A Quasi-Monte Carlo Method for Elliptic Boundary Value Problems. - Michael Mascagni; Aneta Karaivanova; Yaohang Li (Monte Carlo Methods Appl., 2001)

Grid-Based Monte Carlo Application. - Yaohang Li; Michael Mascagni (GRID, 2002)

Improving Performance via Computational Replication on a Large-Scale Computational Grid. - Yaohang Li; Michael Mascagni (CCGRID, 2003)

Grid-based Nonequilibrium Multiple-Time Scale Molecular Dynamics/Brownian Dynamics Simulations of Ligand-Receptor Interactions in Structured Protein Systems. - Yaohang Li; Michael Mascagni; Michael H. Peter (CCGRID, 2003)

Computational Infrastructure for Parallel, Distributed, and Grid-Based Monte Carlo Computations. - Michael Mascagni; Yaohang Li (LSSC, 2003)

GCIMCA: A Globus and SPRNG Implementation of a Grid-Computing Infrastructure for Monte Carlo Applications. - Yaohang Li; Michael Mascagni; Robert van Engelen (PDPTA, 2003)

Analysis of Large-Scale Grid-Based Monte Carlo Applications. - Yaohang Li; Michael Mascagni (Int. J. High Perform. Comput. Appl., 2003)

Bio-inspired Fault Tolerant and Adaptive System Modeling and Simulation on the Grid. - Yaohang Li; Yongduan Song (CCCT (1), 2004)

A Grid Workflow-based Monte Carlo Simultation Environment. - Yaohang Li; Michael Mascagni; Robert A. van Engelen; Qin Cai (Neural Parallel Sci. Comput., 2004)

Parallel tempering in Rosetta Practice. - Yaohang Li; Charlie E. M. Strauss; Andrey Gorin (Advances in Bioinformatics and Its Applications, 2005)

Path Planning for Unmanned Vehicles Using Ant Colony Optimization on a Dynamic Voronoi Diagram. - Yaohang Li; Tao Dong; Marwan Bikdash; Yong-Duan Song (IC-AI, 2005)

Secure Remote Compiling Services on the Grid. - Yaohang Li; Daniel Tsu-Tang Chen; Xiaohong Yuan; Huiming Yu; Albert C. Esterline (PDPTA, 2005)

A Personal Software Process Tool for Eclipse Environment. - Xiaohong Yuan; Percy Vega; Huiming Yu; Yaohang Li (Software Engineering Research and Practice, 2005)

Grid-based Quasi-Monte Carlo Applications. - Yaohang Li; Michael Mascagni (Monte Carlo Methods Appl., 2005)

Large-scale software unit testing on the grid. - Yaohang Li; Tao Dong; Xinyu Zhang; Yong-Duan Song; Xiaohong Yuan (GrC, 2006)

Using Grid Computing for Distributed Software Testing. - Yong-Duan Song; Tao Dong; Yaohang Li (PDPTA, 2006)

Using packet sniffer simulator in the class: experience and evaluation. - Xiaohong Yuan; Percy Vega; Jinsheng Xu; Huiming Yu; Yaohang Li (ACM Southeast Regional Conference, 2007)

Decentralized Replica Exchange Parallel Tempering: An Efficient Implementation of Parallel Tempering Using MPI and SPRNG. - Yaohang Li; Michael Mascagni; Andrey Gorin (ICCSA (3), 2007)

Efficient Parallel Implementation of Evolutionary Markov Chain Monte Carlo. - Yaohang Li; Jason Clark; Kenneth W. Williams; Christopher Doss; Yong-Duan Song (PDPTA, 2007)

Trustworthy remote compiling services for grid-based scientific applications. - Yaohang Li; Daniel Chen; Xiaohong Yuan (J. Supercomput., 2007)

A Sensor Information Framework for Integrating and Orchestrating Distributed Sensor Services. - Yaohang Li; Albert C. Esterline; Cheickna Baber; Kawana Fuller; Michael Burns; Tracy Hansen; Thomas LeFebvre; MarySue Schultz; Mark Govett; Paul Hamer; Ashvin Mysore (PDPTA, 2008)

An adaptive and trustworthy software testing framework on the grid. - Yaohang Li; Yong-Duan Song (J. Supercomput., 2008)

