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Publications

Journal Papers:

  1. M. Yang, Yaohang Li, J. Wang, “Feature and Nuclear Norm Minimization for Matrix Completion,” IEEE Transactions on Knowledge and Data Engineering, in press, 2020.

  2. W. Elhefnawy, M. Li, J. Wang, Yaohang Li, “DeepFrag-k: a fragment-based deep learning approach for protein fold recognition,” BMC Bioinformatics, in press, 2020.

  3. H. Luo, M. Yang, M. Li, Yaohang Li, F. Wu, J. Wang, “Biomedical data and computational models for drug repositioning: a comprehensive review,” Briefings in Bioinformatics, bbz176, 2020.

  4. H. Ji, M. Mascagni, Yaohang Li, “Gaussian Variant of Freivalds' Algorithm for Efficient and Reliable Matrix Product Verification,” Monte Carlo Methods and Applications, in press, 2020.

  5. H. Jiang, M. Yang, X. Chen, M. Li, Yaohang Li, J. Wang, “miRTMC: A miRNA target prediction method based on matrix completion algorithm,” IEEE Journal of Biomedical and Health Informatics, accepted, 2020.

  6. M. Zeng, C. Lu, Z. Fei, F. Wu, Yaohang Li, J. Wang, M. Li, “DMFLDA: A deep learning framework for predicting IncRNA–disease associations,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2020.

  7. M. Zeng, C. Lu, F. Zhang, Y. Li, F. Wu, Yaohang Li, M Li, “SDLDA: lncRNA–disease association prediction based on singular value decomposition and deep learning,” Methods, 179: 73-80, 2020.

  8. D. Guo, G. Duan, Y. Yu, Yaohang Li, F. Wu, M. Li, “A disease inference method based on symptom extraction and bidirectional Long Short Term Memory networks,” Methods, 173: 75-82, 2020.

  9. F. Zhang, H. Song, M. Zeng, Yaohang Li, F. Wu, Y. Pan, M. Li, “A deep learning framework for gene ontology annotations with sequence- and network-based information,” IEEE/ACM transactions on computational biology and bioinformatics, in press, 2020.

  10. M. Zeng, F. Zhang, F. Wu, Yaohang Li, J. Wang, M. Li, “Protein–protein interaction site prediction through combining local and global features with deep neural networks,” Bioinformatics, 36(4): 1114-1120, 2020.

  11. C. Lu, M. Yang, M. Li, Yaohang Li, F. Wu, J. Wang, "Predicting human lncRNA-disease associations based on geometric matrix completion," IEEE Journal of Biomedical and Health Informatics, 24(8): 2420-2429, 2019.

  12. G. Li, M. Li, J. Wang, Yaohang Li, Y. Pan, "United neighborhood closeness centrality and orthology for predicting essential proteins," IEEE/ACM transactions on computational biology and bioinformatics, 17(4): 1451-1458, 2018.

  13. M. Yang, H. Luo, F. Wu, Yaohang Li, J. Wang, "Overlap matrix completion for predicting drug-associated indications," PLOS Computational Biology, 15(12): e1007541, 2019.

  14. M. Zeng, M. Li, F. Wu, Yaohang Li, Y Pan, “DeepEP: a deep learning framework for identifying essential proteins,” BMC Bioinformatics, 20(S16): 506, 2019.  

  15. W. Elhefnawy, M. Li, J. Wang, Yaohang Li, "Decoding the Structural Keywords in Protein Structure Universe,"  Journal of Computer Science and Technology, 34(1): 3-15, 2019.

  16. Z. Haratipour, H. Aldabagh, Yaohang Li, L. H. Greene, "Network Connectivity, Centrality and Fragmentation in the Greek-Key Protein Topology," The Protein Journal, 38(5): 497-505, 2019.

  17. G. Li, M. Li, W. Peng, Yaohang Li, Y. Pan, J. Wang, "A novel extended Pareto Optimality Consensus model for predicting essential proteins," Journal of Theoretical Biology, 480: 141-149, 2019.

  18. M. Zeng, F. Zhang, F. X. Wu, Yaohang Li, J. Wang, M. Li, "Protein–protein interaction site prediction through combining local and global features with deep neural networks," Bioinformatics, 36(4): 1114-1120 , 2019.

