Dr. Bing Wang
Professor/Chair
Department of Electronics, Information & Communication Engineering
Anhui University of Technology
E-mail:wangbing@ustc.edu, wangb@ahut.edu.cn
Google Scholar: https://scholar.google.com/citations?user=312BcwEAAAAJ&hl=en
Brief Biography
Bing Wang received the B.S. degree from Hefei University of Technology in 1998 and the Ph.D. degree from University of Science and Technology of China in 2006, respectively. He was a senior research associate in City University of HongKong in 2007, postdoctorial research fellow in Univeristy of Louisville, and Vanderbilt University in 2008-2012, Currently he is a full professor in the School of Electrical and Information Engineering, and Chair of Department of Electronics, Information & Communication Engineering, Anhui University of Technology, China. His research interests mainly focus on machine learning, bioinformatics, biomedical data analysis, and signal & image processing. He has published over 100 peer-reviewed papers, and got more than 1,100 citations in the field. He is a senior member of IEEE from 2014, and served as editorial member for three journals.
Research Interests
Bioinformatics, Machine Learning, Biomedical data analysis, Chemoinformatics
Research Achievements:
Interdisciplinary training experience in engineering (MS), machine learning/bioinformatics (PhD), and chemoinformatics (Post-Doc), especially in protein interaction prediction.14+ years of research experience in interdisciplinary data analysis, 100+ publications and 1,100+ citations
Education
Dec. 2006, Ph.D., University of Science & Technology Science of China, Hefei, China
Mar. 2004, M.S., Hefei University of Technology, Hefei, China
Jul. 1998, B.Eng, Hefei University of Technology, Hefei, China
Professional Appointments
2013- , Professor/Chair, Department of Electronics Information & Commnication Engineering, Anhui University of Technology
2012-2017, Adjunct Professor, Department of Computer Science & Technology, Tongji University
2011-2012, Postdoctoral Research Fellow, Department of Biomedical Informatics, Vanderbilt University, TN
2008-2011, Postdoctoral Research Associate, Department of Chemistry,University of Louisville, KY
2007-2008, Associate Professor, Department of Electronic & Information Engineering, Anhui University of Technology
2006-2007, Senior Research Associate, Department of ComputerScience, City University of Hong Kong
Memberships
2014-Now, Senior Member, Institute of Electrical and Electronics Engineers (IEEE)
2013-Now, Member, International Neural Network Society (INNS)
Research Grants
2018-2022, Top talent of young scientist project, Anhui University of Technology, AHUT, RMB 400K, PI
2016-2018, Innovation team project of Anhui province, Anhui province, RMB 1,800K, PI
2015-2018, Data quality control and prediction of protein interaction based on network topological structure, NSFC, RMB 830K, PI
2015-2017, Protein interaction data denoising and network reconstruction based on manifold learning, AHNSF, RMB 80K, PI
2013-2013, Feature differential expression and cooperation in the prediction of protein interface residues, NSFC, RMB 200K, PI
2009-2011, Domain composition transformation-based protein interaction prediction, NSFC, RMB 240K, PI
Honors & Distinctions
2007, Chinese academy of sciences (CAS) Presidential Scholarship, CAS, China
2006, The Excellent PhD student scholarship, Institute of Intelligent Machines, CAS, China
2006, Guanghua scholarship, University of Science & Technology Science of China , China
Patents in China
1. A circular workpiece detection method based on artificial fish algorithm (201610374573.X);
2. A method for predicting the temperature of dead charge column in blast furnace core based on multivariate linear regression algorithm (2018110866348)
3. A Leaf Disease Recognition Method Based on Machine Learning Algorithms (2018110877658)
4. A progressive recognition method for mild cognitive impairment based on neuroimaging (201610393554.1)
5. A MOSFET for Improving UIS Avalanche Tolerance and Its Preparation Method (201810447829.4)
6. Mobility Improvement of 4H-SiC MOSFET Inverse Layer by Nitrogen and Boron (201711135993.3)
7. A Low Power 4H-SiC Voltage Controlled Power Semiconductor Device and Its Preparation Method (201610525827.3)
8. A single-end coated reflective long-period fiber grating sensor and its fabrication process and detection method of steel bar corrosion (201610410942.6)
9. A single-ended reflective long-period fiber grating sensor and its fabrication technology (201610410962.3)
10. A sensor for monitoring the corrosion status of steel bars and its fabrication process and detection method for steel bar corrosion (201610410965.7)
Publications:
Journal papers:
1. Bing Wang, Lili Peng, Nian Zhou, Peng Chen*, Jun Zhang, “Inferring Protein-Protein Interaction Sites Using Sequence Profile and Hydrophobic Information”, BMC Bioinformatics, 2019, Accepted.
