification using random projection for gas chromatography–mass spectrometry data, International Journal of Mass Spectrometry* 2016, 407: 16–21. (SCI) 45. SS Hu, Peng Chen, J Zhang, B Wang, Prediction of Hot Spots Based on Physicochemical Features and Relative Accessible Surface Area of Amino Acid Sequence, Intelligent Computing Theories and Application, Lecture Notes in Computer Science 2016, Vol. 9771, 422-431. (EI, ISTP) 2014-2015年：* 44. Chengjun Xie, Rui Li, Jie Zhang, Peilin Hong, Jinyan Li, 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.(SCI, JCR二区） 43. Peng Chen, Jianhua Huang, and Xin Gao, LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone, BMC Bioinformatics, 2014, 15(S15): S4 (SCI, JCR二区）* 42. 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. (SCI, JCR二区）* 41. 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. (SCI)* 40. 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. (SCI)* 39. Chuanxi Li, Peng Chen, Rujing Wang, PPI-IRO: A Two Stage Method for Protein-Protein Interaction Extraction Based on Interaction Relation Ontology. International Journal of Data Mining and Bioinformatics, 2014, 10 (1), 98-119. (SCI)* 38. Yaru Su, Rujing Wang, *Peng Chen,* Chuan-Xi Li, Sparse Representation-Based Approach for Unsupervised Feature Selection, Int. J. Patt. Recogn. Artif. Intell., 2014, 28(3), 1450006. (SCI) 37. *Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, A Random Projection Ensemble Approach to Drug-Target Interaction Prediction, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 693-699. (EI, ISTP) 36. Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, Sequence-Based Random Projection Ensemble Approach to Identify Hotspot Residues from Whole Protein Sequence, Intelligent Computing Theories and Methodologies, Lecture Notes in Computer Science, 2015, Vol. 9226, 379-389. (EI, ISTP) 35. Sen Xia, Peng Chen, Jun Zhang, Xiao-Ping Li, Bing Wang, A Multi-feature Fusion Method for Automatic Multi-label Image Annotation with Weighted Histogram Integral and Closure Regions Counting, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 323-330. (EI, ISTP) 34. Li-Li Cao, Zhi-Shui Zhang, Peng Chen, Jun Zhang, Compound Identification Using Random Projection for Gas Chromatography-Mass Spectrometry Data, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 686-692. (EI, ISTP) 33. Zhi-Shui Zhang, Li-Li Cao, Jun Zhang, Peng Chen, Chun-hou Zheng, Prediction of Molecular Substructure Using Mass Spectral Data Based on Deep Learning, Intelligent Computing Theories and Methodologies, Lecture Notes in Computer Science, 2015, Vol. 9226, 520-529. (EI, ISTP) 2011-2013年：* 32. Bing Wang, Jun Zhang, *Peng Chen, Zhiwei Ji, Shuping Deng and Chi Li, Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features, BMC Bioinformatics, 2013, 14 (Suppl 8), S9. (SCI, JCR二区）* 31. *Peng Chen, Limsoon Wong, Jinyan Li, Outlier detection: a challenge to clean interface data in protein hetero-complexes and the application, ACM/IEEE Transactions on Computational Biology and Bioinformatics, 2012, 9(4):1155-1165. . (SCI, JCR二区）* 30. *Peng Chen, Jinyan Li, Limsoon Wong, Jianhua Huang, and Xin Gao, Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences. Proteins, 2013, 81: 1351–1362. (SCI)* 29. 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.(SCI) 28. Bing Wang, Wenlong Sun, Jun Zhang, and Peng Chen. Current Status of Machine Learning-Based Methods for Identifying Protein-Protein Interaction Sites, Current Bioinformatics, 2013, 8 (2), 177-182. (SCI)* 27. Yaru Su, Rujing Wang, Peng Chen, Agricultural ontology based feature optimization for agricultural text clustering, Agricultural Sciences in China, 2012, 11 (5): 752-759. (SCI)* 26. 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，2013，V26(1)：114-122。 25. Chuan-Xi Li, Peng Chen, Ru-Jing Wang and Ya-Ru Su, Web entity extraction method based on entity attribute classification, In: Proceedings of the SPIE, Volume 8350, pp. 835014-835014-6 (2011) (EI, ISTP) 24. Yaru Su, Rujing Wang, Chuanxi Li, Peng Chen, A dynamic subspace learning method for tumor classification, In: The 7th International Conference on Natural Computation (ICNC’11), 2011, Volume: 1, Page(s): 396 - 400. (EI, ISTP) 23. Peng Chen, Consensus of sample-balanced classifiers for identifying ligand-binding residue by co-evolutionary physicochemical characteristics of amino acids, Emerging Intelligent Computing Technology and Application, 2013, Vol. 375, 206-212 (EI, ISTP) 22. B Wang, Peng Chen, J Zhang, Protein Interface Residues Prediction Based on Amino Acid Properties Only, Bio-Inspired Computing and Applications, Lecture Notes in Computer Science, 2012, Vol. 6840/2012, 448-452. (EI, ISTP) 2008-2010年：* 21. *Peng Chen,* Jinyan Li, Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information, BMC Bioinformatics, 2010, 11:402. (SCI, JCR二区） 20. Peng Chen, Chunmei Liu, Legand Burge, Jinyan Li, Mahmood Mohanmad, Bill Southerland, and Clay Gloster, DomSVR: Domain Boundary Prediction with Support Vector Regression from sequence information Alone, Amino Acids, 2010, 39(3), 713-726 . (SCI, JCR二区）* 19. *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(Suppl 1):S2. (SCI)* 18. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, Prediction of Inter-residue Contact Clusters from Hydrophobic Cores, International Journal of Data Mining and Bioinformatics, 2010, 4(6), 720-732. (SCI)* 17. B. Wang, *Peng Chen, J. Zhang, G. Zhao and X. Zhang, Inferring Protein-Protein Interactions Using a Hybrid Genetic Algorithm/Support Vector Machine Method, Protein & Peptide Letters, 17(9), Pp. 1079-1084, 2010. (SCI)* 16. B. Wang , *Peng Chen, P. Wang, G. Zhao and X. Zhang, Radial Basis Function Neural Network Ensemble for Predicting Protein-Protein Interaction Sites in Heterocomplexes, Protein & Peptide Letters, 17(9), Pp. 1111-1116, 2010. (SCI)* 15. *Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, Protein Fold Classification with Genetic Algorithms and Feature Selection, Journal of Bioinformatics and Computational Biology, vol.7, no.5, pp. 773-788, 2009. 14. Peng Chen, Kyungsook Han, Xueling Li, D.S. Huang, Predicting Key Long-Range Interaction Sites by B-Factors. Protein & Peptide Letters. 15(5):478-483, 2008.(SCI) 13. Peng Chen, D.S. Huang, Predicting Contact Map Using Radial Basis Function Neural Network with Conformational Energy Function, International Journal of Bioinformatics Research and Applications, vol. 4, no.2, pp. 123 - 136, 2008. 12. Peng Chen, Jinyan Li, Prediction of Protein Long-Range Contacts Using GaMC Approach with Sequence Profile Centers, In: Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on, Washington DC, USA, 2009 128-135. (EI, ISTP) 11. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, DomSVR: Domain Boundary Prediction with Support Vector Regression and Evolutionary Information, In: The 3rd International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2009), China, 2009, 1-5. (EI, ISTP) 10. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohammad, Bill Southerland, Clay Gloster, Bing Wang, IRCDB: A Database of Inter-residues Contacts in Protein Chains, In: Advances in Databases, Knowledge, and Data Applications, 2009. DBKDA '09. First International Conference on, 1-6. (EI, ISTP) 9. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, Bill Southerland, and Clay Gloster, Prediction of Inter-residue Contact Clusters from Hydrophobic Cores. In: Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on, San Diego, California, USA, 2008, 703-708. (EI, ISTP) 2007年及以前：* 8. *Peng Chen, Bing Wang, Hau San Wong, D.S., Huang, Prediction of Protein B-factors Using Multi-class Bounded SVM. Protein & Peptide Letters, vol.14, no.2, pp.185-190, 2007. (SCI)* 7. Bing Wang, *Peng Chen, D.S. Huang, Jing-Jing Li, Tat-Ming Lok, Michael R. Lyu, Predicting protein interaction sites from residue spatial sequence profile and evolution rate, FEBS Letters, vol.580, no.2, pp. 380-384, 2006. (Co-first author) (SCI)* 6. Jing-Jing Li, D.S.Huang, Bing Wang, *Peng Chen, Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores, International Journal of Biological Macromolecules, vol.38, nos.3-5, pp.241-247, 2006. (SCI)* 5. *Peng Chen, Bing Wang, Hau San Wong, D.S.Huang, Prediction of Long-range Contacts from Sequence Profile, In: Neural Networks, 2007. IJCNN 2007. International Joint Conference on, Orlando, Florida, USA, 2007, 938-943. (EI, ISTP) 4. Peng Chen, Hau-San Wong, Bing Wang and De-Shuang Huang, Long-range interaction analysis using principal component analysis, In: Neural Networks, 2006. IJCNN 2006. International Joint Conference on, Vancouver, British Columbia, Canada, 2006, 2331-2336. (EI, ISTP) 3. Peng Chen, De-Shuang Huang, Bing Wang, Prediction of contact map integrated PNN with conformational energy, In: Neural Networks, 2005. IJCNN 2005. International Joint Conference on, Montreal, Canada, 2005, 499- 502. (EI, ISTP) 2. Bing Wang, Hau San Wong, Peng Chen, Hong-Qiang Wang and De-Shuang Huang, Predicting protein-protein interaction sites using radial basis function neural networks, In: Neural Networks, 2006. IJCNN 2006. International Joint Conference on, Vancouver, British Columbia, Canada, 2006, 2325- 2330. (EI, ISTP) 1. Bing Wang, De-Shuang Huang, Peng Chen*, Predicting protein-protein interactions based on protein-domain relationships, In: Neural Networks, 2005. IJCNN 2005. International Joint Conference on, Montreal, Canada, 2005, 316- 319. (EI, ISTP) 　 Copyright© Peng Chen 2004-2011 All Rights Reserved