  19. Y. Yu, M. Li, L. Liu, Yaohang Li, J. Wang, "Clinical big data and deep learning: Applications, challenges, and future outlooks," Big Data Mining and Analytics, 2(4): 288-305, 2019.

  20. D. Guo, G. Duan, Y. Yu, Yaohang Li, F. X. Wu, M. Li, "A disease inference method based on symptom extraction and bidirectional Long Short Term Memory networks," Methods, 173: 75-82 , 2019.

  21. M. Yang, H. Luo, Yaohang Li, J. Wang, "Drug repositioning based on bounded nuclear norm regularization," Bioinformatics, 35(14): i455-i463, 2019.

  22. F. Zhang, H. Song, M. Zeng, Yaohang Li, L. Kurgan, M. Li, "DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions," Proteomics, 1900019, 2019.

  23. X. Chen, M. Li, R. Zheng, S. Zhao, F. X. Wu, Yaohang Li, J. Wang, "A novel method of gene regulatory network structure inference from gene knock-out expression data," Tsinghua Science and Technology, 24(4):446-455, 2019.

  24. M. Zeng, M. Li, Z. Fei, F. Wu, Yaohang Li, Y. Pan, J. Wang, "A deep learning framework for identifying essential proteins by integrating multiple types of biological information," IEEE/ACM transactions on computational biology and bioinformatics, in press, 2019.

  25. H. Luo, M. Li, S. Wang, Q. Liu, Yaohang Li, J. Wang, "Computational Drug Repositioning using Low-Rank Matrix Approximation and Randomized Algorithms," Bioinformatics, 34(11):1904-1912 , 2018.

  26. A. Ramlatchan, M. Yang, Q. Liu, M. Li, J. Wang, Yaohang Li, "A Survey of Matrix Completion Methods for Recommendation Systems," Big Data Mining and Analytics, 1(4): 308-323, 2018.

  27. W. Yu, Y. Gu, Yaohang Li, "Efficient Randomized Algorithms for the Fixed-Precision Low-Rank Matrix Approximation," SIAM Journal on Matrix Analysis and Applications, 39(3): 1339-1359, 2018.

  28. C. Lu, M. Yang, F. Luo, F. Wu, M. Li, Y. Pan, Yaohang Li, J. Wang, "Prediction of lncRNA-Disease Associations based on Inductive Matrix Completion," Bioinformatics, 34(19):3357-3364 , 2018.

  29. P. Ni, J. Wang, P. Zhong, Yaohang Li, F. Wu, Y. Pan, "Constructing Disease Similarity Networks Based on Disease Module Theory," IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2018.

  30. M. Li,  Z. Fei,  M. Zeng,  F. Wu,  Yaohang Li,  Y. Pan,  J. Wang, "Automated ICD-9 Coding via A Deep Learning Approach," IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2018.

  31. M. Abdelrasoul, K. Ponniah, A. Mao, M. S. Warden, W. Elhefnawy, Yaohang Li, S. M. Pascal, "Conformational Clusters of Phosphorylated Tyrosine," Journal of the American Chemical Society, 139: 17632-17638, 2017.

  32. Y. Liang, X. Xing, Yaohang Li, "A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions," Journal of Computational Physics, 338: 252-268, 2017.

  33. M. Li, X. Meng, R. Zheng, F. Wu, Yaohang Li, Y. Pan, J. Wang, "Identification of protein complexes by using a spatial and temporal active protein interaction network," IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2017.

  34. M. Li, R. Zheng, Yaohang Li, F. Wu, J. Wang, "MGT-SM: A Method for Constructing Cellular Signal Transduction Networks," IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press, 2017.

  35. H. Ji, Yaohang Li, "Block Conjugate Gradient Algorithms for Least Squares Problems," Journal of Computational and Applied Mathematics, 317: 203-217, 2017.

  36. J. L. Hung, M. C. Wang, S. Wang, M. Abdelrasoul, Yaohang Li, W. He, "Identifying At-Risk Students for Early Interventions - A Time Series Clustering Approach," IEEE Transactions on Emerging Topics in Computing, 5(1): 45-55, 2017.

  37. H. Ji, Yaohang Li, "A Breakdown-Free Block Conjugate Gradient Method," BIT Numerical Mathematics, 57(2): 379-403, 2017.

  38. X. Feng, K. Li, W. Yu, Yaohang Li, “Fast matrix completion algorithm based on randomized singular value decomposition and its applications,” Journal of Computer-Aided Design & Computer Graphics, 12: 193-198, 2017.