Teaching Operating Systems Using Visualization: A Comparative Study. - Xiaohong Yuan; Barbara T. Pioro; Ricky Archer; Yaohang Li (Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education, 2008)

A Population-Based Approach for Diversified Protein Loop Structure Sampling. - Yaohang Li (ICCS (1), 2009)

Minkowski Functionals Study of Random Number Sequences. - Xinyu Zhang; Seth E. Watts; Yaohang Li; Daniel A. Tortorelli (ICCS (1), 2009)

Resource-efficient computing paradigm for computational protein modeling applications. - Yaohang Li; Douglas Wardell; Vincent W. Freeh (IPDPS, 2009)

Hybrid parallel tempering and simulated annealing method. - Yaohang Li; Vladimir A. Protopopescu; Nikita Arnold; Xinyu Zhang; Andrey Gorin (Appl. Math. Comput., 2009)

A decentralized parallel implementation for parallel tempering algorithm. - Yaohang Li; Michael Mascagni; Andrey Gorin (Parallel Comput., 2009)

Study of Computing Consolidation Techniques in Computational Protein Loop Structure Modeling. - Yaohang Li; Douglas Wardell (BICoB, 2010)

Integrating multiple scoring functions to improve protein loop structure conformation space sampling. - Yaohang Li; Ionel Rata; Eric Jakobsson (CIBCB, 2010)

GPU-accelerated differential evolutionary Markov Chain Monte Carlo method for multi-objective optimization over continuous space. - Weihang Zhu; Yaohang Li (BADS@ICAC, 2010)

GPU-accelerated multi-scoring functions protein loop structure sampling. - Yaohang Li; Weihang Zhu (IPDPS Workshops, 2010)

A Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction. - Loc Tran; Debrup Banerjee; Xiaoyan Sun 004; Jihong Wang; Ashok J. Kumar; David Vinning; Frederic D. McKenzie; Yaohang Li; Jiang Li 001 (MLMI, 2011)

Sampling Multiple Scoring Functions Can Improve Protein Loop Structure Prediction Accuracy. - Yaohang Li; Ionel Rata; Eric Jakobsson (J. Chem. Inf. Model., 2011)

DEMCMC-GPU: An Efficient Multi-Objective Optimization Method with GPU Acceleration on the Fermi Architecture. - Weihang Zhu; Ashraf Yaseen; Yaohang Li (New Gener. Comput., 2011)

MOMCMC: An efficient Monte Carlo method for multi-objective sampling over real parameter space. - Yaohang Li (Comput. Math. Appl., 2012)

Accelerating knowledge-based energy evaluation in protein structure modeling with Graphics Processing Units. - Ashraf Yaseen; Yaohang Li (J. Parallel Distributed Comput., 2012)

Reusing Random Walks in Monte Carlo Methods for Linear Systems. - Hao Ji; Yaohang Li (ICCS, 2012)

An improved statistics-based backbone torsion potential energy for protein loop structure modeling. - Ionel Rata; Kyle Wessells; Yaohang Li (ICCABS, 2013)

Template-based prediction of protein 8-state secondary structures. - Ashraf Yaseen; Yaohang Li (ICCABS, 2013)

Dinosolve: a protein disulfide bonding prediction server using context-based features to enhance prediction accuracy. - Ashraf Yaseen; Yaohang Li (BMC Bioinform., 2013)

Building a Knowledge-Based Statistical Potential by Capturing High-Order Inter-residue Interactions and its Applications in Protein Secondary Structure Assessment. - Yaohang Li; Hui Liu 021; Ionel Rata; Eric Jakobsson (J. Chem. Inf. Model., 2013)

High-dimensional MRI data analysis using a large-scale manifold learning approach. - Loc Tran; Debrup Banerjee; Jihong Wang; Ashok J. Kumar; Frederic D. McKenzie; Yaohang Li; Jiang Li 001 (Mach. Vis. Appl., 2013)

Convergence Analysis of Markov Chain Monte Carlo Linear Solvers Using Ulam-von Neumann Algorithm. - Hao Ji; Michael Mascagni; Yaohang Li (SIAM J. Numer. Anal., 2013)