2. ShanShan Hu, Peng Chen*, DeNan Xia, Bing Wang and Jinyan Li, “A New Structure of Convolutional Neural Networks to Discriminate Drug-target Interactions”. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2019. Minor revision.
3. Qingxin Xiao, Jun Zhang, Peng Chen*, Bing Wang*, “Prediction of the Occurrence of Pests and Diseases in Cotton with Bidirectional Recurrent Neural Networks”. BMC Medical Informatics and Decision Making. Accepted, 2019
4. Bing Wang, Changqing Mei, Yuanyuan Wan, Jun Zhang, Peng Chen*, Yan Xiong*, “An imbalance Data Processing Strategy for Protein Interaction Sites Prediction”, IEEE/ACM Transactions on Computational Biology and Bioinformatics 2019. Minor revision.
5. ShanShan Hu, Peng Chen*, Bing Wang and Jinyan Li, “Drug-target Interaction Predictions Based on A Convolutional Neural Network System”. BMC Genomics 2019. Accepted
6. Weilu Li, Peng Chen, Bing Wang*, Chengjun Xie, “Automatic Localization and Count of Agricultural Crop Pests Based on an Improved Deep Learning Pipeline”, Scientific Reports 2019, DOI:10.1038/s41598-019-43171-0
7. Zhuming Cheng, Jie Zeng, Dakai Liang, Chen Chang,Bing Wang. “Influence of Initial Phase Modulation on the Sensitivity of the Optical Fiber Sagnac Acoustic Emission Sensor”. Applied Science 2019, 9, 1018
8. Muchun Zhu, Xiaoping Song, Peng Chen*, Wenyan Wang and Bing Wang*, “dbHDPLS: Database of Human Disease Protein-Ligand Structure”. Computational Biology and Chemistry 2019, 78:353-358.
9. Quanya Liu, Bing Wang*, Peng Chen*, Zhang Jun. “Hot Spot prediction in protein-protein interactions by an ensemble learning”. BMC Systems Biology 2018, 12(9):132.
10. Fang Zhou, Tin-Yu Wu, Jun Liu, Bing Wang, and Mohammad S. Obaidat. “A 3D neural network for moving microorganism extraction”, Neural Computing & Applications, 2018. 30(1), pp: 57-67.
11. Denan Xia, Peng Chen*, Bing Wang, Jun Zhang, and Chenjun Xie, “Insect detection and classification based on improved convolutional neural network”. Sensors 2018, 18(12), 4169.
12. Ce Shi, Mu-Tian Cheng*, Xiao-San Ma, Dong Wang, Xianshan Huang, Bing Wang and Jia-Yan Zhang, “Nonreciprocal Single Photon Frequency Conversion via Chiral Coupling between a V-Type System and a Pair of Waveguides”, Chinese Physics Letters. 2018, 35:054202
13. Quanya Liu, Peng Chen*, Jun Zhang,Bing Wang* and Jinyan Li, “dbMPIKT: A kinetic and thermodynamic database of mutant protein interaction”. BMC Bioinformatics 2018,19:455.
14. Mu-Tian Cheng, Xiuwen Xia, Jingping Xu, Chengjie Zhu, Bing Wang, and Xiao-San Ma, “Single photon polarization conversion via scattering by a pair of atoms”, Optics Express, 2018, 26(22): 28872-28878
15. Yuming Zhou ,Hangzhi Liu, Tingting Yang and Bing Wang*, “SPICE modeling of SiC MOSFET considering interface-trap influence”, CPSS Transactions on Power Electronics and Applications 2018, 3(1): 56 – 64.