  39. H. Ji, Yaohang Li, S. Weinberg, "Calcium Ion Fluctuations Alter Channel Gating in a Stochastic Luminal Calcium Release Site Model," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(3): 611-619, 2017.

  40. J. López-Blanco, A. Canosa-Valls, Yaohang Li, P. Chacón, "RCD+: Fast loop modeling server," Nucleic Acids Research, 44(W1): W395-W400, 2016.

  41. A. Yaseen, M. Nijim, B. Williams, L. Qian, J. Wang, M. Li, Yaohang Li, "FLEXc: Protein Flexibility Prediction using Context-based Statistics, Predicted Structural Features, and Sequence Information," BMC Bioinformatics, 17(S8):281, 2016.

  42. A. Yaseen, H. Ji, Yaohang Li, "A Load-Balancing Workload Distribution Scheme for Three-Body Interaction Computation on Graphics Processing Units (GPU)," Journal of Parallel and Distributed Computing, 87: 91-101, 2016.

  43. Y. Liang, D. Wu, G. Liu, Yaohang Li, C. Gao, Z. Ma, W. Wu, "Big Data-enabled Multiscale Serviceability Analysis for Aging Bridges," Digital Communications and Networks, 2(3): 97-107, 2016.

  44. W. Lan, J. Wang, M. Li, J. Liu, Yaohang Li, F. Wu, Y. Pan, "Predicting drug–target interaction using positive-unlabeled learning," Neurocomputing, 206: 50-57, 2016.

  45. B. Zhao, J. Wang, M. Li, X. Li, Yaohang Li, F. Wu, Y. Pan, "A new method for predicting protein functions from dynamic weighted interactome networks," IEEE Transactions on NanoBioscience, 15(2): 131-139, 2016.

  46. W. Elhefnawy, L. Chen, Y. Han, Yaohang Li, “ICOSA: A Distance-dependent, Orientation-specific Coarse-grain Contact Potential for Protein Structure Modeling,” Journal of Molecular Biology, 427(15): 2562-2576, 2015.

  47. W. He, J. Shen, X. Tian, Yaohang Li, A. Akula, G. Yan, R. Tao, “Gaining Competitive Intelligence from Social Media Data: Evidence from Two Largest Retail Chains in the World,” Industrial Management & Data Systems, 115(9): 1622-1636, 2015.

  48. A. Yaseen, Yaohang Li, “Context-based Features Enhance Protein Secondary Structure Prediction Accuracy,” Journal of Chemical Information and Modeling, 54(3): 992-1002, 2014.

  49. W. He, A. Kshirsagar, A. Nwala, Yaohang Li, “Teaching Information Security with Workflow Technology – A Case Study Approach,” Journal of Information Systems Education, 25(3): 201-210, 2014.

  50. A. Yaseen, Yaohang Li, “Template-based C8-SCORPION: a Protein 8-state Secondary Structure Prediction Method using Structural Information and Context-based Features,” BMC Bioinformatics, 15(S8): S3, 2014.

  51. H. Ji, M. Mascagni, Yaohang Li, “Convergence Analysis of Markov Chain Monte Carlo Linear Solvers using Ulam-von Neumann Algorithm,” SIAM Journal on Numerical Analysis, 51(4): 2107-2122, 2013.

  52. A. Yaseen, Yaohang Li, “Dinosolve: A Protein Disulfide Bonding Prediction Server using Context-based Features to Enhance Prediction Accuracy,” BMC Bioinformatics, 14(S13): S9, 2013.

  53. L. Tran, D. Banerjee, J. Wang, A. Kumar, F. McKenzie, Yaohang Li, J. Li, “High-Dimensional MRI Data Analysis using a Large-Scale Manifold Learning Approach,” Machine Vision and Applications, 24(5): 995-1014, 2013.

  54. Yaohang Li, “Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview,” Computational and Structural Biotechnology Journal, 5(6): e201302003, 2013.

  55. Yaohang Li, H. Liu, I. Rata, E. Jakobsson, “Building a Knowledge-based Statistical Potential by Capturing High-Order Inter-Residue Interactions and its Applications in Protein Secondary Structure Assessment,” Journal of Chemical Information and Modeling, 53(2): 500-508, 2013.