An implementation of block conjugate gradient algorithm on CPU-GPU processors. - Hao Ji; Masha Sosonkina; Yaohang Li (Co-HPC@SC, 2014)

Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features. - Ashraf Yaseen; Yaohang Li (BMC Bioinform., 2014)

Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy. - Ashraf Yaseen; Yaohang Li (J. Chem. Inf. Model., 2014)

Teaching Information Security with Workflow Technology: A Case Study Approach. - Wu He; Ashish Kshirsagar; Alexander C. Nwala; Yaohang Li (J. Inf. Syst. Educ., 2014)

Understanding Mobile Banking Applications' Security risks through Blog Mining and the Workflow Technology. - Wu He; Xin Tian; Jiancheng Shen; Yaohang Li (ICIS, 2015)

Using Workflow Technology to Create Scenario-based Workflows for Information Security Education: Scenario-based Workflows (Abstract Only). - Wu He; Ashish Kshirsagar; Alexander C. Nwala; Yaohang Li (SIGCSE, 2015)

Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world. - Wu He; Jiancheng Shen; Xin Tian; Yaohang Li; Vasudeva Akula; Gongjun Yan; Ran Tao 005 (Ind. Manag. Data Syst., 2015)

Coarse-Grained Contact Potential Helps Improve Fold Recognition Sensitivity in Template-Based Protein Structure Modeling. - Maha M. Abdelrasoul; Yaohang Li (BDCloud-SocialCom-SustainCom, 2016)

Malware Sequence Alignment. - Andrew Dinh; Daniel Brill; Yaohang Li; Wu He (BDCloud-SocialCom-SustainCom, 2016)

What Differentiates News Articles with Short and Long Shelf Lives? A Case Study on News Articles at Bloomberg.com. - Wessam Elhefnawy; Jesse Wright; Kumara Kallepalli; Kevin Racheal; Ajay Gupta 003; Rohit Parimi; Parth Shah; Yaohang Li (BDCloud-SocialCom-SustainCom, 2016)

An Apache Spark Implementation of Block Power Method for Computing Dominant Eigenvalues and Eigenvectors of Large-Scale Matrices. - Hao Ji; Seth H. Weinberg; Min Li 007; Jianxin Wang 001; Yaohang Li (BDCloud-SocialCom-SustainCom, 2016)

FLEXc: protein flexibility prediction using context-based statistics, predicted structural features, and sequence information. - Ashraf Yaseen; Mais Nijim; Brandon Williams; Lei Qian; Min Li 007; Jianxin Wang 001; Yaohang Li (BMC Bioinform., 2016)

Efficient randomized algorithms for adaptive low-rank factorizations of large matrices. - Yu Gu; Wenjian Yu; Yaohang Li (CoRR, 2016)

A Revisit of Block Power Methods for Finite State Markov Chain Applications. - Hao Ji; Seth H. Weinberg; Yaohang Li (CoRR, 2016)

A Rank Revealing Randomized Singular Value Decomposition (R3SVD) Algorithm for Low-rank Matrix Approximations. - Hao Ji; Wenjian Yu; Yaohang Li (CoRR, 2016)

Big data-enabled multiscale serviceability analysis for aging bridges☆. - Yu Liang; Dalei Wu; Guirong Liu; Yaohang Li; Cuilan Gao; Zhongguo John Ma; Weidong Wu (Digit. Commun. Networks, 2016)

Predicting drug-target interaction using positive-unlabeled learning. - Wei Lan; Jianxin Wang 001; Min Li 007; Jin Liu 012; Yaohang Li; Fang-Xiang Wu; Yi Pan 001 (Neurocomputing, 2016)

A load-balancing workload distribution scheme for three-body interaction computation on Graphics Processing Units (GPU). - Ashraf Yaseen; Hao Ji; Yaohang Li (J. Parallel Distributed Comput., 2016)

RCD+: Fast loop modeling server. - José Ramón López-Blanco; Alejandro Jesús Canosa-Valls; Yaohang Li; Pablo Chacón (Nucleic Acids Res., 2016)

Validating the Correctness of Outsourced Computational Tasks Using Pseudorandom Number Generators. - Yaohang Li; Ravi Mukkamala; Michael Mascagni (DASC/PiCom/DataCom/CyberSciTech, 2017)