Publications: (* Correspondence Author)

2021年：

109. Peng Chen, Weilu Li, Sijie Yao, Chun Ma, Chunhou Zheng, Jun Zhang, Chengjun Xie, Bing Wang, Dong Liang, Recognition and Counting of Wheat Mites in Wheat Fields by A Three-Step Deep Learning Method. Neurocomputing 2021, 437: 21-30. (SCI, JCR二区）

108. ShanShan Hu, DeNan Xia, Benyue Su, Peng Chen*, Bing Wang and Jinyan Li, A Convolutional Neural Network System to Discriminate Drug-Target Interactions. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2021, 18(4): 1315 - 1324. in print. (SCI, JCR二区）

107. Bing Wang, Changqing Mei, Yuanyuan Wan, Jun Zhang, Peng Chen*, Yan Xiong*, Imbalance Data Processing Strategy for Protein Interaction Sites Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2021, 18(3): 985 - 994. in print. (SCI, JCR二区）

106. Wenyan Wang, Yuming Zhou, Mu-Tian Cheng, Yan Wang, Chun-Hou Zheng, Yan Xiong, Peng Chen*, Zhiwei Ji, Bing Wang, Potential Pathogenic Genes Prioritization Based on Protein Domain Interaction Network Analysis, IEEE/ACM Transactions on Computational Biology and Bioinformatics 2021, 18(3): 1026 - 1034. in print. (SCI, JCR二区）

105. Rujing Wang, Lin Jiao, Chengjun Xie, Peng Chen*, Du Jianming, Li Rui, S-RPN: Sampling-balanced region proposal network for small crop pest detection. Computers and Electronics in Agriculture 2021, 187: 106290

104. Cheng Wang, Jun Zhang, Peng Chen*, Bing Wang, Predicting Drug-Target Interactions Based on the Ensemble Models of Multiple Feature Pairs. International Journal of Molecular Sciences 2021, 22(12): 6598

103. Wenyan Wang, Kun Lu, Ziheng Wu, Hongming Long, Jun Zhang, Peng Chen*, Bing Wang, Surface Defects Classification of Hot Rolled Strip Based on Improved Convolutional Neural Network. Isij International 2021, Accepted

102. Huimin Shen, Youzhi Zhang, Chun-Hou Zheng, Bing Wang, Peng Chen*. A Cascade Graph Convolutional Network for Predicting Protein–Ligand Binding Affinity. International Journal of Molecular Sciences 2021, 22(8), 4023

101. HUANG Jian, CHEN Peng, ZHENG Chunhou, ZHANG Jun, WANG Bing, Few-Shot Metric Transfer Learning Network for Surface Defect Detection. Pattern Recognition and Artificial Intelligence 2021. Accepted

100.ZHANG Han , ZHANG Dexiang, CHEN Peng*, ZHANG Jun, WANG Bin, Application of Parallel Attention Mechanism in Image Semantic Segmentation. Computer Engineering and Applications 2020. Accepted

99. Qiang Hu, Jun Zhang, Peng Chen*, Bing Wang, Compound identification via deep classification model for electron-ionization mass spectrometry. International Journal of Mass Spectrometry 2021, 463: 116540

98. Wenyan Wang, Jun Zhang, Fang Zhou, Peng Chen*, Bing Wang, Paper acceptance prediction at the institutional level based on the combination of individual and network features. Scientometrics 2021, 126: pages1581–1597

97. Cheng Lin Zhang, You Zhi Zhang, Bing Wang, Peng Chen*, Prediction of Drug-Target Binding Affinity by An Ensemble Learning System with Network Fusion Information. Current Bioinformatics 2021, Accepted.