16. Bing Wang, Kun Lu, Xiao Zheng, Benyue Su, Yuming Zhou, Peng Chen*, Jun Zhang*, “Early Stage Identification of Alzheimer’s Disease Using a Two-stage Ensemble Classifier”, Current Bioinformatics, 2018, 13(5), 529-535.
17. Sen Xia, Peng Chen, Jun Zhang, Xiao-Ping Li, Bing Wang*, “Utilization of Rotation-Invariant Uniform LBP Histogram Distribution and Statistics of Connected Regions in Automatic Image Annotation Based on Multilabel Learning”, Neurocomputing, 2017,228: 11-18
18. Zhiwei Ji#, Bing Wang#, Ke Yan, Ligang Dong, Guanmin Meng, Lei Shi, “A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy”, BMC systems biology, 2017,11 (7), 127
19. Shan-Shan Hu, Peng Chen, Bing Wang*, Jinyan Li, “Protein binding hot spots prediction from sequence only by a new ensemble learning method”, Amino acids, 2017, 49 (10), 1773-1785
20. Jinjian Jiang, Nian Wang, Peng Chen, Chunhou Zheng, Bing Wang*, “Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System”, International journal of molecular sciences, 2017, 18 (7), 1543
21. Jun Zhang, MuchunZhu, Peng Chen, Bing Wang*, “DrugRPE: Random Projection Ensemble Approach to Drug-Protein Interaction Prediction”, Neurocomputing, 2017,228:256-262
22. Jinjian Jiang, Nian Wang, Peng Chen, Jun Zhang, and Bing Wang*, “DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction”, BioMed Research International, 2017, Article ID 6340316
23. Ke Yan, Bing Wang, Holun Cheng, Zhiwei Ji, Jing Huang, and Zhigang Gao, “Molecular Skin Surface-Based Transformation Visualization between Biological Macromolecules”, Journal of Healthcare Engineering , 2017, Article ID 4818604
24. 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
25. Bing Wang*, Hao Shen, Aiqin Fang, Changjun Jiang, Peng Chen, and Jun Zhang, “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, 1451:127-134.
26. Mu-Tian Cheng*, Wei-Wei Zong, Gen-Long Ye, Xiao-San Ma, Jia-Yan Zhang, and Bing Wang, “Single photon scattering properties in coupled-resonator waveguide coupling with a nanocavity interacting with an external mirror”, Communications in Theoretical Physics, 2016, 65:767.
27. Peng Chen, Jun Zhang, Xin Gao, Jinyan Li, and Jun-feng Xia, Bing Wang*, “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
28. Jun Zhang, 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
29. Rezaul Islam Khan, Yushu Wang, Shajia Afrin, Bing Wang, Yumin Liu, Xiaoqing Zhang, Lei Chen, Weiwen Zhang, Lin Gao, Gang Ma, “Transcriptional regulator PrqR plays a negative role in glucose metabolism and oxidative stress acclimation in Synechocystis sp. PCC 6803”, Scientific Reports, 2016, 6:32507.
30. Mu-Tian Cheng, Xiao-San Ma, Jia-Yan Zhang, and Bing Wang, “Single photon transport in two waveguides chirally coupled by a quantum emitter”, Optics Express, 2016, 24( 17): 19988-19993.
31. 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.