  56. Yaohang Li, “MOMCMC: An Efficient Monte Carlo Method for Multi-Objective Sampling over Real Parameter Space,” Computers and Mathematics with Applications, 64: 3542-3556, 2012.

  57. A. Yaseen, Yaohang Li, “Accelerating Knowledge-based Energy Evaluation in Protein Structure Modeling with Graphics Processing Units,” Journal of Parallel and Distributed Computing, 72(2): 297-307, 2012.

  58. Yaohang Li, I. Rata, E. Jakobsson, “Sampling Multiple Scoring Functions Can Improve Protein Loop Structure Prediction Accuracy,” Journal of Chemical Information and Modeling, 51(7): 1656-1666, 2011.

  59. W. Zhu, A. Yaseen, Yaohang Li, “DEMCMC-GPU: An Efficient Multi-Objective Optimization Method with GPU Acceleration on the Fermi Architecture,” New Generation Computing, 29(2): 163-184, 2011.

  60. Yaohang Li, I. Rata, S. Chiu, E. Jakobsson, “Improving Predicted Protein Loop Structure Ranking using a Pareto-Optimality Consensus Method,” BMC Structural Biology, 10: 22, 2010.

  61. I. Rata, Yaohang Li, E. Jakobsson, “Backbone Statistical Potential from Local Sequence-Structure Interactions in Protein Loops,” Journal of Physical Chemistry B, 114(5): 1859-1869, 2010.

  62. Yaohang Li, V. A. Protopopescu, N. Arnold, X. Zhang, A. Gorin, “Hybrid Parallel Tempering/Simulated Annealing Method,” Applied Mathematics and Computation, 212: 216-228, 2009.

  63. Yaohang Li, M. Mascagni, A. Gorin “A Decentralized Parallel Implementation for Parallel Tempering Algorithm,” Parallel Computing, 35(5): 269-283, 2009.

  64. Yaohang Li, C. E. M. Strauss, A. Gorin, “Hybrid Parallel Tempering and Simulated Annealing Method – an Efficient Sampling Method in ab initio Protein Folding,” International Journal of Computational Science, 2(5): 646-661, 2008.

  65. Yaohang Li, Y. D. Song, “An Adaptive and Trustworthy Software Testing Framework on the Grid,” Journal of Supercomputing, 46: 124-138, 2008.

  66. Yaohang Li, D. Chen, X. Yuan, “Trustworthy Remote Compiling Service for Grid-based Scientific Applications,” Journal of Supercomputing, 41(2):119-131, 2007.

  67. Yaohang Li, “A Bio-inspired Adaptive Job Scheduling Mechanism on the Grid,” International Journal of Computer Science and Network Security, 6(3B): 1-7, 2006.

  68. Yaohang Li, M. Mascagni, “Grid-based Quasi-Monte Carlo Applications,” Monte Carlo Methods and Applications, 11: 39-55, 2005.

  69. Yaohang Li, V. A. Protopopescu, A. Gorin, “Accelerated Simulated Tempering,” Physics Letters A, 328(4): 274-283, 2004.

  70. Yaohang Li, M. Mascagni, R. van Engelen, Q. Cai, “A Grid Workflow-Based Monte Carlo Simulation Environment,” Journal of Neural Parallel and Scientific Computations, 12:439-455, 2004.

  71. Yaohang Li, M. Mascagni, “Analysis of Large-scale Grid-based Monte Carlo Applications,” International Journal of High Performance Computing Applications (IJHPCA), 17(4): 369-382, 2003.

  72. Y. Zhang, Yaohang Li, M. H. Peters, “Nonequilibrium, Multiple-Time Scale Simulations of Ligand-Receptor Interactions in Structured Protein Systems,” Proteins: Structure, Function, and Genetics, 52(3): 339-348, 2003.

  73. M. Mascagni, A. Karaivanova, Yaohang Li, “Quasi-Monte Carlo method for elliptic boundary value problems”, Monte Carlo Methods and Applications, 7: 283-294, 2001.

Book Chapters:

  1. L. Kurgan, M. Li, Yaohang Li, "The Methods and Tools for Intrinsic Disorder Prediction and Their Application to Systems Medicine," Elsevier, 2019.

  2. Y. Liang, D. Wu, D. Huston, G. R. Liu, Yaohang Li, C. Gao, J. Ma, "Civil Infrastructure Serviceability Evaluation Based on Big Data," Guide to Big Data Application, Springer Publishing, 2017.