96. Bing Wang, Lili Peng, Nian Zhou, Peng Chen*, Jun Zhang, Inferring Protein-Protein Interaction Sites Using Sequence Profile and Hydrophobic Information, BMC Bioinformatics, 2020, Accepted.(SCI, JCR二区）

2020年：

96. Xiaofeng Cong, Jie Gui, Kai-Chao Miao, Jun Zhang, Bing Wang, and Peng Chen, Discrete Haze Level Dehazing Network. In 28th ACM International Conference on Multimedia (MM ’20), October 12–16, 2020, Seattle, WA, USA.. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3394171.

95. Peng Chen Qingxin Xiao, Jun Zhang, Chengjun Xie, Bing Wang, Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation. Computers and Electronics in Agriculture 2020, 176: 105612.

94.Aijun Deng, Huan Zhang, Wenyan Wang, Jun Zhang, Dingdong Fan, Peng Chen*, and Bing Wang, Developing Computational Model to Predict Protein-Protein Interaction Sites Based on the XGBoost Algorithm. International Journal of Molecular Sciences 2020, 21(7), 2274. [Full paper]

93.ShanShan Hu, Peng Chen*, Jun Zhang, Bing Wang, Jinyan Li, A Deep Learning-Based Chemical System for QSAR Prediction, IEEE Journal of Biomedical and Health Informatics 2020, 24(10): 3020-3028.[Full paper] (SCI, JCR一区）

92.Kai-chao Miao, Ting-ting Han, Ye-qing Yao, Hui Lu, Peng Chen*, Bing Wang and Jun Zhang, Application of LSTM for Short Term Fog Forecasting based on Meteorological Elements, NeuroComputing 2020, 408: 285-291. online (SCI, JCR二区）

91.Peng Chen*, Tong Shen, Youzhi Zhang* and Bing Wang, A Sequence-Segment Neighbor Encoding Schema for Protein Hotspot Residue Prediction. Current Bioinformatics 2020, 15: 1-10.

90.Tao Fang, Peng Chen*, Jun Zhang, Bing Wang, Crop leaf disease grade identification based on an improved convolutional neural network, Journal of Image Electronics 2020, 29(1): 013004.

2019年：

89.Ye Wang, Changqing Mei, Yuming Zhou, Yan Wang, Chunhou Zheng, Xiao Zhen, Yan Xiong, Peng Chen*, Jun Zhang and Bing Wang, Semi-supervised prediction of protein interaction sites from unlabeled sample information, BMC Bioinformatics 2019, 20(S25):699.(SCI, JCR二区）

88.ShanShan Hu, Peng Chen*, Bing Wang and Jinyan Li, Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks. BMC Bioinformatics 2019, 20(S25):689.(SCI, JCR二区）

87.Qingxin Xiao, Jun Zhang, Peng Chen*, Bing Wang, Prediction of the Occurrence of Pests and Diseases in Cotton on the basis of Weather by Long Short Term Memory Network. BMC Bioinformatics 2019, 20(S25):688. (SCI, JCR二区）

86. Gaili Guo, Kankan Wang, Shan-Shan Hu, Tian Tian, Peng Liu, Tetsuya Mori, Peng Chen, Carl Hirschie Johnson, Ximing Qin. Auto-kinase activity of Casein Kinase 1 δ/ε Governs the Period of Mammalian Circadian Rhythms. Journal of Biological Rhythms 2019, 34(5), 482–496. (SCI, JCR二区）

85. Jie Hang, Dexiang Zhang, Peng Chen*, Jun Zhang and Bing Wang, Classification of plant leaf diseases based on improved convolutional neural network. Sensors 2019, 19(19): 4083.

84. Yangyang Wang , Qingxin Xiao, Peng Chen*, Bing Wang, In silico Prediction of Drug-Induced Liver Injury Based on Ensemble Classifier Method. International Journal of Molecular Sciences 2019, 20(17), 4106. [Journal paper](SCI, JCR二区, Top期刊）

83. Weilu Li, Peng Chen*, Bing Wang, Chengjun Xie, Automatic Localization and Count of Agricultural Crop Pests Based on an Improved Deep Learning-Based Pipeline, Scientific Reports, 2019. (9): 7024.

82. Lin-Wei Ge, Jun Zhang, Yi Xia, Peng Chen*, Bing Wang, Chun-Hou Zheng, Deep spatial attention hashing network for image retrieval. J. Vis. Commun. Image R. (2019). 63: 102577.

81. Jie Hang, Dexiang Zhang, Peng Chen*, Jun Zhang, and Bing Wang, Identification of Apple Tree Trunk Diseases Based on Improved Convolutional Neural Network with Fused Loss Functions. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 274–283. Springer, Cham.