32. Zhiwei Ji, Guanmin Meng, Deshuang Huang, Xiaoqiang Yue, Bing Wang*, “NMFBFS: a NMF-based feature selection method in identifying pivotal clinical symptoms of Hepatocellular carcinoma”, Computational and Mathematical Methods in Medicine, 2015,2015:12
33. Zhiwei Ji, Bing Wang*, “Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm”, BioMed Research International, 2014,2014:12
34. Bing Wang*, De-shuang Huang, Changjun Jiang, "A new strategy for protein interface identification using manifold learning method". IEEE Transactions on NanoBioscience,2014, 13(2):118-2
35. Zhiwei Ji, Zhu-Hong You, Shuping Deng, Bing Wang*. “Predicting dynamic deformation of retaining structure by LSSVR-based time series method”, Neurocomputing, 2014, 137(5 ):165–172
36. 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
37. Zhu-Hong You, Ying-Ke Lei, Lin Zhu, Junfeng Xia, Bing Wang*. “Prediction of Protein-Protein Interactions from Amino Acid Sequences with Ensemble Extreme Learning Machines And Principal Component Analysis”. BMC Bioinformatics, 2013, 14(Suppl 8):S10
38. Lin Zhu, Zhu-Hong You,Bing Wang, De-Shuang Huang, “t-LSE:A Novel Robust Geometric Approach for Modeling Protein-Protein Interaction Networks”, Plos One, 2013,8(4): e58368
39. Jian-Xun Mi, De-shuang Huang, Bing Wang, Xingjie Zhu. “The Nearest-Farthest Subspace Classification for Face Recognition”. Neurocomputing, 2013, 113(3) :241-250
40. 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
41. Bing Wang*, “A Two-stage Peak Alignment Algorithm for Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-Based Metabolomics”, Computational and Structural Biotechnology Journal, 2013, 7(8): e201304002
42. Colins O. Eno, Guoping Zhao, Avinashanarayan Venkatanarayan, Bing Wang, Elsa R. Flores, Chi Li, “Noxa couples lysosomal membrane permeabilization and apoptosis during oxidative stress” Free Radical Biology & Medicine, 2013,65:26-37
43. Jun Zhang, Imhoi Koo, Bing Wang, Qingwei Gao, Chunhou Zheng. “A large scale test dataset to determine optimal retention index threshold based on three mass spectral similarity measures”. Journal of Chromatography A, 2012, 1251: 188-193
44. Junfeng Xia, Qingguo Wang, Peilin Jia, Bing Wang, William Pao, Zhongming Zhao, “NGS Catalog: A Database of Next Generation Sequencing Studies in Humans”. Human Mutation, 2012,33: E2341-2355
45. Xiaoli Wei, Wenlong Sun, Xue Shi, Imhoi Koo, Bing Wang, Jun Zhang, Xinming Yin, Tang, Y.; Bogdanov, B. Seongho Kim, Zhanxiang Zhou, McClain, C. J.; Xiang Zhang. “MetSign: A computational platform for high-resolution mass spectrometry-based metabolomics”. Analytical. Chemistry. 2011, 83, 7668-7675
46. Jun Zhang, Aiqin Fang, Bing Wang, Seong Ho Kim, Bogdan Bogdanov, Zhanxiang Zhou, Craig McClain and Xiang Zhang, “iMatch, A retention index tool for analysis of gas chromatography-mass spectrometry data”. Journal of Chromatography A, 2011, 1218:6522-6530
47. Seongho Kim, Aiqin Fang, Bing Wang, Jaesik Jeong and Xiang Zhang, “An Optimal Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry Using Mixture Similarity Measure”, Bioinformatics, 2011, 27(12):1660-1666
48. Yaping Zhao, Jun Zhang, Bing Wang, Seong Ho Kim, Aiqin Fang, Bogdan Bogdanov and Xiang Zhang, “A Method of Calculating the Second Dimension Retention Index in Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry”. Journal of Chromatography A, 2011, 1218(18) :2577-2583
49. Bing Wang, Aiqin Fang, John Heim, Bogdan Bogdanov, Scott Pugh, Mark Libardoni And Xiang Zhang, “DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics”, Analytical Chemistry, 2010, 82 (12): 5069–5081
50. Bing Wang, Peng Chen, Jun Zhang, Guangxin Zhao and Xiang Zhang, “Inferring protein-protein interactions using a hybrid genetic algorithm/support vector machine method” , Protein & Peptide Letters, Vol.17, 2010,17:1079-1084
51. Bing Wang, Steve Valentine, Manolo Plasencia, Sriram Raghuraman and Xiang Zhang, “Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry”, BMC Bioinformatics, 2010, 11:182