  3. H. Ji, Yaohang Li, “Monte Carlo Methods and their Applications in Big Data Analysis,” Mathematical Problems in Data Science - Theoretical and Practical Methods, Springer, ISBN: 978-3-319-25127-1, 2015.

  4. Yaohang Li, M. Mascagni, “An Overview of Grid-based Monte Carlo Computing,” Grid Technologies, Emerging from Distributed Architectures to Virtual Organizations, WIT Press, ISBN: 978-1-84564-055-2, 2006.

  5. Y. D. Song, Yaohang Li, M. Bikdash, T. Dong, ”Cooperative Control of Multiple UAV’s in Close Formation Flight via Nonlinear Adaptive Approach,” Theory and Algorithms for Cooperative Systems, World Scientific Publishing Company, ISBN: 978-9-81256-020-9, 2004.

Selected Papers in Conference Proceedings:

  1. W. Xuan, N. Liu, N. Huang, Yaohang Li, J. Wang, “CLPred: A sequence-based protein crystallization predictor using BLSTM neural network,” 19th European Conference on Computational Biology (ECCB2020), accepted, 2020.

  2. G. Wu, M. Yang, Yaohang Li, J. Wang, “De novo prediction of drug-target interaction via Laplacian regularized Schatten-p norm minimization,” International Symposium on Bioinformatics Research and Applications (ISBRA2020), accepted, 2020.

  3. M. Yang, H. Luo, Yaohang Li, J. Wang, "Drug repositioning based on bounded nuclear norm regularization," Proceedings of the 27th Conference on Intelligent Systems for Molecular Biology and the 19th European Conference on Computational Biology (ISMB/ECCB-2019), Basel, 2019.

  4. Q. Zhao, F. Xiao, M. Yang, Yaohang Li, J. Wang, “AttentionDTA: prediction of drug–target binding affinity using attention model,” Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM2019), San Diego, 2019.

  5. M. Zeng, C. Lu, F. Zhang, Z. Lu, F. Wu, Yaohang Li, M. Li, “LncRNA–disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques,” Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM2019), San Diego, 2019

  6. W. Elhefnawy, Yaohang Li, "DeepFrag-k: A Fragment-based Deep Learning Approach for Protein Fold Recognition," Proceedings of International Symposium on Bioinformatics Research and Applications (ISBRA2019), Barcelona, 2019.

  7. D. Guo, M. Li, Y. Yu, Yaohang Li, G. Duan, F. Wu, J. Wang, "Disease Inference with Symptom Extraction and Bidirectional Recurrent Neural Network," Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018.

  8. M. Zeng, M. Li, Z. Fei, F. Wu, Yaohang Li, Y. Pan, "A deep learning framework for identifying essential proteins based on protein-protein interaction network and gene expression data," Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018.

  9. X. Feng, W. Yu, Yaohang Li, "Faster Matrix Completion Using Randomized SVD," Proceedings of the 30th IEEE International Conference on Tools with Artificial Intelligence, (ITCAI2018), Volos, 2018.

  10. M. Abdelrasoul, Yaohang Li, "Exploring Multi-Objective with Protein Sequence Alignment," Proceedings of the 10th International Conference on Bioinformatics and Computational Biology, (BICoB-2018), Las Vegas, 2018.

  11. Y. Wang, M. Li, R. Zheng, X. Shi, Yaohang Li, F. Wu, J. Wang, “Using Deep Neural Network to Predict Drug Sensitivity of Cancer Cell Lines,” Proceedings of International Conference on Intelligent Computing, (ICIC 2018), Wuhan, 2018.

  12. Yaohang Li, R. Mukkamala, M. Mascagni, "Validating the Correctness of Outsourced Computational Tasks using Pseudorandom Number Generators," Proceedings of the 15th IEEE International Conference on Dependable, Autonomic and Secure Computing, (DASC 2017), Orlando, 2017.

  13. W. Yu, Y. Gu, J. Li, S. Liu, Yaohang Li, "Single-Pass PCA of Large High-Dimensional Data," Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), Melbourne, 2017.

  14. W. Elhenfnawy, Yaohang Li, "Construction of Protein Backbone Fragments Libraries on Large Protein Sets using a Randomized Spectral Clustering Algorithm," Proceedings of International Symposium on Bioinformatics Research and Applications (ISBRA2017), Hononulu, 2017.