Single-Pass PCA of Large High-Dimensional Data. - Wenjian Yu; Yu Gu; Jian Li; Shenghua Liu; Yaohang Li (IJCAI, 2017)

Construction of Protein Backbone Fragments Libraries on Large Protein Sets Using a Randomized Spectral Clustering Algorithm. - Wessam Elhefnawy; Min Li 007; Jianxin Wang 001; Yaohang Li (ISBRA, 2017)

Relating Diseases Based on Disease Module Theory. - Peng Ni; Min Li 007; Ping Zhong 002; Guihua Duan; Jianxin Wang 001; Yaohang Li; Fang-Xiang Wu (ISBRA, 2017)

A Fast Implementation of Singular Value Thresholding Algorithm using Recycling Rank Revealing Randomized Singular Value Decomposition. - Yaohang Li; Wenjian Yu (CoRR, 2017)

Block Conjugate Gradient algorithms for least squares problems. - Hao Ji; Yaohang Li (J. Comput. Appl. Math., 2017)

A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions. - Yihao Liang; Xiangjun Xing; Yaohang Li (J. Comput. Phys., 2017)

Calcium Ion Fluctuations Alter Channel Gating in a Stochastic Luminal Calcium Release Site Model. - Hao Ji; Yaohang Li; Seth H. Weinberg (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Identifying At-Risk Students for Early Interventions - A Time-Series Clustering Approach. - Jui-Long Hung; Morgan C. Wang; Shuyan Wang; Maha M. Abdelrasoul; Yaohang Li; Wu He (IEEE Trans. Emerg. Top. Comput., 2017)

Disease Inference with Symptom Extraction and Bidirectional Recurrent Neural Network. - Donglin Guo; Min Li 007; Ying Yu; Yaohang Li; Guihua Duan; Fang-Xiang Wu; Jianxin Wang 001 (BIBM, 2018)

A Deep Learning Framework for Identifying Essential Proteins Based on Protein-Protein Interaction Network and Gene Expression Data. - Min Zeng; Min Li 007; Zhihui Fei; Fang-Xiang Wu; Yaohang Li; Yi Pan 001 (BIBM, 2018)

Using Deep Neural Network to Predict Drug Sensitivity of Cancer Cell Lines. - Yake Wang; Min Li 007; Ruiqing Zheng; Xinghua Shi; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (ICIC (2), 2018)

Faster Matrix Completion Using Randomized SVD. - Xu Feng; Wenjian Yu; Yaohang Li (ICTAI, 2018)

PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks. - Siyu Zhao; Ruiqing Zheng; Xiang Chen; Yaohang Li; Fang-Xiang Wu; Min Li 007 (ISBRA, 2018)

A survey of matrix completion methods for recommendation systems. - Andy Ramlatchan; Mengyun Yang; Quan Liu; Min Li 007; Jianxin Wang 001; Yaohang Li (Big Data Min. Anal., 2018)

Prediction of lncRNA-disease associations based on inductive matrix completion. - Chengqian Lu; Mengyun Yang; Feng Luo 001; Fang-Xiang Wu; Min Li 007; Yi Pan 001; Yaohang Li; Jianxin Wang 001 (Bioinform., 2018)

Computational drug repositioning using low-rank matrix approximation and randomized algorithms. - Huimin Luo; Min Li 007; Shaokai Wang; Quan Liu; Yaohang Li; Jianxin Wang 001 (Bioinform., 2018)

Efficient Randomized Algorithms for the Fixed-Precision Low-Rank Matrix Approximation. - Wenjian Yu; Yu Gu; Yaohang Li (SIAM J. Matrix Anal. Appl., 2018)

LncRNA-disease association prediction through combining linear and non-linear features with matrix factorization and deep learning techniques. - Min Zeng; Chengqian Lu; Fuhao Zhang; Zhangli Lu; Fang-Xiang Wu; Yaohang Li; Min Li 007 (BIBM, 2019)

AttentionDTA: prediction of drug-target binding affinity using attention model. - Qichang Zhao; Fen Xiao; Mengyun Yang; Yaohang Li; Jianxin Wang 001 (BIBM, 2019)