80. Tao Fang, Peng Chen, Jun Zhang, and Bing Wang, Identification of Apple Leaf Diseases Based on Convolutional Neural Network. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 553–564. Springer, Cham.

79. Xiao-Tao Xu, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia, Urine Sediment Detection Based on Deep Learning. In: Huang DS., Bevilacqua V., Premaratne P. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11643, pp. 543–552. Springer, Cham.

78. Panpan Lu, Kun Lu, Wenyan Wang, Jun Zhang, Peng Chen, and Bing Wang, Real-Time Pedestrian Detection in Monitoring Scene Based on Head Model. In: Huang DS., Jo KH., Huang Z.K. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science, vol 11644, pp. 558–568. Springer, Cham.

77. Guangyu Wang, Bing Dai, Wenyan Wang, Hongming Long, Jun Zhang, Peng Chen, and Bing Wang, An Optimization Regression Model for Predicting Average Temperature of Core Dead Stock Column. In: Huang DS., Huang Z.K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Artifical Intelligence, vol 11645, pp. 468–478. Springer, Cham.

76. Wenyan Wang, Guangyu Wang, Jun Zhang, Peng Chen, and Bing Wang, Ranking Research Institutions Based on the Combination of Individual and Network Features. In: Huang DS., Huang Z.K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Artifical Intelligence, vol 11645, pp. 443–454. Springer, Cham.

2018年：

75. Chengjun Xie, Rujing Wang, Jie Zhang, Peng Chen*, Wei Dong, Rui Li, Jian Yu, Multi-level learning features for automatic classification of field crop insects. Computers and Electronics in Agriculture. In print. (SCI, JCR二区）

74. 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) 19:14. Online paper (SCI, JCR二区）

73. Quanya Liu, Peng Chen*, Jun Zhang, Bing Wang and Jinyan Li, dbMPIKT: A kinetic and thermodynamic database of mutant protein interaction. 2018. BMC Bioinformatics 2018, 2018. 19: 455. (arXiv e-prints) (SCI, JCR二区）

72. Quanya Liu, Bing Wang, Hot Spot prediction in protein-protein interactions by an ensemble learning. BMC Systems Biology 2018, 12 (Suppl 9): 132.

71.Denan Xia, Peng Chen*, Bing Wang, Jun Zhang, Chengjun Xie, Insect detection and classification based on improved convolutional neural network. Sensors, 2018, 18: 4169.

70. Bing Wang, Kun Lu, Xiao Zheng, Benyue Su, Yuming Zhou, Peng Chen* and Jun Zhang, Early Stage Identification of Alzheimer’s Disease Using a Two-stage Ensemble Classifier. Current Bioinformatics (2018) 13(5): 529 - 535.

69. MuChun Zhu, Xiaoping Song, Peng Chen*, Wenyan Wang and Bing Wang, dbHDPLS: Database of Human Disease Protein-Ligand Structure. Computational Biology and Chemistry 2018, (2019) 78: 353–358.

68. ShanShan Hu, DeNan Xia, Peng Chen*, and Bing Wang, Using Novel Convolutional Neural Networks Architecture to Predict Drug-Target Interactions. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 432-437. Springer, Cham.

67. Qingxin Xiao, Weilu Li, Peng Chen*, and Bing Wang, Prediction of Crop Pests and Diseases in Cotton by Long Short Term Memory Network. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 11-16. Springer, Cham.

66. Yan-Zhe Di, Peng Chen, and Chun-Hou Zheng, Similarity-Based Integrated Method for Predicting Drug-Disease Interactions. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 395-400. Springer, Cham.

65. Jun Zhang, Hui Lu, Yi Xia, Ting-Ting Han, Kai-Chao Miao, Ye-Qing Yao, Cheng-Xiao Liu, Jian-Ping Zhou, Peng Chen, and Bing Wang, Deep Convolutional Neural Network for Fog Detection. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 1-10. Springer, Cham.

64. Nian Zhou, Lingshan Zhou, Lili Peng, Bing Wang, Peng Chen, and Jun Zhang, Verifying TCM Syndrome Hypothesis Based on Improved Latent Tree Model. In: Huang DS., Jo KH., Zhang X.L. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10955, pp. 461-469. Springer, Cham.

63. Run-xu Tan, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia. Cells Counting with Convolutional Neural Network. In: Huang DS., Gromiha M.M., Han K., Hussain A.. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science, vol 10956, pp. 102-111. Springer, Cham.