  15. P. Ni, M. Li, P. Zhong, G. Duan, J. Wang, Yaohang Li, F. Wu, "Relating Diseases Based on Disease Module Theory," Proceedings of International Symposium on Bioinformatics Research and Applications (ISBRA2017), Hononulu, 2017.

  16. W. Elhenfnawy, J. Wright, K. Kallepalli, K. Racheal, A. Gupta, Yaohang Li, R. Parimi, P. Shah,  "What Differentiates News Articles with Short and Long Shelf Lives? A Case Study on News Articles at Bloomberg.com," Proceedings of 6th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2016), Atlanta, 2016.

  17. H. Ji, S. H. Weinberg, M. Li, J. Wang, Yaohang Li, "An Apache Spark Implementation of Block Power Method for Computing Dominant Eigenvalues and Eigenvectors of Large-Scale Matrices," Proceedings of Applications of Big Data Science (ABDS16) Workshop, Atlanta, 2016.

  18. M. Abdelrasoul, Yaohang Li, "Coarse-grained Contact Potential Helps Improve Fold Recognition Sensitivity in Template-based Protein Structure Modeling," Proceedings of Big Data And Cloud Computing in Bioinformatics (BDACCB2016) Workshop, Atlanta, 2016.

  19. A. Dinh, D. Brill, Yaohang Li, W. He, “Malware Sequence Alignment,” proceedings of Big Data And Cloud Computing in Bioinformatics (BDACCB2016) Workshop, Atlanta, 2016.

  20. H. Ji, E. O'Saben, R. Lambi, Yaohang Li, “Matrix Completion Based Model V2.0: Predicting the Winning Probabilities of March Madness Matches,” Proceedings of Modeling, Simulation, and Visualization Student Capstone Conference, Suffolk, VA, 2016.

  21. M. Li, R. Zheng, Yaohang Li, F. Wu, J. Wang, “MGT-SM: a method for constructing cellular signal transduction networks,” Proceedings of 27th International Conference on Genome Informatics, Shanghai, 2016.

  22. H. Ji, Yaohang Li, S. H. Weinberg, "Calcium ion fluctuations alter channel gating in a stochastic luminal calcium release site model," Proceedings of International Symposium on Bioinformatics Research and Applications (ISBRA2015), Norfolk, 2015.

  23. W. He, X. Tian, J. Shen, Yaohang Li, "Understanding Mobile Banking Applications’ Security risks through Blog Mining and the Workflow Technology," Proceedings of the International Conference on Information Systems, Fort Worth, 2015.

  24. H. Ji, E. O'Saben, A. Boudion, Yaohang Li, "March Madness Prediction: A Matrix Completion Approach," Proceedings of Modeling, Simulation, and Visualization Student Capstone Conference, Sulfolk, 2015. (Best Paper Award)

  25. H. Ji, M. Sosonkina, Yaohang Li, "An Implementation of Block Conjugate Gradient Algorithm on CPU-GPU Processors," Proceedings of 1st International Workshop on Hardware-Software Co-Design for High Performance Computing (Co-HPC2014), New Orleans, 2014.

  26. Q. Li, S. Pascal, Yaohang Li, "Intrinsically Disorder Protein Prediction using Undersampling Feedforward Neural Networks and Predicted Amino Acid Features," Proceedings of Modeling, Simulation, and Visualization Capstone Conference, Sulfolk, 2014.

  27. H. Ji, Yaohang Li, "GPU Accelerated Randomized Singular Value Decomposition and Its Application in Image Compression," Proceedings of Modeling, Simulation, and Visualization Capstone Conference, Sulfolk, 2014. (Best Paper Award)

  28. A. Yaseen, Yaohang Li, "Predicting Protein Solvent Accessibility with Sequence, Evolutionary Information and Context-based Features," Proceedings of Biotechnology and Bioinformatics Symposium, (BIOT2013), Provo, 2013.

  29. A. Yaseen, Yaohang Li, "Template-based Prediction of Protein 8-state Secondary Structures," Proceedings of 3rd IEEE International Conference on Computational Advances in Bio and Medical Sciences, (ICCABS2013), New Orleans, 2013.