52. Bing Wang, Peng Chen, Peizhen Wang, Guangxin Zhao and Xiang Zhang, “Radial basis function neural network ensemble for predicting protein-protein interaction sites in heterocomplexes” Protein & Peptide Letters, 2010,17(9): 1111-1116
53. Bing wang, Steve Valentine, Manolo Plasencia, Sriram Raghuraman And Xiang Zhang, “Prediction of drift time in ion mobility-mass spectrometry based on peptide molecular weight”, Protein And Peptide Letters, 2010,17:1143-1147
54. Bing Wang, Fahim Mohammad, Jun Zhang, Xinmin Yiin, Eric Rouchka and Xiang Zhang, “Statistical Analysis of multiple significance test methods for differential proteomics”,BMC Bioinformatics, 2010,11(Suppl 4): 30
55. Peng Chen, Chunmei Liu, Legand Burge, Jinyan Li, Mahmood Mohammad, William Southerland, Clay Gloster and Bing Wang ,”DomSVR: domain boundary prediction with support vector regression from sequence information alone”, Amino Acids, 2010, 39(3):713-726
56. Bing Wang, Steve Valentine, Sriram Raghuraman, Manolo Plasencia and Xiang Zhang. “Prediction of peptide drift time in ion mobility-mass spectrometry” BMC Bioinformatics 2009, 10(Suppl 7):A1
57. Peng Chen, Bing Wang, Hau San Wong, D.S.Huang,“Prediction of Protein B-factors Using Multi-class Bounded SVM”. Proteins & Peptide Letters,pp.2007,14(2):185-190
58. 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, 2006,580(2):380-384
59. Bing Wang, Hau San Wong, D.S.Huang “Inferring Protein-Protein Interaction Sites From Residue Evolutionary Conservation Information”, Protein & Peptide Letters, 2006,13(10):999-1005
60. 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, 2006,38(3-5):241-247
61. Hong-Qiang Wang, D.S.Huang, Bing Wang, "Optimization of radial basis function classifiers using simulated annealing algorithm for cancer classification," IEE Electronics Letters, 2005,41(11):630-632
Journal papers in Chinese：
62. 周郁明, 刘航志, 杨婷婷, 王兵*, “碳化硅MOSFET电路模型及其应用”[J]. 《西安电子科技大学学报》, 2018,45(3):97-101
63. 周郁明, 刘航志, 杨婷婷, 王兵*, “碳化硅MOSFET的Matlab/Simulink建模及其温度特性评估”[J]. 南京航空航天大学学报, 2017, 49(6): 851-857
64. 马小陆, 王涛, 王兵, “负电容压电阻尼振动系统控制器参数研究”[J]，传感器与微系统，2011，30(9)：44-4 6.
65. 王兵,陈科, “液压系统噪声产生原因分析及对策”[J]，合肥工业大学学报, 2005, 25(s1)：.978-981.
Conference papers:
66. Run-xu Tan, Jun Zhang, Peng Chen, Bing Wang, and Yi Xia, “Cells Counting with Convolutional Neural Network” , 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China..
67. Ting-ting Han, Kai-chao Miao, Ye-qing Yao, Cheng-xiao Liu, Jian-ping Zhou, Hui Lu, Peng Chen, Xia Yi, Bing Wang, and Jun Zhang, “Convolutional Neural Network for Short Term Fog Forecasting Based on Meteorological Elements”, 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China..
68. Wei-wei Gao, Jun Zhang, Peng Chen, Bing Wang and Yi Xia, “Chinese Text Detection Using Deep Learning Model and Synthetic Data” , 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China.
69. 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” , 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China.
70. Qingxin Xiao, Weilu Li, Peng Chen, and Bing Wang,” Prediction of Crop Pests and Diseases in Cotton by Long Short Term Memory Network” , 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China..
71. ShanShan Hu, DeNan Xia, Peng Chen, and Bing Wang, “Using Novel Convolutional Neural Networks Architecture to Predict Drug-Target Interactions” , 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China.
72. Lili Peng, Nian Zhou, Peng Chen, Jun Zhang, Bing Wang*, “Prediction of Protein-Protein Interaction Sites combing Sequence Profile and Hydrophobic information”, 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China.
73. Nian Zhou, Lingshan Zhou, Lili Peng, and Bing Wang*, “Verifying TCM Syndrome Hypothesis Based on Improved Latent Tree Model”, 2018 International Conference on Intelligent Computing, August 15-18, 2018, Wuhan, China.
74. Changqing Mei, Yuanyuan Wang, Kun Lu, Yuming Zhou, Peng Chen, Bing Wang*, “Unbalance Data Processing Strategy for Protein Interaction Sites Prediction”, 9th International Conference on IT in Medicine and Education (ITME 2018), 2018, Oct. 19-21, Hangzhou, China.
