World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5685
World Ranking
9843
National Ranking
4144

Overview

Yaohang Li is affiliated with Old Dominion University in the United States. Their research primarily spans the fields of Biochemistry, Genetics and Molecular Biology as well as Computer Science. Within these domains, they have contributed extensively to subfields including Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Nuclear and High Energy Physics, and Materials Chemistry.

Li's work covers major topics such as Computational Drug Discovery Methods, Machine Learning in Bioinformatics, Protein Structure and Dynamics, Bioinformatics and Genomic Networks, Particle Physics Theoretical and Experimental Studies, Machine Learning in Materials Science, and Gene Expression and Cancer Classification.

The scientist's recent publications have appeared in respected journals and conferences, reflecting active engagement in bioinformatics and computational biology. Notable recent papers include:

  • Biomedical data and computational models for drug repositioning: a comprehensive review, 2020, Briefings in Bioinformatics
  • DeepDTAF: a deep learning method to predict protein-ligand binding affinity, 2021, Briefings in Bioinformatics
  • Computational drug repositioning based on multi-similarities bilinear matrix factorization, 2020, Briefings in Bioinformatics
  • SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning, 2020, Methods
  • BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction, 2022, Bioinformatics

Frequent co-authors with whom Li has collaborated include Jianxin Wang, Min Li, Qichang Zhao, Mengyun Yang, and Fang-Xiang Wu. Their collaborative work indicates sustained research partnerships within computational biology and related fields.

Li's research has been published frequently in venues such as arXiv (Cornell University), Bioinformatics, Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and IEEE Journal of Biomedical and Health Informatics. This reflects a strong presence in both biological and computational research communities.

Best Publications

  • Protein–protein interaction site prediction through combining local and global features with deep neural networks

    Min Zeng;Fuhao Zhang;Fang-Xiang Wu;Yaohang Li

  • Prediction of lncRNA-disease associations based on inductive matrix completion.

    Chengqian Lu;Mengyun Yang;Feng Luo;Fang-Xiang Wu

  • Computational drug repositioning using low-rank matrix approximation and randomized algorithms.

    Huimin Luo;Min Li;Shaokai Wang;Quan Liu

  • Biomedical data and computational models for drug repositioning: a comprehensive review.

    Huimin Luo;Min Li;Mengyun Yang;Fang-Xiang Wu

  • DeepDTAF: a deep learning method to predict protein-ligand binding affinity.

    Kaili Wang;Renyi Zhou;Yaohang Li;Min Li

  • Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world

    Wu He;Jiancheng Shen;Xin Tian;Yaohang Li

  • Drug repositioning based on bounded nuclear norm regularization

    Mengyun Yang;Mengyun Yang;Huimin Luo;Yaohang Li;Jianxin Wang

  • A Survey of Matrix Completion Methods for Recommendation Systems

    Andy Ramlatchan;Mengyun Yang;Quan Liu;Min Li

  • Automated ICD-9 Coding via A Deep Learning Approach

    Min Li;Zhihui Fei;Min Zeng;Fang-Xiang Wu

  • DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines

    Min Li;Yake Wang;Ruiqing Zheng;Xinghua Shi

  • Clinical big data and deep learning: Applications, challenges, and future outlooks

    Ying Yu;Min Li;Liangliang Liu;Yaohang Li

  • Predicting drugtarget interaction using positive-unlabeled learning

    Wei Lan;Jianxin Wang;Min Li;Jin Liu

  • Identifying At-Risk Students for Early Interventions—A Time-Series Clustering Approach

    Jui-Long Hung;Morgan C. Wang;Shuyan Wang;Maha Abdelrasoul

  • Computational drug repositioning based on multi-similarities bilinear matrix factorization.

    Mengyun Yang;Gaoyan Wu;Qichang Zhao;Yaohang Li

  • A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information

    Min Zeng;Min Li;Zhihui Fei;Fang-Xiang Wu

  • DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions.

    Fuhao Zhang;Hong Song;Min Zeng;Yaohang Li;Yaohang Li

  • United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins

    Gaoshi Li;Min Li;Jianxin Wang;Yaohang Li

  • SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning.

    Min Zeng;Chengqian Lu;Fuhao Zhang;Yiming Li

  • Context-based features enhance protein secondary structure prediction accuracy.

    Ashraf Yaseen;Yaohang Li

  • AttentionDTA: prediction of drug–target binding affinity using attention model

    Qichang Zhao;Fen Xiao;Mengyun Yang;Yaohang Li

Frequent Co-Authors

Jianxin Wang
Jianxin Wang Central South University
Min Li
Min Li Central South University
Fang-Xiang Wu
Fang-Xiang Wu University of Saskatchewan
Yi Pan
Yi Pan Shenzhen Institutes of Advanced Technology
Wu He
Wu He Old Dominion University
Lukasz Kurgan
Lukasz Kurgan Virginia Commonwealth University
Gongjun Yan
Gongjun Yan University of Southern Indiana

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