62. Ting-ting Han, Kai-chao Miao, Ye-qing Yao, Cheng-xiao Liu, Jian-ping Zhou, Hui Lu, Peng Chen, Xia Yi, Bing Wang, Convolutional Neural Network for Short Term Fog Forecasting Based on Meteorological Elements and Jun Zhang. In: Huang DS., Gromiha M.M., Han K., Hussain A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science, vol 10956, pp. 143-148. Springer, Cham.

61. Lili Peng, Fang Chen, Nian Zhou, Peng Chen, Jun Zhang,and Bing Wang, Prediction of Protein-Protein Interaction Sites Combing Sequence Profile and Hydrophobic Information. In: Huang DS., Premaratne V.B.P., Gupta P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10954, pp. 697-702. Springer, Cham.

60. Wei-wei Gao, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia. In: Huang DS., Chinese Text Detection Using Deep Learning Model and Synthetic Data. Premaratne V.B.P., Gupta P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science, vol 10954, pp. 503-512. Springer, Cham.

2016-2017年：

59. 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) 49:1773–1785, Online paper. (SCI, JCR二区）

58. 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. [Journal paper]

57. Jinjian Jiang, Nian Wang, Peng Chen*, Jun Zhang, Bing Wang, DrugECs: ensemble system with feature subspaces to accurate drug-target interaction prediction. BioMed Research International 2017(2017). [Journal paper]

56. 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. (SCI, JCR二区）

55. Jun Zhang, Muchun Zhu, Peng Chen*, Bing Wang, DrugRPE: random projection ensemble approach to drug-target interaction prediction, Neurocomputing 2017, 228: 256–262. (SCI, JCR二区）

54. Sen Xia, Peng Chen, Jun Zhang, Xiaoping Li, Bing Wang, Utilization of rotation-invariant uniform LBP histogram distribution and statistics of connected regions in automatic image annotation based on multi-label learning. NeuroComputing, 2017, 228: 11-18. (SCI, JCR二区）

53. Wenyan Wang, Kun Lu, Rui Hong, Peng Chen, Jun Zhang and Bing Wang, A Machine Vision Method for Automatic Circular Parts Detection Based on Optimization Algorithm. In: Huang DS., Jo KH., Figueroa-García J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science, vol 10361, pp. 600–611. Springer, Cham.

52. Feng-Lin DuJia-Xing LiZhi YangPeng ChenBing WangJun Zhang, Captcha recognition based on faster R-CNN. In: Huang DS., Jo KH., Figueroa-García J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science, vol 10362. Springer, Cham.

51. 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):4298-309. (SCI, JCR一区）Co-first author

50. Bing Wang, Hao Shen, Aiqin Fang, De-shuang Huang, Changjun Jiang, Jun Zhang, Peng Chen*, A regression model for calculating the second dimension retention index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry, Journal of Chromatography A, 2016, 1451(17): 127–134. (SCI, JCR二区）

49. 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.(SCI)

48. Peng Chen, Bing Wang, Jun Zhang, Xin Gao, Jinyan Li, and Jun-feng Xia, A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction, ACM/IEEE Transactions on Computational Biology and Bioinformatics, 2016, 13(5):901-912,(SCI)

47. Jun Zhang, Yi Xia, Chun-Hou Zheng, Bing Wang, Xiang Zhang, Peng Chen*, Combine multiple mass spectral similarity measures for compound identification, International Journal of Data Mining and Bioinformatics 2016 ,15 (1), 84-100. (SCI)

46. Jun Zhang, Xiao-Li Wei, Chun-Hou Zheng, Bing Wang, Feng Wang, Peng Chen, Compound identification using random projection for gas chromatography–mass spectrometry data, International Journal of Mass Spectrometry 2016, 407: 16–21. (SCI)

45. SS Hu, Peng Chen*, J Zhang, B Wang, Prediction of Hot Spots Based on Physicochemical Features and Relative Accessible Surface Area of Amino Acid Sequence, Intelligent Computing Theories and Application, Lecture Notes in Computer Science 2016, Vol. 9771, 422-431. (EI, ISTP)

2014-2015年：

44. Chengjun Xie, Rui Li, Jie Zhang, Peilin Hong, Jinyan Li, 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.(SCI, JCR二区）

43. Peng Chen, Jianhua Huang, and Xin Gao, LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone, BMC Bioinformatics, 2014, 15(S15): S4 (SCI, JCR二区）

42. 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. (SCI, JCR二区）

41. 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. (SCI)

40. 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. (SCI)

39. Chuanxi Li, Peng Chen*, Rujing Wang, PPI-IRO: A Two Stage Method for Protein-Protein Interaction Extraction Based on Interaction Relation Ontology. International Journal of Data Mining and Bioinformatics, 2014, 10 (1), 98-119. (SCI)