Clinical big data and deep learning: Applications, challenges, and future outlooks. - Ying Yu; Min Li 007; Liangliang Liu 001; Yaohang Li; Jianxin Wang 001 (Big Data Min. Anal., 2019)

Drug repositioning based on bounded nuclear norm regularization. - Mengyun Yang; Huimin Luo; Yaohang Li; Jianxin Wang 001 (Bioinform., 2019)

DeepEP: a deep learning framework for identifying essential proteins. - Min Zeng; Min Li 007; Fang-Xiang Wu; Yaohang Li; Yi Pan 001 (BMC Bioinform., 2019)

Decoding the Structural Keywords in Protein Structure Universe. - Wessam Elhefnawy; Min Li 007; Jianxin Wang 001; Yaohang Li (J. Comput. Sci. Technol., 2019)

Overlap matrix completion for predicting drug-associated indications. - Mengyun Yang; Huimin Luo; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (PLoS Comput. Biol., 2019)

Automated ICD-9 Coding via A Deep Learning Approach. - Min Li 007; Zhihui Fei; Min Zeng; Fang-Xiang Wu; Yaohang Li; Yi Pan 001; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

MGT-SM: A Method for Constructing Cellular Signal Transduction Networks. - Min Li 007; Ruiqing Zheng; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

A novel approach based on deep residual learning to predict drug's anatomical therapeutic chemical code. - Haochen Zhao; Peng Ni; Cheng Yan; Yaohang Li; Jianxin Wang 001 (BIBM, 2020)

cFAT-GAN: Conditional Simulation of Electron-Proton Scattering Events with Variate Beam Energies by a Feature Augmented and Transformed Generative Adversarial Network. - Luisa Velasco; Evan McClellan; Nobuo Sato; Pawel Ambrozewicz; Tianbo Liu 004; W. Melnitchouk; Michelle P. Kuchera; Yasir Alanazi; Yaohang Li (ICMLA, 2020)

De novo Prediction of Drug-Target Interaction via Laplacian Regularized Schatten-p Norm Minimization. - Gaoyan Wu; Mengyun Yang; Yaohang Li; Jianxin Wang 001 (ISBRA, 2020)

CLPred: a sequence-based protein crystallization predictor using BLSTM neural network. - Wenjing Xuan; Ning Liu; Neng Huang; Yaohang Li; Jianxin Wang 001 (Bioinform., 2020)

Protein-protein interaction site prediction through combining local and global features with deep neural networks. - Min Zeng; Fuhao Zhang; Fang-Xiang Wu; Yaohang Li; Jianxin Wang 001; Min Li 007 (Bioinform., 2020)

DeepFrag-k: a fragment-based deep learning approach for protein fold recognition. - Wessam Elhefnawy; Min Li 007; Jianxin Wang 001; Yaohang Li (BMC Bioinform., 2020)

Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). - Yasir Alanazi; Nobuo Sato; Tianbo Liu 004; W. Melnitchouk; Michelle P. Kuchera; Evan Pritchard; Michael Robertson; Ryan R. Strauss; Luisa Velasco; Yaohang Li (CoRR, 2020)

Gaussian variant of Freivalds' algorithm for efficient and reliable matrix product verification. - Hao Ji; Michael Mascagni; Yaohang Li (Monte Carlo Methods Appl., 2020)

United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins. - Gaoshi Li; Min Li 007; Jianxin Wang 001; Yaohang Li; Yi Pan 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Identification of Protein Complexes by Using a Spatial and Temporal Active Protein Interaction Network. - Min Li 007; Xiangmao Meng; Ruiqing Zheng; Fang-Xiang Wu; Yaohang Li; Yi Pan 001; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Constructing Disease Similarity Networks Based on Disease Module Theory. - Peng Ni; Jianxin Wang 001; Ping Zhong 002; Yaohang Li; Fang-Xiang Wu; Yi Pan 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

miRTMC: A miRNA Target Prediction Method Based on Matrix Completion Algorithm. - Hui Jiang 008; Mengyun Yang; Xiang Chen; Min Li 007; Yaohang Li; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2020)

Predicting Human lncRNA-Disease Associations Based on Geometric Matrix Completion. - Chengqian Lu; Mengyun Yang; Min Li 007; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2020)

