EDUCATION
B.S. Computer Science and Technology Hohai University (HHU), Nanjing, China (2002)
M.S. Computer Software and Theory Hohai University (HHU), Nanjing, China (2005)
Ph.D. Student Computer Science Utah State University (USU), Logan, USA (2006-2007)
Ph.D. Student Computer Science University of Georgia (UGA), Athens, USA (2008 - present)
Research Interests
Bioinformatics, Algorithms, Machine Learning
Selected Publication
Master Thesis
“Sensitivity Study of Madalines”, awarded by the Provincial Excellent Master Thesis of Jiangsu, advisor: Prof. Xiaoqin Zeng.
Journal
Yingfeng Wang, Amir Manzour, Pooya Shareghi, Timothy I. Shaw, Ying Wai Li, Russell L. Malmberg, and Liming Cai, “Stable Stem Enabled Shannon Entropies Distinguish Noncoding RNAs from Random Backgrounds,” BMC Bioinformatics, accepted. (see also ICCABS 2011)
Timothy I. Shaw, Amir Manzour, Yingfeng Wang, Russell L. Malmberg, and Liming Cai, “Analyzing Modular RNA Structure Reveals Low Global Structural Entropy in MicroRNA Sequence,” Journal of Bioinformatics and Computational Biology, vol.9, no.2, pp.283-298, 2011. (see also CSB 2010)
Leilei Guo, Dong Zhang, Yingfeng Wang, Russell L. Malmberg, Michael J. McEachern and Liming Cai, “TRFolder: Computational Prediction of Novel Telomerase RNA Structures in Yeast Genomes,” International Journal of Bioinformatics Research and Applications, vol.7, no.1, pp.63-81, 2011.
Yingfeng Wang, Zhibin Huang, Yong Wu, Russell L. Malmber and Liming Cai, “RNATOPS-W: a web server for RNA structure searches of genomes,” Bioinformatics, vol. 25, no. 8, pp. 1080-1081, 2009.
Xiaoqin Zeng, Jing Shao, Yingfeng Wang and Shuiming Zhong “A sensitivity-based approach for pruning architecture of Madalines,” Neural Computing & Applications, vol. 18, no. 8, pp. 957-965, 2009.
Yingfeng Wang, Xiaoqin Zeng, Daniel So Yeung and Zhihang Peng, “Computation of Madalines’ Sensitivity to Input and Weight Perturbations,” Neural Computation, vol. 18, no. 11, pp. 2854-2877, 2006.
Xiaoqin Zeng, Yingfeng Wang and Kang Zhang, “Computation of Aadalines’ Sensitivity to Weight Perturbation,” IEEE Transactions on Neural Networks, vol. 17, no. 2, pp. 515-519, 2006.
Lecture Notes
Yingfeng Wang, Xiaoqin Zeng and Daniel S. Yeung, “Sensitivity Analysis of Madalines to Weight Perturbation,” Lecture Notes in Artificial Intelligence, vol. 3930, pp. 822-831, 2006. (see also ICMLC2005)
Conference
Pooya Shareghi, Yingfeng Wang, Russell L. Malmberg, and Liming Cai, “Simultaneous Prediction of RNA Secondary Structure and Helix Coaxial Stacking,” Proceedings of 2011 IEEE International Conference on Bioinformatics and Biomedicine, pp.89-95, Nov. 2011. (The journal version of this paper has been selected to BMC Genomics)Yingfeng Wang, Amir Manzour, Pooya Shareghi, Timothy I. Shaw, Ying-Wai Li, Russell L. Malmberg, and Liming Cai, “Stable Stem Enabled Shannon Entropies Distinguish Noncoding RNAs from Random Backgrounds,” Proceedings of 1st IEEE International Conference on Computational Advances in Bio and medical Sciences, pp.184-189, Feb. 2011. (The journal version of this paper has been invited to submit to BMC Bioinformatics)
Timothy I. Shaw, Amir Manzour, Russell L. Malmberg, Yingfeng Wang and Liming Cai, “Analyzing Modular RNA Structure Reveals Low Global Structural Entropy in MicroRNA Sequence,” Proceedings of 9th Annual International Conference on Computational Systems Bioinformatics pp. 146-155, Aug. 2010. (The journal version of this paper has been selected to publish in Journal of Bioinformatics and Computational Biology)
Yingfeng Wang and Xiaoqin Zeng, “Using a Sensitivity Measure to Improve Training Accuracy and Convergence for Madalines,” Proceedings of International Joint Conference on Neural Networks pp. 1750-1756, Jul. 2006.
Yingfeng Wang, Xiaoqin Zeng and Daniel S. Yeung, “Analysis of Sensitivity Behavior of Madalines,” Proceedings of IEEE International Conference on Machine Learning and Cybernetics, pp. 4731-4737, Aug. 2005. (This paper has been selected to be published in Lecture Notes in Artificial Intelligence)
Yingfeng Wang, Xiaoqin Zeng and Lixin Han, “Sensitivity of Madalines to Input and Weight Perturbations,” Proceedings of IEEE International Conference on Machine Learning and Cybernetics, pp.1349-1354, Nov. 2003.