38. Yaru Su, Rujing Wang, Peng Chen, Chuan-Xi Li, Sparse Representation-Based Approach for Unsupervised Feature Selection, Int. J. Patt. Recogn. Artif. Intell., 2014, 28(3), 1450006. (SCI)

37. Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, A Random Projection Ensemble Approach to Drug-Target Interaction Prediction, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 693-699. (EI, ISTP)

36. Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, Sequence-Based Random Projection Ensemble Approach to Identify Hotspot Residues from Whole Protein Sequence, Intelligent Computing Theories and Methodologies, Lecture Notes in Computer Science, 2015, Vol. 9226, 379-389. (EI, ISTP)

35. Sen Xia, Peng Chen, Jun Zhang, Xiao-Ping Li, Bing Wang, A Multi-feature Fusion Method for Automatic Multi-label Image Annotation with Weighted Histogram Integral and Closure Regions Counting, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 323-330. (EI, ISTP)

34. Li-Li Cao, Zhi-Shui Zhang, Peng Chen, Jun Zhang, Compound Identification Using Random Projection for Gas Chromatography-Mass Spectrometry Data, Advanced Intelligent Computing Theories and Applications, Lecture Notes in Computer Science, 2015, Vol. 9227, 686-692. (EI, ISTP)

33. Zhi-Shui Zhang, Li-Li Cao, Jun Zhang, Peng Chen, Chun-hou Zheng, Prediction of Molecular Substructure Using Mass Spectral Data Based on Deep Learning, Intelligent Computing Theories and Methodologies, Lecture Notes in Computer Science, 2015, Vol. 9226, 520-529. (EI, ISTP)

2011-2013年：

32. Bing Wang, Jun Zhang, Peng Chen, Zhiwei Ji, Shuping Deng and Chi Li, Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features, BMC Bioinformatics, 2013, 14 (Suppl 8), S9. (SCI, JCR二区）

31. Peng Chen, Limsoon Wong, Jinyan Li, Outlier detection: a challenge to clean interface data in protein hetero-complexes and the application, ACM/IEEE Transactions on Computational Biology and Bioinformatics, 2012, 9(4):1155-1165. . (SCI, JCR二区）

30. Peng Chen, Jinyan Li, Limsoon Wong, Jianhua Huang, and Xin Gao, Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences. Proteins, 2013, 81: 1351–1362. (SCI)

29. 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.(SCI)

28. Bing Wang, Wenlong Sun, Jun Zhang, and Peng Chen. Current Status of Machine Learning-Based Methods for Identifying Protein-Protein Interaction Sites, Current Bioinformatics, 2013, 8 (2), 177-182. (SCI)

27. Yaru Su, Rujing Wang, Peng Chen*, Agricultural ontology based feature optimization for agricultural text clustering, Agricultural Sciences in China, 2012, 11 (5): 752-759. (SCI)

26. 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，2013，V26(1)：114-122。

25. Chuan-Xi Li, Peng Chen, Ru-Jing Wang and Ya-Ru Su, Web entity extraction method based on entity attribute classification, In: Proceedings of the SPIE, Volume 8350, pp. 835014-835014-6 (2011) (EI, ISTP)

24. Yaru Su, Rujing Wang, Chuanxi Li, Peng Chen, A dynamic subspace learning method for tumor classification, In: The 7th International Conference on Natural Computation (ICNC’11), 2011, Volume: 1, Page(s): 396 - 400. (EI, ISTP)

23. Peng Chen, Consensus of sample-balanced classifiers for identifying ligand-binding residue by co-evolutionary physicochemical characteristics of amino acids, Emerging Intelligent Computing Technology and Application, 2013, Vol. 375, 206-212 (EI, ISTP)

22. B Wang, Peng Chen, J Zhang, Protein Interface Residues Prediction Based on Amino Acid Properties Only, Bio-Inspired Computing and Applications, Lecture Notes in Computer Science, 2012, Vol. 6840/2012, 448-452. (EI, ISTP)

2008-2010年：

21. Peng Chen, Jinyan Li, Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information, BMC Bioinformatics, 2010, 11:402. (SCI, JCR二区）

20. Peng Chen*, Chunmei Liu, Legand Burge, Jinyan Li, Mahmood Mohanmad, Bill Southerland, and Clay Gloster, DomSVR: Domain Boundary Prediction with Support Vector Regression from sequence information Alone, Amino Acids, 2010, 39(3), 713-726 . (SCI, JCR二区）

19. 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(Suppl 1):S2. (SCI)

18. Peng Chen*, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, Prediction of Inter-residue Contact Clusters from Hydrophobic Cores, International Journal of Data Mining and Bioinformatics, 2010, 4(6), 720-732. (SCI)