Multi-Label Classification of ICD-10 Coding & Clinical Notes Using MIMIC & CodiEsp. - Ivan Makohon; Yaohang Li (BHI, 2021)

Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). - Yasir Alanazi; Nobuo Sato; Tianbo Liu 004; Wally Melnitchouk; Pawel Ambrozewicz; Florian Hauenstein; Michelle P. Kuchera; Evan Pritchard; Michael Robertson; Ryan R. Strauss; Luisa Velasco; Yaohang Li (IJCAI, 2021)

A Survey of Machine Learning-Based Physics Event Generation. - Yasir Alanazi; Nobuo Sato; Pawel Ambrozewicz; Astrid N. Hiller Blin; Wally Melnitchouk; Marco Battaglieri; Tianbo Liu 004; Yaohang Li (IJCAI, 2021)

Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems. - Manal Almaeen; Yasir Alanazi; Nobuo Sato; W. Melnitchouk; Michelle P. Kuchera; Yaohang Li (IJCNN, 2021)

Biomedical data and computational models for drug repositioning: a comprehensive review. - Huimin Luo; Min Li 007; Mengyun Yang; Fang-Xiang Wu; Yaohang Li; Jianxin Wang 001 (Briefings Bioinform., 2021)

DeepDTAF: a deep learning method to predict protein-ligand binding affinity. - Kaili Wang; Renyi Zhou; Yaohang Li; Min Li 007 (Briefings Bioinform., 2021)

Computational drug repositioning based on multi-similarities bilinear matrix factorization. - Mengyun Yang; Gaoyan Wu; Qichang Zhao; Yaohang Li; Jianxin Wang 001 (Briefings Bioinform., 2021)

A novel graph attention model for predicting frequencies of drug-side effects from multi-view data. - Haochen Zhao; Kai Zheng 020; Yaohang Li; Jianxin Wang 001 (Briefings Bioinform., 2021)

Parallel computing for genome sequence processing. - You Zou; Yuejie Zhu; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (Briefings Bioinform., 2021)

A convolutional neural network and graph convolutional network-based method for predicting the classification of anatomical therapeutic chemicals. - Haochen Zhao; Yaohang Li; Jianxin Wang 001 (Bioinform., 2021)

De Novo Prediction of Drug-Target Interactions Using Laplacian Regularized Schatten p-Norm Minimization. - Gaoyan Wu; Mengyun Yang; Yaohang Li; Jianxin Wang 001 (J. Comput. Biol., 2021)

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines. - Min Li 007; Yake Wang; Ruiqing Zheng; Xinghua Shi; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information. - Min Zeng; Min Li 007; Zhihui Fei; Fang-Xiang Wu; Yaohang Li; Yi Pan 001; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations. - Min Zeng; Chengqian Lu; Zhihui Fei; Fang-Xiang Wu; Yaohang Li; Jianxin Wang 001; Min Li 007 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information. - Fuhao Zhang; Hong Song; Min Zeng; Fang-Xiang Wu; Yaohang Li; Yi Pan 001; Min Li 007 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Protein interaction networks: centrality, modularity, dynamics, and applications. - Xiangmao Meng; Wenkai Li; Xiaoqing Peng; Yaohang Li; Min Li 007 (Frontiers Comput. Sci., 2021)

Point Cloud-based Variational Autoencoder Inverse Mappers (PC-VAIM) - An Application on Quantum Chromodynamics Global Analysis. - Manal Almaeen; Yasir Alanazi; Nobuo Sato; W. Melnitchouk; Yaohang Li (ICMLA, 2022)

Image Synthesis Using Conditional GANs for Selective Laser Melting Additive Manufacturing. - Andy Ramlatchan; Yaohang Li (IJCNN, 2022)

IIFDTI: predicting drug-target interactions through interactive and independent features based on attention mechanism. - Zhongjian Cheng; Qichang Zhao; Yaohang Li; Jianxin Wang 001 (Bioinform., 2022)

BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction. - Min Li 007; Zhangli Lu; Yifan Wu 008; Yaohang Li (Bioinform., 2022)

Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning. - Yiming Li; Min Zeng; Yifan Wu 008; Yaohang Li; Min Li 007 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Biomedical Data and Deep Learning Computational Models for Predicting Compound-Protein Relations. - Qichang Zhao; Mengyun Yang; Zhongjian Cheng; Yaohang Li; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

A Pseudo Label-Wise Attention Network for Automatic ICD Coding. - Yifan Wu 008; Min Zeng; Ying Yu; Yaohang Li; Min Li 007 (IEEE J. Biomed. Health Informatics, 2022)

Feature and Nuclear Norm Minimization for Matrix Completion. - Mengyun Yang; Yaohang Li; Jianxin Wang 001 (IEEE Trans. Knowl. Data Eng., 2022)

CellBRF: a feature selection method for single-cell clustering using cell balance and random forest. - Yunpei Xu; Hong-Dong Li; Cui-Xiang Lin; Ruiqing Zheng; Yaohang Li; Jinhui Xu 001; Jianxin Wang 001 (Bioinform., 2023)

Retrieve and rerank for automated ICD coding via Contrastive Learning. - Kunying Niu; Yifan Wu 008; Yaohang Li; Min Li 007 (J. Biomed. Informatics, 2023)

A Deep Learning Framework for Predicting Protein Functions With Co-Occurrence of GO Terms. - Min Li 007; Wenbo Shi; Fuhao Zhang; Min Zeng; Yaohang Li (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

A Comparison of Topologically Associating Domain Callers Based on Hi-C Data. - Kun Liu 028; Hong-Dong Li; Yaohang Li; Jun Wang 153; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

RNPredATC: A Deep Residual Learning-Based Model With Applications to the Prediction of Drug-ATC Code Association. - Haochen Zhao; Guihua Duan; Peng Ni; Cheng Yan; Yaohang Li; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

AttentionDTA: Drug-Target Binding Affinity Prediction by Sequence-Based Deep Learning With Attention Mechanism. - Qichang Zhao; Guihua Duan; Mengyun Yang; Zhongjian Cheng; Yaohang Li; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

GIFDTI: Prediction of Drug-Target Interactions Based on Global Molecular and Intermolecular Interaction Representation Learning. - Qichang Zhao; Guihua Duan; Haochen Zhao; Kai Zheng 020; Yaohang Li; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

CRMSS: predicting circRNA-RBP binding sites based on multi-scale characterizing sequence and structure features. - Lishen Zhang; Chengqian Lu; Min Zeng; Yaohang Li; Jianxin Wang 001 (Briefings Bioinform., 2023)

DFHiC: a dilated full convolution model to enhance the resolution of Hi-C data. - Bin Wang; Kun Liu 028; Yaohang Li; Jianxin Wang 001 (Bioinform., 2023)

MSDRP: a deep learning model based on multisource data for predicting drug response. - Haochen Zhao; Xiaoyu Zhang; Qichang Zhao; Yaohang Li; Jianxin Wang 001 (Bioinform., 2023)

BenchLMM: Benchmarking Cross-Style Visual Capability of Large Multimodal Models. - Rizhao Cai; Zirui Song; Dayan Guan; Zhenhao Chen; Yaohang Li; Xing Luo; Chenyu Yi; Alex C. Kot (ECCV (50), 2024)

Unfolding Particle Detector Acceptance in High Energy Physics with Generative AI. - Tareq Alghamdi; Tommaso Vittorini; Marco Spreafico; Marco Battaglieri; Nobuo Sato; Yaohang Li (ICTAI, 2024)

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. - Meng Wang; Chuqi Lei; Jianxin Wang 001; Yaohang Li; Min Li 007 (Briefings Bioinform., 2024)

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks. - Chao Deng; Hong-Dong Li; Li-Shen Zhang; Yiwei Liu; Yaohang Li; Jianxin Wang 001 (Bioinform., 2024)

MMAC-Copilot: Multi-modal Agent Collaboration Operating System Copilot. - Zirui Song; Yaohang Li; Meng Fang; Zhenhao Chen; Zecheng Shi; Yuan Huang; Ling Chen 006 (CoRR, 2024)

TopoLa: a novel embedding framework for understanding complex networks. - Kai Zheng 020; Qilong Feng; Yaohang Li; Qichang Zhao; Jinhui Xu 001; Jianxin Wang 001 (CoRR, 2024)