  30. I. Rata, K. Wessells, Yaohang Li, "An Improved Statistics-based Backbone Torsion Potential Energy for Protein Loop Structure Modeling," Proceedings of 3rd IEEE International Conference on Computational Advances in Bio and Medical Sciences, (ICCABS2013), New Orleans, 2013.

  31. Yaohang Li, A. Yaseen, "Pareto-based Optimal Sampling Method and Its Applications in Protein Structural Conformation Sampling," Proceedings of AAAI Workshop on Artificial Intelligence and Robotics Methods in Computational Biology, Bellevue, 2013.

  32. Yaohang Li, "A Coarse-grained, Context-dependent Contact Potential for Protein Decoy Discrimination," Proceedings of the 5th International Conference on Bioinformatics and Computational Biology, (BICoB-2013), Honolulu, 2013.

  33. A. Yaseen, Yaohang Li, "Enhancing Protein Disulfide Bonding Prediction Accuracy with Context-based Features," Proceedings of Biotechnology and Bioinformatics Symposium, (BIOT2012), Provo, 2012.

  34. H. Ji, Yaohang Li, "Reusing Random Walks in Monte Carlo Methods for Linear Systems," Proceedings of International Conference on Computational Science, (ICCS2012), Omaha, 2012.

  35. L. Tran, D. Banerjee, J. Wang, A. Kumar, F. McKenzie, Yaohang Li, J. Li, “A Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction,” Proceedings of 2nd International Workshop on Machine Learning in Medical Imaging, (MLMI2011), Toronto, 2011.

  36. Yaohang Li, W. Zhu, “GPU-Accelerated Multi-scoring Functions Protein Loop Structure Modeling,” Proceedings of 9th IEEE International Workshop on High Performance Computational Biology, (HiCOMB2010), Atlanta, 2010.

  37. W. Zhu, Yaohang Li, “GPU-Accelerated Differential Evolutionary Markov Chain Monte Carlo Method for Multi-Objective Optimization over Continuous Space,” Proceedings of 2nd Workshop on Bio-Inspired Algorithms for Distributed Systems, (BADS2010), Washington DC, 2010.

  38. Yaohang Li, I. Rata, E. Jakobsson, “Integrating Multiple Scoring Functions to Improve Protein Loop Structure Conformation Space Sampling,” Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, (CIBCB2010), Montreal, 2010.

  39. I. Waddell, N. Jones, C. Steed, X. Yuan, Yaohang Li, “Using the Workflow Technology in Secure Software Engineering Education,” Proceedings of 14th Colloquium for Information Systems Security Education, (CISSE2010), Baltimore, 2010.

  40. Yaohang Li, D. Wardell, “Study of Computing Consolidation Techniques in Computational Protein Loop Structure Modeling,” Proceedings of the 2nd International Conference on Bioinformatics and Computational Biology, (BICoB-2010), Honolulu, 2010.

  41. Yaohang Li, D. Wardell, V. Freeh, “A Resource-Efficient Computing Paradigm for Computational Protein Modeling Applications,” Proceedings of the 8th IEEE International Workshop on High Performance Computational Biology, (HiCOMB09), Rome, 2009.

  42. Yaohang Li, “A Population-based Approach for Diversified Protein Loop Structure Sampling,” Proceedings of the International Conference on Computational Science, (ICCS09), Baton Rouge, 2009.

  43. X. Zhang, S. Watts, Yaohang Li, D. Tortorelli, "Minkowski Functionals Study of Random Number Sequences," Proceedings of the International Conference on Computational Science, (ICCS09), Baton Rouge, 2009.

  44. Yaohang Li, A. J. Bordner, Y. Tian, X. Tao, A. Gorin, “Extensive Exploration of the Conformational Space Improves Rosetta Results for Short Protein Domains,” 7th Annual International Conference on Computational Systems Bioinformatics (CSB08), Stanford, 2008.

  45. A. Frazier, S. Hudson, Yaohang Li, X. Yuan, “Developing Software System Security Modules,” Proceedings of 12th Colloquium for Information Systems Security Education (CISSE08), Dallas, 2008.

  46. Yaohang Li, M. Mascagni, A. Gorin, “Decentralized Replica Exchange Parallel Tempering: An Efficient Implementation of Parallel Tempering using MPI and SPRNG,” Proceedings of International Conference on Computational Science and Its Applications (ICCSA07), Kuala Lumpur, 2007.