17. B. Wang, Peng Chen, J. Zhang, G. Zhao and X. Zhang, Inferring Protein-Protein Interactions Using a Hybrid Genetic Algorithm/Support Vector Machine Method, Protein & Peptide Letters, 17(9), Pp. 1079-1084, 2010. (SCI)

16. B. Wang , Peng Chen, P. Wang, G. Zhao and X. Zhang, Radial Basis Function Neural Network Ensemble for Predicting Protein-Protein Interaction Sites in Heterocomplexes, Protein & Peptide Letters, 17(9), Pp. 1111-1116, 2010. (SCI)

15. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, Protein Fold Classification with Genetic Algorithms and Feature Selection, Journal of Bioinformatics and Computational Biology, vol.7, no.5, pp. 773-788, 2009.

14. Peng Chen, Kyungsook Han, Xueling Li, D.S. Huang, Predicting Key Long-Range Interaction Sites by B-Factors. Protein & Peptide Letters. 15(5):478-483, 2008.(SCI)

13. Peng Chen, D.S. Huang, Predicting Contact Map Using Radial Basis Function Neural Network with Conformational Energy Function, International Journal of Bioinformatics Research and Applications, vol. 4, no.2, pp. 123 - 136, 2008.

12. Peng Chen, Jinyan Li, Prediction of Protein Long-Range Contacts Using GaMC Approach with Sequence Profile Centers, In: Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on, Washington DC, USA, 2009 128-135. (EI, ISTP)

11. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, William Southerland, and Clay Gloster, DomSVR: Domain Boundary Prediction with Support Vector Regression and Evolutionary Information, In: The 3rd International Conference on Bioinformatics and Biomedical Engineering (ICBBE 2009), China, 2009, 1-5. (EI, ISTP)

10. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohammad, Bill Southerland, Clay Gloster, Bing Wang, IRCDB: A Database of Inter-residues Contacts in Protein Chains, In: Advances in Databases, Knowledge, and Data Applications, 2009. DBKDA '09. First International Conference on, 1-6. (EI, ISTP)

9. Peng Chen, Chunmei Liu, Legand Burge, Mahmood Mohanmad, Bill Southerland, and Clay Gloster, Prediction of Inter-residue Contact Clusters from Hydrophobic Cores. In: Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on, San Diego, California, USA, 2008, 703-708. (EI, ISTP)

2007年及以前：

8. Peng Chen, Bing Wang, Hau San Wong, D.S., Huang, Prediction of Protein B-factors Using Multi-class Bounded SVM. Protein & Peptide Letters, vol.14, no.2, pp.185-190, 2007. (SCI)

7. Bing Wang, Peng Chen, D.S. Huang, Jing-Jing Li, Tat-Ming Lok, Michael R. Lyu, Predicting protein interaction sites from residue spatial sequence profile and evolution rate, FEBS Letters, vol.580, no.2, pp. 380-384, 2006. (Co-first author) (SCI)

6. Jing-Jing Li, D.S.Huang, Bing Wang, Peng Chen, Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores, International Journal of Biological Macromolecules, vol.38, nos.3-5, pp.241-247, 2006. (SCI)

5. Peng Chen, Bing Wang, Hau San Wong, D.S.Huang, Prediction of Long-range Contacts from Sequence Profile, In: Neural Networks, 2007. IJCNN 2007. International Joint Conference on, Orlando, Florida, USA, 2007, 938-943. (EI, ISTP)

4. Peng Chen, Hau-San Wong, Bing Wang and De-Shuang Huang, Long-range interaction analysis using principal component analysis, In: Neural Networks, 2006. IJCNN 2006. International Joint Conference on, Vancouver, British Columbia, Canada, 2006, 2331-2336. (EI, ISTP)

3. Peng Chen, De-Shuang Huang, Bing Wang, Prediction of contact map integrated PNN with conformational energy, In: Neural Networks, 2005. IJCNN 2005. International Joint Conference on, Montreal, Canada, 2005, 499- 502. (EI, ISTP)

2. Bing Wang, Hau San Wong, Peng Chen, Hong-Qiang Wang and De-Shuang Huang, Predicting protein-protein interaction sites using radial basis function neural networks, In: Neural Networks, 2006. IJCNN 2006. International Joint Conference on, Vancouver, British Columbia, Canada, 2006, 2325- 2330. (EI, ISTP)

1. Bing Wang, De-Shuang Huang, Peng Chen, Predicting protein-protein interactions based on protein-domain relationships, In: Neural Networks, 2005. IJCNN 2005. International Joint Conference on, Montreal, Canada, 2005, 316- 319. (EI, ISTP)