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- affiliation: Old Dominion University, Norfolk, USA
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Journal Articles
- 2024
[j79]Meng Wang, Chuqi Lei, Jianxin Wang
, Yaohang Li, Min Li:
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. Briefings Bioinform. 25(3) (2024)- [j78]Chao Deng, Hong-Dong Li, Li-Shen Zhang, Yiwei Liu, Yaohang Li, Jianxin Wang:
Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks. Bioinform. 40(Supplement_1): i511-i520 (2024) - 2023
- [j77]Lishen Zhang, Chengqian Lu, Min Zeng, Yaohang Li, Jianxin Wang:
CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features. Briefings Bioinform. 24(1) (2023) - [j76]Bin Wang, Kun Liu, Yaohang Li, Jianxin Wang:
DFHiC: a dilated full convolution model to enhance the resolution of Hi-C data. Bioinform. 39(5) (2023) - [j75]Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang:
MSDRP: a deep learning model based on multisource data for predicting drug response. Bioinform. 39(9) (2023) - [j74]Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang:
CellBRF: a feature selection method for single-cell clustering using cell balance and random forest. Bioinform. 39(Supplement-1): 368-376 (2023) - [j73]Kunying Niu, Yifan Wu, Yaohang Li, Min Li:
Retrieve and rerank for automated ICD coding via Contrastive Learning. J. Biomed. Informatics 143: 104396 (2023) - [j72]Kun Liu, Hong-Dong Li, Yaohang Li, Jun Wang, Jianxin Wang:
A Comparison of Topologically Associating Domain Callers Based on Hi-C Data. IEEE ACM Trans. Comput. Biol. Bioinform. 20(1): 15-29 (2023) - [j71]Min Li, Wenbo Shi, Fuhao Zhang, Min Zeng, Yaohang Li:
A Deep Learning Framework for Predicting Protein Functions With Co-Occurrence of GO Terms. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 833-842 (2023) - [j70]Qichang Zhao, Guihua Duan, Mengyun Yang, Zhongjian Cheng, Yaohang Li, Jianxin Wang:
AttentionDTA: Drug-Target Binding Affinity Prediction by Sequence-Based Deep Learning With Attention Mechanism. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 852-863 (2023) - [j69]Qichang Zhao, Guihua Duan, Haochen Zhao, Kai Zheng, Yaohang Li, Jianxin Wang:
GIFDTI: Prediction of Drug-Target Interactions Based on Global Molecular and Intermolecular Interaction Representation Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 1943-1952 (2023) - [j68]Haochen Zhao, Guihua Duan, Peng Ni, Cheng Yan, Yaohang Li, Jianxin Wang:
RNPredATC: A Deep Residual Learning-Based Model With Applications to the Prediction of Drug-ATC Code Association. IEEE ACM Trans. Comput. Biol. Bioinform. 20(5): 2712-2723 (2023) - 2022
- [j67]Min Li, Zhangli Lu, Yifan Wu, Yaohang Li:
BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction. Bioinform. 38(7): 1995-2002 (2022) - [j66]Zhongjian Cheng, Qichang Zhao, Yaohang Li, Jianxin Wang:
IIFDTI: predicting drug-target interactions through interactive and independent features based on attention mechanism. Bioinform. 38(17): 4153-4161 (2022) - [j65]Qichang Zhao, Mengyun Yang, Zhongjian Cheng, Yaohang Li, Jianxin Wang:
Biomedical Data and Deep Learning Computational Models for Predicting Compound-Protein Relations. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2092-2110 (2022) - [j64]Yiming Li, Min Zeng, Yifan Wu, Yaohang Li, Min Li:
Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3263-3271 (2022) - [j63]Yifan Wu, Min Zeng, Ying Yu, Yaohang Li, Min Li:
A Pseudo Label-Wise Attention Network for Automatic ICD Coding. IEEE J. Biomed. Health Informatics 26(10): 5201-5212 (2022) - [j62]Mengyun Yang, Yaohang Li, Jianxin Wang:
Feature and Nuclear Norm Minimization for Matrix Completion. IEEE Trans. Knowl. Data Eng. 34(5): 2190-2199 (2022) - 2021
- [j61]Huimin Luo, Min Li, Mengyun Yang, Fang-Xiang Wu, Yaohang Li, Jianxin Wang:
Biomedical data and computational models for drug repositioning: a comprehensive review. Briefings Bioinform. 22(2): 1604-1619 (2021) - [j60]Mengyun Yang, Gaoyan Wu, Qichang Zhao, Yaohang Li, Jianxin Wang:
Computational drug repositioning based on multi-similarities bilinear matrix factorization. Briefings Bioinform. 22(4) (2021) - [j59]Kaili Wang, Renyi Zhou, Yaohang Li, Min Li:
DeepDTAF: a deep learning method to predict protein-ligand binding affinity. Briefings Bioinform. 22(5) (2021) - [j58]You Zou, Yuejie Zhu, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Parallel computing for genome sequence processing. Briefings Bioinform. 22(5) (2021) - [j57]Haochen Zhao, Kai Zheng, Yaohang Li, Jianxin Wang:
A novel graph attention model for predicting frequencies of drug-side effects from multi-view data. Briefings Bioinform. 22(6) (2021) - [j56]Haochen Zhao, Yaohang Li, Jianxin Wang:
A convolutional neural network and graph convolutional network-based method for predicting the classification of anatomical therapeutic chemicals. Bioinform. 37(18): 2841-2847 (2021) - [j55]Xiangmao Meng, Wenkai Li, Xiaoqing Peng, Yaohang Li, Min Li:
Protein interaction networks: centrality, modularity, dynamics, and applications. Frontiers Comput. Sci. 15(1) (2021) - [j54]Gaoyan Wu, Mengyun Yang, Yaohang Li, Jianxin Wang:
De Novo Prediction of Drug-Target Interactions Using Laplacian Regularized Schatten p-Norm Minimization. J. Comput. Biol. 28(7): 660-673 (2021) - [j53]Min Zeng, Min Li, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang:
A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information. IEEE ACM Trans. Comput. Biol. Bioinform. 18(1): 296-305 (2021) - [j52]Min Li, Yake Wang, Ruiqing Zheng, Xinghua Shi, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines. IEEE ACM Trans. Comput. Biol. Bioinform. 18(2): 575-582 (2021) - [j51]Fuhao Zhang, Hong Song, Min Zeng, Fang-Xiang Wu, Yaohang Li, Yi Pan, Min Li:
A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2208-2217 (2021) - [j50]Min Zeng, Chengqian Lu, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Jianxin Wang, Min Li:
DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2353-2363 (2021) - 2020
- [j49]Min Zeng, Fuhao Zhang, Fang-Xiang Wu, Yaohang Li, Jianxin Wang, Min Li:
Protein-protein interaction site prediction through combining local and global features with deep neural networks. Bioinform. 36(4): 1114-1120 (2020) - [j48]Wenjing Xuan, Ning Liu, Neng Huang, Yaohang Li, Jianxin Wang:
CLPred: a sequence-based protein crystallization predictor using BLSTM neural network. Bioinform. 36(Supplement-2): i709-i717 (2020) - [j47]Wessam Elhefnawy, Min Li, Jianxin Wang, Yaohang Li:
DeepFrag-k: a fragment-based deep learning approach for protein fold recognition. BMC Bioinform. 21-S(6): 203 (2020) - [j46]Hao Ji, Michael Mascagni, Yaohang Li:
Gaussian variant of Freivalds' algorithm for efficient and reliable matrix product verification. Monte Carlo Methods Appl. 26(4): 273-284 (2020) - [j45]Min Li, Xiangmao Meng, Ruiqing Zheng, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang:
Identification of Protein Complexes by Using a Spatial and Temporal Active Protein Interaction Network. IEEE ACM Trans. Comput. Biol. Bioinform. 17(3): 817-827 (2020) - [j44]Peng Ni, Jianxin Wang, Ping Zhong, Yaohang Li, Fang-Xiang Wu, Yi Pan:
Constructing Disease Similarity Networks Based on Disease Module Theory. IEEE ACM Trans. Comput. Biol. Bioinform. 17(3): 906-915 (2020) - [j43]Gaoshi Li, Min Li, Jianxin Wang, Yaohang Li, Yi Pan:
United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins. IEEE ACM Trans. Comput. Biol. Bioinform. 17(4): 1451-1458 (2020) - [j42]Chengqian Lu, Mengyun Yang, Min Li, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion. IEEE J. Biomed. Health Informatics 24(8): 2420-2429 (2020) - [j41]Hui Jiang, Mengyun Yang, Xiang Chen, Min Li, Yaohang Li, Jianxin Wang:
miRTMC: A miRNA Target Prediction Method Based on Matrix Completion Algorithm. IEEE J. Biomed. Health Informatics 24(12): 3630-3641 (2020) - 2019
- [j40]Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang:
Clinical big data and deep learning: Applications, challenges, and future outlooks. Big Data Min. Anal. 2(4): 288-305 (2019) - [j39]Mengyun Yang, Huimin Luo, Yaohang Li, Jianxin Wang:
Drug repositioning based on bounded nuclear norm regularization. Bioinform. 35(14): i455-i463 (2019) - [j38]Min Zeng, Min Li, Fang-Xiang Wu, Yaohang Li, Yi Pan:
DeepEP: a deep learning framework for identifying essential proteins. BMC Bioinform. 20-S(16): 506:1-506:10 (2019) - [j37]Wessam Elhefnawy, Min Li, Jianxin Wang, Yaohang Li:
Decoding the Structural Keywords in Protein Structure Universe. J. Comput. Sci. Technol. 34(1): 3-15 (2019) - [j36]Mengyun Yang, Huimin Luo, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Overlap matrix completion for predicting drug-associated indications. PLoS Comput. Biol. 15(12) (2019) - [j35]Min Li, Ruiqing Zheng, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
MGT-SM: A Method for Constructing Cellular Signal Transduction Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 417-424 (2019) - [j34]Min Li, Zhihui Fei, Min Zeng, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang:
Automated ICD-9 Coding via A Deep Learning Approach. IEEE ACM Trans. Comput. Biol. Bioinform. 16(4): 1193-1202 (2019) - 2018
- [j33]Andy Ramlatchan, Mengyun Yang, Quan Liu, Min Li, Jianxin Wang, Yaohang Li:
A survey of matrix completion methods for recommendation systems. Big Data Min. Anal. 1(4): 308-323 (2018) - [j32]Huimin Luo, Min Li, Shaokai Wang, Quan Liu, Yaohang Li, Jianxin Wang:
Computational drug repositioning using low-rank matrix approximation and randomized algorithms. Bioinform. 34(11): 1904-1912 (2018) - [j31]Chengqian Lu, Mengyun Yang, Feng Luo, Fang-Xiang Wu, Min Li, Yi Pan, Yaohang Li, Jianxin Wang:
Prediction of lncRNA-disease associations based on inductive matrix completion. Bioinform. 34(19): 3357-3364 (2018) - [j30]Wenjian Yu, Yu Gu, Yaohang Li:
Efficient Randomized Algorithms for the Fixed-Precision Low-Rank Matrix Approximation. SIAM J. Matrix Anal. Appl. 39(3): 1339-1359 (2018) - 2017
- [j29]Hao Ji, Yaohang Li:
Block Conjugate Gradient algorithms for least squares problems. J. Comput. Appl. Math. 317: 203-217 (2017) - [j28]Yihao Liang, Xiangjun Xing, Yaohang Li:
A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions. J. Comput. Phys. 338: 252-268 (2017) - [j27]Hao Ji, Yaohang Li, Seth H. Weinberg:
Calcium Ion Fluctuations Alter Channel Gating in a Stochastic Luminal Calcium Release Site Model. IEEE ACM Trans. Comput. Biol. Bioinform. 14(3): 611-619 (2017) - [j26]Jui-Long Hung, Morgan C. Wang, Shuyan Wang, Maha M. Abdelrasoul, Yaohang Li, Wu He:
Identifying At-Risk Students for Early Interventions - A Time-Series Clustering Approach. IEEE Trans. Emerg. Top. Comput. 5(1): 45-55 (2017) - 2016
- [j25]Ashraf Yaseen, Mais Nijim, Brandon Williams, Lei Qian, Min Li, Jianxin Wang, Yaohang Li:
FLEXc: protein flexibility prediction using context-based statistics, predicted structural features, and sequence information. BMC Bioinform. 17(S-8): 281 (2016) - [j24]Yu Liang, Dalei Wu, Guirong Liu, Yaohang Li, Cuilan Gao, Zhongguo John Ma, Weidong Wu:
Big data-enabled multiscale serviceability analysis for aging bridges☆. Digit. Commun. Networks 2(3): 97-107 (2016) - [j23]Wei Lan, Jianxin Wang, Min Li, Jin Liu, Yaohang Li, Fang-Xiang Wu, Yi Pan:
Predicting drug-target interaction using positive-unlabeled learning. Neurocomputing 206: 50-57 (2016) - [j22]Ashraf Yaseen, Hao Ji, Yaohang Li:
A load-balancing workload distribution scheme for three-body interaction computation on Graphics Processing Units (GPU). J. Parallel Distributed Comput. 87: 91-101 (2016) - [j21]José Ramón López-Blanco, Alejandro Jesús Canosa-Valls, Yaohang Li, Pablo Chacón:
RCD+: Fast loop modeling server. Nucleic Acids Res. 44(Webserver-Issue): W395-W400 (2016) - 2015
- [j20]Wu He, Jiancheng Shen, Xin Tian, Yaohang Li, Vasudeva Akula, Gongjun Yan, Ran Tao:
Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world. Ind. Manag. Data Syst. 115(9): 1622-1636 (2015) - 2014
- [j19]Ashraf Yaseen, Yaohang Li:
Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features. BMC Bioinform. 15(S-8): S3 (2014) - [j18]Ashraf Yaseen, Yaohang Li:
Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy. J. Chem. Inf. Model. 54(3): 992-1002 (2014) - [j17]Wu He, Ashish Kshirsagar, Alexander C. Nwala, Yaohang Li:
Teaching Information Security with Workflow Technology: A Case Study Approach. J. Inf. Syst. Educ. 25(3): 201-210 (2014) - 2013
- [j16]Ashraf Yaseen, Yaohang Li:
Dinosolve: a protein disulfide bonding prediction server using context-based features to enhance prediction accuracy. BMC Bioinform. 14(S-13): S9 (2013) - [j15]Yaohang Li, Hui Liu, Ionel Rata, Eric Jakobsson:
Building a Knowledge-Based Statistical Potential by Capturing High-Order Inter-residue Interactions and its Applications in Protein Secondary Structure Assessment. J. Chem. Inf. Model. 53(2): 500-508 (2013) - [j14]Loc Tran, Debrup Banerjee, Jihong Wang, Ashok J. Kumar, Frederic D. McKenzie, Yaohang Li, Jiang Li:
High-dimensional MRI data analysis using a large-scale manifold learning approach. Mach. Vis. Appl. 24(5): 995-1014 (2013) - [j13]Hao Ji, Michael Mascagni, Yaohang Li:
Convergence Analysis of Markov Chain Monte Carlo Linear Solvers Using Ulam-von Neumann Algorithm. SIAM J. Numer. Anal. 51(4): 2107-2122 (2013) - 2012
- [j12]Yaohang Li:
MOMCMC: An efficient Monte Carlo method for multi-objective sampling over real parameter space. Comput. Math. Appl. 64(11): 3542-3556 (2012) - [j11]Ashraf Yaseen, Yaohang Li:
Accelerating knowledge-based energy evaluation in protein structure modeling with Graphics Processing Units. J. Parallel Distributed Comput. 72(2): 297-307 (2012) - 2011
- [j10]Yaohang Li, Ionel Rata, Eric Jakobsson:
Sampling Multiple Scoring Functions Can Improve Protein Loop Structure Prediction Accuracy. J. Chem. Inf. Model. 51(7): 1656-1666 (2011) - [j9]Weihang Zhu, Ashraf Yaseen, Yaohang Li:
DEMCMC-GPU: An Efficient Multi-Objective Optimization Method with GPU Acceleration on the Fermi Architecture. New Gener. Comput. 29(2): 163-184 (2011) - 2009
- [j8]Yaohang Li, Vladimir A. Protopopescu, Nikita Arnold, Xinyu Zhang, Andrey Gorin:
Hybrid parallel tempering and simulated annealing method. Appl. Math. Comput. 212(1): 216-228 (2009) - [j7]Yaohang Li, Michael Mascagni, Andrey Gorin:
A decentralized parallel implementation for parallel tempering algorithm. Parallel Comput. 35(5): 269-283 (2009) - 2008
- [j6]Yaohang Li, Yong-Duan Song:
An adaptive and trustworthy software testing framework on the grid. J. Supercomput. 46(2): 124-138 (2008) - 2007