75. Wenyan Wang, Kun Lu, Rui Hong, Peng Chen, Jun Zhang, Bing Wang*, “A Machine Vision Method for Automatic Circular Parts Detection Based on Optimization Algorithm”, International Conference on Intelligent Computing, 2017, 600-611
76. Feng-Lin Du, Jia-Xing Li, Zhi Yang, Peng Chen, Bing Wang, Jun Zhang.”Captcha recognition based on faster R-CNN”, International Conference on Intelligent Computing, 2017, 597-605
77. Yuming Zhou, Yongjie Li, Bing Wang*, “Spice modeling of 4H-SiC MOSFET based on the advanced mobility model”, 2016 IEEE 4th Workshop of WiPDA, 2016, 1-7
78. Zhongwen Zhang, Peng Chen, Jun Zhang, and Bing Wang*, “Inferring Disease-Related Domain Using Network-Based Method”, International Conference on Intelligent Computing (ICIC 2016), in Lanzhou, Ganshu, China, August 20-23, 2016, 9771: 775–783.
79. Zhen Sun, Jun Zhang, Chun-Hou Zheng, Bing Wang, Peng Chen, “Accurate prediction of protein hotspots residues based on gentle adaboost algorithm”, International Conference on Intelligent Computing, in Lanzhou, China, August 2-4, 2016: 742-749.
80. Bing Wang, Rui Hong, Yanhui Xu, Fang Zhou, Peizhen Wang, “Identifying Mild Cognitive Impairment Conversion to Alzheimer’s Disease from Medical Image Information”, IEEE International Conference on Consumer Electronics-Taiwan, in Nantou ,Taiwan, May 27-29, 2016.
81. Fang Zhou, Jun Liu, Bing Wang, Peizhen Wang. “An Improved Multilayer Self-Organizing Background Subtraction Algorithm for Microorganism Detection in Sewage”, IEEE International Conference on Consumer Electronics-Taiwan, in Nantou ,Taiwan, May 27-29, 2016.
82. Peizhen Wang, Rui Sun, Dailin Zhang, Fang Zhou, Bing Wang*, “Classification of Inertinite in Coal Macerical Based on Virtual Sample”, IEEE International Conference on Consumer Electronics-Taiwan, in Nantou ,Taiwan, May 27-29, 2016.
83. Hao Shen, Wen Zhang, Peng Chen, Jun Zhang, Aiqin Fang, and Bing Wang*, “A Feature Selection Scheme for Accurate Identification of Alzheimer’s Disease”, The 4rd International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2016), in Granada, Spain, April 20-23, 2016.
84. ShanShan Hu, Peng Chen, Jun Zhang, Bing Wang, “Prediction of Hot Spots Based on Physicochemical Features and Relative Accessible Surface Area of Amino Acid Sequence” , International Conference on Intelligent Computing (ICIC 2016), in Lanzhou, Ganshu, China, August 20-23, 2016: 422-431
85. Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, “A Random Projection Ensemble Approach to Drug-Target Interaction Prediction”, International Conference on Intelligent Computing (ICIC 2015), in Fuzhou, Fujian, China, August 20-23, 2015(9227): 693-699.
86. Peng Chen, ShanShan Hu, Bing Wang, Jun Zhang, “Sequence-Based Random Projection Ensemble Approach to Identify Hotspot Residues from Whole Protein Sequence”, International Conference on Intelligent Computing (ICIC 2015), in Fuzhou, Fujian, China, August 20-23, 2015(9226): 379-389.
87. Bing Wang*, Liyan Du, Jun Zhang, Peng Chen, “A Hierarchical Model for Identifying Mild Cognitive Impairment”,The 11th International Conference on Natural Computation, in Zhangjiajie, Hunan,China, August 15-17, 2015.
88. Wen Zhang, Hao Shen, Zhiwei Ji, Guanmin Meng, Bing Wang*, “Identification of Mild Cognitive Impairment Using Extreme Learning Machines Model”, International Conference on Intelligent Computing (ICIC 2015), in Fuzhou, Fujian, China, August 20-23, 2015.
