Yaohang Li

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Jianxin WangSchool of Computer Science and Engineering, Central South universityVerified email at mail.csu.edu.cn
Min LiSchool of Computer Science and Engineering, Central South UniversityVerified email at mail.csu.edu.cn
FangXiang WUProfessor, FIEEE, FIET, University of Saskatchewan, CanadaVerified email at usask.ca
Min ZengSchool of Computer Science and Engineering, Central South UniversityVerified email at csu.edu.cn
Yi PanShenzhen University of Advanced Technology, ChinaVerified email at cs.gsu.edu
Prof. Michael MascagniProfessor of Computer Science, Florida State UniversityVerified email at fsu.edu
Hao JiCalifornia State Polytechnic University, PomonaVerified email at cpp.edu
Ashraf YaseenAssociate Professor of Data Science, UTVerified email at uth.tmc.edu
Wenjian YuDept. Computer Science & Technology, Tsinghua UniversityVerified email at tsinghua.edu.cn
Eric JakobssonVerified email at illinois.edu
Feng LuoProfessor, School of Computing, Clemson UniversityVerified email at clemson.edu
Yu LIANG (梁煜)Professor of Computer Science, University of Tennessee at ChattanoogaVerified email at utc.edu
Weihang ZhuUniversity of HoustonVerified email at uh.edu
Vladimir ProtopopescuChief Scientist, CSED, ORNLVerified email at ornl.gov
Seth H. WeinbergBiomedical Engineering, The Ohio State UniversityVerified email at osu.edu
Pablo ChacónHead of Structural Bioinformatics Group at the Instituto de Química Física Blas Cabrera (CSIC)Verified email at chaconlab.org
michael h. petersProfessor of Chemical and Life Science EngineeringVerified email at vcu.edu
Nikita ArnoldSoft Matter Physics and LIT Soft Materials Lab, Johannes Kepler University LinzVerified email at jku.at
Jiang LiOld Dominion UniversityVerified email at odu.edu
Alexander C. Nwala, PhDAssistant professor, William & MaryVerified email at wm.edu

Yaohang Li

Department of Computer Science, Old Dominion University

Verified email at cs.odu.edu

Computational Biology Monte Carlo Methods Parallel Computing


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Prediction of lncRNA–disease associations based on inductive matrix completion C Lu, M Yang, F Luo, FX Wu, M Li, Y Pan, Y Li, J Wang Bioinformatics 34 (19), 3357-3364, 2018	261	2018
Computational drug repositioning using low-rank matrix approximation and randomized algorithms H Luo, M Li, S Wang, Q Liu, Y Li, J Wang Bioinformatics 34 (11), 1904-1912, 2018	240	2018
Protein–protein interaction site prediction through combining local and global features with deep neural networks M Zeng, F Zhang, FX Wu, Y Li, J Wang, M Li Bioinformatics 36 (4), 1114-1120, 2020	233	2020
Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world W He, J Shen, X Tian, Y Li, V Akula, G Yan, R Tao Industrial management & data systems 115 (9), 1622-1636, 2015	189	2015
Biomedical data and computational models for drug repositioning: a comprehensive review H Luo, M Li, M Yang, FX Wu, Y Li, J Wang Briefings in bioinformatics 22 (2), 1604-1619, 2021	171	2021
Clinical big data and deep learning: Applications, challenges, and future outlooks Y Yu, M Li, L Liu, Y Li, J Wang Big Data Mining and Analytics 2 (4), 288-305, 2019	170	2019
A survey of matrix completion methods for recommendation systems A Ramlatchan, M Yang, Q Liu, M Li, J Wang, Y Li Big Data Mining and Analytics 1 (4), 308-323, 2018	150	2018
Automated ICD-9 coding via a deep learning approach M Li, Z Fei, M Zeng, FX Wu, Y Li, Y Pan, J Wang IEEE/ACM transactions on computational biology and bioinformatics 16 (4 …, 2018	150	2018
Drug repositioning based on bounded nuclear norm regularization M Yang, H Luo, Y Li, J Wang Bioinformatics 35 (14), i455-i463, 2019	148	2019
DeepDSC: A deep learning method to predict drug sensitivity of cancer cell lines M Li, Y Wang, R Zheng, X Shi, Y Li, F Wu, J Wang IEEE/ACM transactions on computational biology and bioinformatics, 2019	139	2019
DeepDTAF: a deep learning method to predict protein–ligand binding affinity K Wang, R Zhou, Y Li, M Li Briefings in Bioinformatics 22 (5), bbab072, 2021	131	2021
Identifying at-risk students for early interventions—A time-series clustering approach JL Hung, MC Wang, S Wang, M Abdelrasoul, Y Li, W He IEEE Transactions on Emerging Topics in Computing 5 (1), 45-55, 2015	127	2015
AttentionDTA: prediction of drug–target binding affinity using attention model Q Zhao, F Xiao, M Yang, Y Li, J Wang 2019 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2019	109	2019
Predicting drug–target interaction using positive-unlabeled learning W Lan, J Wang, M Li, J Liu, Y Li, FX Wu, Y Pan Neurocomputing 206, 50-57, 2016	108	2016
DeepFunc: a deep learning framework for accurate prediction of protein functions from protein sequences and interactions F Zhang, H Song, M Zeng, Y Li, L Kurgan, M Li Proteomics 19 (12), 1900019, 2019	104	2019
A deep learning framework for identifying essential proteins by integrating multiple types of biological information M Zeng, M Li, Z Fei, FX Wu, Y Li, Y Pan, J Wang IEEE/ACM transactions on computational biology and bioinformatics 18 (1 …, 2019	101	2019
Computational drug repositioning based on multi-similarities bilinear matrix factorization M Yang, G Wu, Q Zhao, Y Li, J Wang Briefings in bioinformatics 22 (4), bbaa267, 2021	87	2021
Efficient randomized algorithms for the fixed-precision low-rank matrix approximation W Yu, Y Gu, Y Li SIAM Journal on Matrix Analysis and Applications 39 (3), 1339-1359, 2018	86	2018
United neighborhood closeness centrality and orthology for predicting essential proteins G Li, M Li, J Wang, Y Li, Y Pan IEEE/ACM transactions on computational biology and bioinformatics 17 (4 …, 2018	85	2018
Context-based features enhance protein secondary structure prediction accuracy A Yaseen, Y Li Journal of chemical information and modeling 54 (3), 992-1002, 2014	85	2014

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