- [j5]Yaohang Li, Daniel Chen, Xiaohong Yuan:
Trustworthy remote compiling services for grid-based scientific applications. J. Supercomput. 41(2): 119-131 (2007) - 2005
- [j4]Yaohang Li, Michael Mascagni:
Grid-based Quasi-Monte Carlo Applications. Monte Carlo Methods Appl. 11(1): 39-55 (2005) - 2004
- [j3]Yaohang Li, Michael Mascagni, Robert A. van Engelen, Qin Cai:
A Grid Workflow-based Monte Carlo Simultation Environment. Neural Parallel Sci. Comput. 12(3): 439-454 (2004) - 2003
- [j2]Yaohang Li, Michael Mascagni:
Analysis of Large-Scale Grid-Based Monte Carlo Applications. Int. J. High Perform. Comput. Appl. 17(4): 369-382 (2003) - 2001
- [j1]Michael Mascagni, Aneta Karaivanova, Yaohang Li:
A Quasi-Monte Carlo Method for Elliptic Boundary Value Problems. Monte Carlo Methods Appl. 7(3-4): 283-294 (2001)
Conference and Workshop Papers
- 2024
- [c56]Rizhao Cai, Zirui Song, Dayan Guan, Zhenhao Chen, Yaohang Li, Xing Luo, Chenyu Yi, Alex C. Kot:
BenchLMM: Benchmarking Cross-Style Visual Capability of Large Multimodal Models. ECCV (50) 2024: 340-358 - [c55]Tareq Alghamdi, Tommaso Vittorini, Marco Spreafico, Marco Battaglieri, Nobuo Sato, Yaohang Li:
Unfolding Particle Detector Acceptance in High Energy Physics with Generative AI. ICTAI 2024: 962-968 - 2022
- [c54]Manal Almaeen, Yasir Alanazi, Nobuo Sato, W. Melnitchouk, Yaohang Li:
Point Cloud-based Variational Autoencoder Inverse Mappers (PC-VAIM) - An Application on Quantum Chromodynamics Global Analysis. ICMLA 2022: 1151-1158 - [c53]Andy Ramlatchan, Yaohang Li:
Image Synthesis Using Conditional GANs for Selective Laser Melting Additive Manufacturing. IJCNN 2022: 1-8 - 2021
- [c52]Ivan Makohon, Yaohang Li:
Multi-Label Classification of ICD-10 Coding & Clinical Notes Using MIMIC & CodiEsp. BHI 2021: 1-4 - [c51]Yasir Alanazi, Nobuo Sato, Tianbo Liu, Wally Melnitchouk, Pawel Ambrozewicz, Florian Hauenstein, Michelle P. Kuchera, Evan Pritchard, Michael Robertson, Ryan R. Strauss, Luisa Velasco, Yaohang Li:
Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). IJCAI 2021: 2126-2132 - [c50]Yasir Alanazi, Nobuo Sato, Pawel Ambrozewicz, Astrid N. Hiller Blin, Wally Melnitchouk, Marco Battaglieri, Tianbo Liu, Yaohang Li:
A Survey of Machine Learning-Based Physics Event Generation. IJCAI 2021: 4286-4293 - [c49]Manal Almaeen, Yasir Alanazi, Nobuo Sato, W. Melnitchouk, Michelle P. Kuchera, Yaohang Li:
Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems. IJCNN 2021: 1-8 - 2020
- [c48]Haochen Zhao, Peng Ni, Cheng Yan, Yaohang Li, Jianxin Wang:
A novel approach based on deep residual learning to predict drug's anatomical therapeutic chemical code. BIBM 2020: 921-926 - [c47]Luisa Velasco, Evan McClellan, Nobuo Sato, Pawel Ambrozewicz, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Yasir Alanazi, Yaohang Li:
cFAT-GAN: Conditional Simulation of Electron-Proton Scattering Events with Variate Beam Energies by a Feature Augmented and Transformed Generative Adversarial Network. ICMLA 2020: 372-375 - [c46]Gaoyan Wu, Mengyun Yang, Yaohang Li, Jianxin Wang:
De novo Prediction of Drug-Target Interaction via Laplacian Regularized Schatten-p Norm Minimization. ISBRA 2020: 154-165 - 2019
- [c45]Qichang Zhao, Fen Xiao, Mengyun Yang, Yaohang Li, Jianxin Wang:
AttentionDTA: prediction of drug-target binding affinity using attention model. BIBM 2019: 64-69 - [c44]Min Zeng, Chengqian Lu, Fuhao Zhang, Zhangli Lu, Fang-Xiang Wu, Yaohang Li, Min Li:
LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques. BIBM 2019: 577-582 - 2018
- [c43]Min Zeng, Min Li, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Yi Pan:
A Deep Learning Framework for Identifying Essential Proteins Based on Protein-Protein Interaction Network and Gene Expression Data. BIBM 2018: 583-588 - [c42]Donglin Guo, Min Li, Ying Yu, Yaohang Li, Guihua Duan, Fang-Xiang Wu, Jianxin Wang:
Disease Inference with Symptom Extraction and Bidirectional Recurrent Neural Network. BIBM 2018: 864-868 - [c41]Yake Wang, Min Li, Ruiqing Zheng, Xinghua Shi, Yaohang Li, Fang-Xiang Wu, Jianxin Wang:
Using Deep Neural Network to Predict Drug Sensitivity of Cancer Cell Lines. ICIC (2) 2018: 223-226 - [c40]Xu Feng, Wenjian Yu, Yaohang Li:
Faster Matrix Completion Using Randomized SVD. ICTAI 2018: 608-615 - [c39]Siyu Zhao, Ruiqing Zheng, Xiang Chen, Yaohang Li, Fang-Xiang Wu, Min Li:
PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks. ISBRA 2018: 38-48 - 2017
- [c38]Yaohang Li, Ravi Mukkamala, Michael Mascagni:
Validating the Correctness of Outsourced Computational Tasks Using Pseudorandom Number Generators. DASC/PiCom/DataCom/CyberSciTech 2017: 391-398 - [c37]Wenjian Yu, Yu Gu, Jian Li, Shenghua Liu, Yaohang Li:
Single-Pass PCA of Large High-Dimensional Data. IJCAI 2017: 3350-3356 - [c36]Peng Ni, Min Li, Ping Zhong, Guihua Duan, Jianxin Wang, Yaohang Li, Fang-Xiang Wu:
Relating Diseases Based on Disease Module Theory. ISBRA 2017: 24-33 - [c35]Wessam Elhefnawy, Min Li, Jianxin Wang, Yaohang Li:
Construction of Protein Backbone Fragments Libraries on Large Protein Sets Using a Randomized Spectral Clustering Algorithm. ISBRA 2017: 108-119 - 2016
- [c34]Wessam Elhefnawy, Jesse Wright, Kumara Kallepalli, Kevin Racheal, Ajay Gupta, Rohit Parimi, Parth Shah, Yaohang Li:
What Differentiates News Articles with Short and Long Shelf Lives? A Case Study on News Articles at Bloomberg.com. BDCloud-SocialCom-SustainCom 2016: 131-136 - [c33]Hao Ji, Seth H. Weinberg, Min Li, Jianxin Wang, Yaohang Li:
An Apache Spark Implementation of Block Power Method for Computing Dominant Eigenvalues and Eigenvectors of Large-Scale Matrices. BDCloud-SocialCom-SustainCom 2016: 554-559 - [c32]Maha M. Abdelrasoul, Yaohang Li:
Coarse-Grained Contact Potential Helps Improve Fold Recognition Sensitivity in Template-Based Protein Structure Modeling. BDCloud-SocialCom-SustainCom 2016: 607-612 - [c31]Andrew Dinh, Daniel Brill, Yaohang Li, Wu He:
Malware Sequence Alignment. BDCloud-SocialCom-SustainCom 2016: 613-617 - 2015
- [c30]Wu He, Xin Tian, Jiancheng Shen, Yaohang Li:
Understanding Mobile Banking Applications' Security risks through Blog Mining and the Workflow Technology. ICIS 2015 - [c29]Hao Ji, Yaohang Li, Seth H. Weinberg:
Calcium Ion Fluctuations Alter Channel Gating in a Stochastic Luminal Calcium Release Site Model. ISBRA 2015: 162-174 - [c28]Wu He, Ashish Kshirsagar, Alexander C. Nwala, Yaohang Li:
Using Workflow Technology to Create Scenario-based Workflows for Information Security Education: Scenario-based Workflows (Abstract Only). SIGCSE 2015: 688 - 2014
- [c27]Hao Ji, Masha Sosonkina, Yaohang Li:
An implementation of block conjugate gradient algorithm on CPU-GPU processors. Co-HPC@SC 2014: 72-77 - 2013
- [c26]Ionel Rata, Kyle Wessells, Yaohang Li:
An improved statistics-based backbone torsion potential energy for protein loop structure modeling. ICCABS 2013: 1-6 - [c25]Ashraf Yaseen, Yaohang Li:
Template-based prediction of protein 8-state secondary structures. ICCABS 2013: 1-2 - 2012
- [c24]Hao Ji, Yaohang Li:
Reusing Random Walks in Monte Carlo Methods for Linear Systems. ICCS 2012: 383-392 - 2011
- [c23]Loc Tran, Debrup Banerjee, Xiaoyan Sun, Jihong Wang, Ashok J. Kumar, David Vinning, Frederic D. McKenzie, Yaohang Li, Jiang Li:
A Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction. MLMI 2011: 265-272 - 2010
- [c22]Yaohang Li, Douglas Wardell:
Study of Computing Consolidation Techniques in Computational Protein Loop Structure Modeling. BICoB 2010: 67-72 - [c21]Yaohang Li, Ionel Rata, Eric Jakobsson:
Integrating multiple scoring functions to improve protein loop structure conformation space sampling. CIBCB 2010: 1-8 - [c20]Weihang Zhu, Yaohang Li:
GPU-accelerated differential evolutionary Markov Chain Monte Carlo method for multi-objective optimization over continuous space. BADS@ICAC 2010: 1-8 - [c19]Yaohang Li, Weihang Zhu:
GPU-accelerated multi-scoring functions protein loop structure sampling. IPDPS Workshops 2010: 1-8 - 2009
- [c18]Yaohang Li:
A Population-Based Approach for Diversified Protein Loop Structure Sampling. ICCS (1) 2009: 94-103 - [c17]Xinyu Zhang, Seth E. Watts, Yaohang Li, Daniel A. Tortorelli:
Minkowski Functionals Study of Random Number Sequences. ICCS (1) 2009: 550-559 - [c16]Yaohang Li, Douglas Wardell, Vincent W. Freeh:
Resource-efficient computing paradigm for computational protein modeling applications. IPDPS 2009: 1-8 - 2008
- [c15]Yaohang Li, Albert C. Esterline, Cheickna Baber, Kawana Fuller, Michael Burns, Tracy Hansen, Thomas LeFebvre, MarySue Schultz, Mark Govett, Paul Hamer, Ashvin Mysore:
A Sensor Information Framework for Integrating and Orchestrating Distributed Sensor Services. PDPTA 2008: 857-862 - 2007
- [c14]Xiaohong Yuan, Percy Vega, Jinsheng Xu, Huiming Yu, Yaohang Li:
Using packet sniffer simulator in the class: experience and evaluation. ACM Southeast Regional Conference 2007: 116-121 - [c13]Yaohang Li, Michael Mascagni, Andrey Gorin:
Decentralized Replica Exchange Parallel Tempering: An Efficient Implementation of Parallel Tempering Using MPI and SPRNG. ICCSA (3) 2007: 507-519 - [c12]Yaohang Li, Jason Clark, Kenneth W. Williams, Christopher Doss, Yong-Duan Song:
Efficient Parallel Implementation of Evolutionary Markov Chain Monte Carlo. PDPTA 2007: 299-306 - 2006
- [c11]Yaohang Li, Tao Dong, Xinyu Zhang, Yong-Duan Song, Xiaohong Yuan:
Large-scale software unit testing on the grid. GrC 2006: 596-599 - [c10]Yong-Duan Song, Tao Dong, Yaohang Li:
Using Grid Computing for Distributed Software Testing. PDPTA 2006: 931-936 - 2005
- [c9]Yaohang Li, Tao Dong, Marwan Bikdash, Yong-Duan Song:
Path Planning for Unmanned Vehicles Using Ant Colony Optimization on a Dynamic Voronoi Diagram. IC-AI 2005: 716-721 - [c8]Yaohang Li, Daniel Tsu-Tang Chen, Xiaohong Yuan, Huiming Yu, Albert C. Esterline:
Secure Remote Compiling Services on the Grid. PDPTA 2005: 373-378 - [c7]Xiaohong Yuan, Percy Vega, Huiming Yu, Yaohang Li:
A Personal Software Process Tool for Eclipse Environment. Software Engineering Research and Practice 2005: 717-723 - 2004
- [c6]Yaohang Li, Yongduan Song:
Bio-inspired Fault Tolerant and Adaptive System Modeling and Simulation on the Grid. CCCT (1) 2004: 192-198 - 2003
- [c5]Yaohang Li, Michael Mascagni:
Improving Performance via Computational Replication on a Large-Scale Computational Grid. CCGRID 2003: 442-448 - [c4]Yaohang Li, Michael Mascagni, Michael H. Peter:
Grid-based Nonequilibrium Multiple-Time Scale Molecular Dynamics/Brownian Dynamics Simulations of Ligand-Receptor Interactions in Structured Protein Systems. CCGRID 2003: 568-573 - [c3]Michael Mascagni, Yaohang Li:
Computational Infrastructure for Parallel, Distributed, and Grid-Based Monte Carlo Computations. LSSC 2003: 39-52 - [c2]Yaohang Li, Michael Mascagni, Robert van Engelen:
GCIMCA: A Globus and SPRNG Implementation of a Grid-Computing Infrastructure for Monte Carlo Applications. PDPTA 2003: 71-76 - 2002