89. 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”, International Conference on Intelligent Computing (ICIC 2015), in Fuzhou, Fujian, China, August 20-23, 2015.
90. Bing Wang* De-shuang Huang, “Dataset Reconstruction for Protein Interface Identification Using Manifold Learning Method”, The 2013 International Conference on BioInformation and BioMedicine (BIBM 2013), in Shanghai, China, Dec 18-21, 2013.
91. Bing Wang*, Zhiwei Ji, “Disease-related gene expression analysis using an ensemble statistical test method”, International Conference on Intelligent Computing (ICIC 2013), in Nanning, Guanxi China, August 1-3, 2013.
92. Bing Wang*, Peng Chen, Jun Zhang. “Protein interface residues prediction based on amino acid properties only”. International Conference on Intelligent Computing (ICIC 2011), in Zhengzhou, Henan, China, August 11-14, 2011
93. Bing Wang, Aiqin Fang, Xue Shi, Seong Ho Kim, Xiang Zhang. “A Comprehensive Peak Alignment Algorithm for Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry”. in Zhengzhou, Henan, China, August 11-14, 2011International Conference on Intelligent Computing (ICIC 2011),
94. Bing Wang, Jun Zhang, and Xiang Zhang “Multiple linear regression for peptides drift time prediction”, the 2010 International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics (BCBGC-10), in Orlando, FL, USA, July 12-14, 2010.
95. XiaoDong Dai, Bing Wang*, Peizhen Wang: “Palmprint recognition combining LBP and cellular automata”. International Conference on Intelligent Computing （ICIC 2010）: 460-466.
96. Jun Zhang, Bing Wang, Xiang Zhang: “Optimal selection of support vector regression parameters and molecular descriptors for retention indices Prediction”. International Conference on Intelligent Computing （ICIC 2010）: 83-90.
97. 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.
98. Jun-Feng Xia, Bing Wang and De-Shuang Huang, “Inferring Strengths of Protein-Protein Interaction Using Artificial Neural Network” The 2007 International Joint Conference on Neural Networks (IJCNN2007), Orlando, Florida, USA p.2471-2475.
99. Bing Wang, Lu-Sheng Ge, Hau San Wong and D.S.Huang, "Prediction of protein-protein interaction sites by combining SVM algorithm with Bayesian method", The 3rd International Conference on Natural Computation, in Haikou, China, August 24- 27 , 2007, 2:329-333.
100. Bing Wang, Lu-Sheng Ge, Wen-You Jia, Li Liu and Fu-Chun Chen, "Prediction of Protein-Protein Interactions by Combining Genetic Algorithm with SVM Method", The 2007 IEEE Congress on Evolutionary Computation, in the Swissotel The Stamford, Singapore, September 26, 2007，pp.320-325.
101. 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,” The 2006 International Joint Conference on Neural Networks (IJCNN2006), Sheraton Vancouver Wall Centre, Vancouver, BC, Canada, 16-21 July 2006, pp.2325–2330.
102. Peng Chen, Bing Wang, Hau San Wong, D.S.Huang, “Long-Range Interaction Analysis using Principal Component Analysis,” The 2006 International Joint Conference on Neural Networks (IJCNN2006), Sheraton Vancouver Wall Centre, Vancouver, BC, Canada, 16-21 July 2006, pp.2331– 2336.
103. Peng Chen, Bing Wang, D. S. Huang, Yunping Zhu and Yixue Li, “Prediction of contact map integrated PNN with conformational energy,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.1, 31 July-4 Aug. 2005. pp. 499-502.
104. Bing Wang, D. S. Huang, Peng Chen, Yunping Zhu and Yixue Li, “Predicting Protein-Protein Interactions Based on Protein-Domain Relationships,” The 2005 International Joint Conference on Neural Networks (IJCNN2005), Montreal, Quebec, Canada, Vol.1, 31 July-4 Aug. 2005. pp.316-319.
Book Chapter:
105. Bing Wang and Xiang Zhang “Evolutionary computation applications in current bioinformatics”, New Achievements In Evolutionary Computation, book edited by: Peter Korosec, ISBN: 978-953-307-053-7, Publisher: Intech, Publishing Date: February 2010.