  47. Yaohang Li, T. Dong, X. Zhang, Y. Song, X. Yuan, “Large-Scale Software Unit Testing on the Grid,” Proceedings of IEEE International Conference on Granular Computing (GrC06), Atlanta, 2006.

  48. Yaohang Li, J. Clark, X. Zhang, “Parallel Implementation of the Accelerated Simulated Tempering Method,” Proceedings of 3rd International Conference on Neural, Parallel & Scientific Computations, (NPSC06), Atlanta, 2006.

  49. X. Zhang, Yaohang Li, A. Myklebust, “Hybrid Optimization of Geometrically Trimmed NURBS Surfaces,” Proceedings of ASME International Mechanical Engineering Congress and Exposition (IMECE05), Orlando, 2005.

  50. Yaohang Li, M. Mascagni, “A Bio-inspired Job Scheduling Algorithm for Monte Carlo Applications on a Computational Grid,” proceedings of 17th IMACS World Congress, Scientific Computation, Applied Mathematics, and Simulation, Paris, 2005.

  51. Yaohang Li, C. E. M. Strauss, A. Gorin, “Parallel Tempering in Rosetta Practice,” Proceedings of International Conference on Bioinformatics and its Applications, (ICBA’04), Fort Lauderdale, 2004.

  52. Yaohang Li, M. Mascagni, “e-Science Workflow on the Grid,” Proceedings of the IADIS International Conference, e-Society 2004, Avila, 2004.

  53. Yaohang Li, Y. Song, “Bio-inspired Fault Tolerant and Adaptive System Modeling and Simulation on the Grid,” Proceedings of the International Conference on Computing, Communications and Control Technologies, (CCCT04), Austin, 2004.

  54. Yaohang Li, M. Mascagni, “e-Science Workflow on the Grid,” Proceedings of the IADIS International Conference, (e-Society04), Avila, Spain, 2004.

  55. Yaohang Li, M. Mascagni, M. H. Peters, “Grid-based Nonequilibrium Multiple-Time Scale Molecula Dynamics/Brownian Dynamics Simulations of Ligand-Receptor Interactions in Structured Protein Systems,” Proceedings of the First BioGrid Workshop at the 3rd IEEE/ACM Symposium Cluster Computing and the Grid, (BioGrid03), Tokyo, 2003.

  56. M. Mascagni, Yaohang Li, “Computational Infrastructure for Parallel, Distributed, and Grid-based Monte Carlo Computations,” Proceedings of the Fourth International Conference on Large-Scale Scientific Computations (LSSC'03), Sozopol, Bulgaria, Lecture Notes in Computer Sciences, 2907: 39-52, 2003.

  57. Yaohang Li, M. Mascagni, “Improving Performance via Computational Replication on a Large-Scale Computational Grid,” proceedings of the GP2PC at the IEEE/ACM International Symposium on Cluster Computing and the Grid, IEEE/ACM (CCGRID03), Tokyo, 2003.

  58. Yaohang Li, M. Mascagni, “Grid-based Monte Carlo Applications,” Lecture Notes in Computer Science, 2536:13-24, Grid Computing Third International Workshop/Conference (GRID02), Baltimore, 2002.

Preprints in arXiv:

  1. Y. Alanazi, P. Ambrozewicz, M. P. Kuchera, Yaohang Li, T. Liu, R. E. McClellan, W. Melnitchouk, E. Pritchard, M. Robertson, N. Sato, R. Strauss, L. Velasco, “AI-based Monte Carlo event generator for electron-proton scattering,” arXiv:2008.03151, 2020.

  2.  Y. Alanazi, N. Sato, T. Liu, W. Melnitchouk, M. P. Kuchera, E. Pritchard, M. Robertson, R. Strauss, L. Velasco, Yaohang Li, “Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN),” arXiv:2001.11103, 2020.

  3. Yaohang Li, W. Yu, “A Fast Implementation of Singular Value Thresholding Algorithm using Recycling Rank Revealing Randomized Singular Value Decomposition,” arXiv:1704.05528, 2017.

  4. H. Ji, S. H. Weinberg, Yaohang Li, “A Revisit of Block Power Methods for Finite State Markov Chain Applications,” arXiv:1610.08881, 2016.

  5. H. Ji, W. Yu, Yaohang Li, “A Rank Revealing Randomized Singular Value Decomposition (R3SVD) Algorithm for Low-rank Matrix Approximations,” arXiv:1605.08134, 2016.