- [c1]Yaohang Li, Michael Mascagni:
Grid-Based Monte Carlo Application. GRID 2002: 13-24
Parts in Books or Collections
- 2008
- [p2]Xiaohong Yuan, Barbara T. Pioro, Ricky Archer, Yaohang Li:
Teaching Operating Systems Using Visualization: A Comparative Study. Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education 2008: 576-580 - 2005
- [p1]Yaohang Li, Charlie E. M. Strauss, Andrey Gorin:
Parallel tempering in Rosetta Practice. Advances in Bioinformatics and Its Applications 2005
Editorship
- 2021
- [e2]Yufei Huang, Lukasz A. Kurgan, Feng Luo, Xiaohua Hu, Yidong Chen, Edward R. Dougherty, Andrzej Kloczkowski, Yaohang Li:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021, Houston, TX, USA, December 9-12, 2021. IEEE 2021, ISBN 978-1-6654-0126-5 [contents] - 2015
- [e1]Robert W. Harrison, Yaohang Li, Ion I. Mandoiu:
Bioinformatics Research and Applications - 11th International Symposium, ISBRA 2015, Norfolk, VA, USA, June 7-10, 2015 Proceedings. Lecture Notes in Computer Science 9096, Springer 2015, ISBN 978-3-319-19047-1 [contents]
Informal and Other Publications
- 2024
- [i12]Zirui Song, Yaohang Li, Meng Fang, Zhenhao Chen, Zecheng Shi, Yuan Huang, Ling Chen:
MMAC-Copilot: Multi-modal Agent Collaboration Operating System Copilot. CoRR abs/2404.18074 (2024) - [i11]Kai Zheng, Qilong Feng, Yaohang Li, Qichang Zhao, Jinhui Xu, Jianxin Wang:
TopoLa: a novel embedding framework for understanding complex networks. CoRR abs/2405.16928 (2024) - 2022
- [i10]Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li:
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. CoRR abs/2208.04314 (2022) - 2021
- [i9]Yasir Alanazi, Nobuo Sato, Pawel Ambrozewicz, Astrid N. Hiller Blin, W. Melnitchouk, Marco Battaglieri, Tianbo Liu, Yaohang Li:
A survey of machine learning-based physics event generation. CoRR abs/2106.00643 (2021) - 2020
- [i8]Yasir Alanazi, Nobuo Sato, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Evan Pritchard, Michael Robertson, Ryan R. Strauss, Luisa Velasco, Yaohang Li:
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). CoRR abs/2001.11103 (2020) - 2018
- [i7]Xu Feng, Wenjian Yu, Yaohang Li:
Faster Matrix Completion Using Randomized SVD. CoRR abs/1810.06860 (2018) - 2017
- [i6]Yaohang Li, Wenjian Yu:
A Fast Implementation of Singular Value Thresholding Algorithm using Recycling Rank Revealing Randomized Singular Value Decomposition. CoRR abs/1704.05528 (2017) - [i5]Wenjian Yu, Yu Gu, Jian Li, Shenghua Liu, Yaohang Li:
Single-Pass PCA of Large High-Dimensional Data. CoRR abs/1704.07669 (2017) - [i4]Hao Ji, Michael Mascagni, Yaohang Li:
Gaussian Variant of Freivalds' Algorithm for Efficient and Reliable Matrix Product Verification. CoRR abs/1705.10449 (2017) - 2016
- [i3]Hao Ji, Wenjian Yu, Yaohang Li:
A Rank Revealing Randomized Singular Value Decomposition (R3SVD) Algorithm for Low-rank Matrix Approximations. CoRR abs/1605.08134 (2016) - [i2]Yu Gu, Wenjian Yu, Yaohang Li:
Efficient randomized algorithms for adaptive low-rank factorizations of large matrices. CoRR abs/1606.09402 (2016) - [i1]Hao Ji, Seth H. Weinberg, Yaohang Li:
A Revisit of Block Power Methods for Finite State Markov Chain Applications. CoRR abs/1610.08881 (2016)
Coauthor Index
[j79] [j78] [j77] [j76] [j75] [j74] [j72] [j70] [j69] [j68] [j66] [j65] [j62] [j61] [j60] [j58] [j57] [j56] [j54] [j53] [j52] [j50] [j49] [j48] [j47] [j45] [j44] [j43] [j42] [j41] [j40] [j39] [j37] [j36] [j35] [j34] [j33] [j32] [j31] [j25] [j23] [c48] [c46] [c45] [c42] [c41] [c36] [c35] [c33] [i11] [i10]
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