Yaohang Li

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Min LiSchool of Computer Science and Engineering, Central South UniversityVerified email at mail.csu.edu.cn
Jianxin WangSchool of Computer Science and Engineering, Central South universityVerified email at mail.csu.edu.cn
FangXiang WUUniversity of SaskatchewanVerified email at usask.ca
Prof. Michael MascagniProfessor of Computer Science, Florida State UniversityVerified email at fsu.edu
Yi PanShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, ChinaVerified email at cs.gsu.edu
Min ZengSchool of Computer Science and Engineering, Central South UniversityVerified email at csu.edu.cn
Hao JiCalifornia State Polytechnic University, PomonaVerified email at cpp.edu
Ashraf YaseenAssistant Professor of Data Science, UTHealthVerified email at uth.tmc.edu
Wenjian YuDept. Computer Science & Technology, Tsinghua UniversityVerified email at tsinghua.edu.cn
Eric JakobssonVerified email at illinois.edu
Weihang ZhuUniversity of HoustonVerified email at uh.edu
Yu LIANG (梁煜)Professor of Computer Science, University of Tennessee at ChattanoogaVerified email at utc.edu
Feng LuoProfessor, School of Computing, Clemson UniversityVerified email at clemson.edu
Vladimir ProtopopescuChief Scientist, CSED, ORNLVerified email at ornl.gov
Seth H. WeinbergBiomedical Engineering, The Ohio State UniversityVerified email at osu.edu
michael h. petersProfessor of Chemical and Life Science EngineeringVerified email at vcu.edu
Pablo ChacónHead of Structural Bioinformatics Group at the Instituto de Química Física Rocasolano (CSIC), MadridVerified email at chaconlab.org
Nikita ArnoldJKU LinzVerified email at jku.at
Jiang LiOld Dominion UniversityVerified email at odu.edu
Charlie E M StraussLos Alamos National LaboratoryVerified email at lanl.gov

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	196	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	161	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	142	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, 2015	140	2015
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	106	2018
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	98	2021
Drug repositioning based on bounded nuclear norm regularization M Yang, H Luo, Y Li, J Wang Bioinformatics 35 (14), i455-i463, 2019	95	2019
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	94	2015
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	93	2018
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	88	2016
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	87	2019
Context-based features enhance protein secondary structure prediction accuracy A Yaseen, Y Li Journal of chemical information and modeling 54 (3), 992-1002, 2014	77	2014
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	68	2019
Improving Performance via Computational Replication on a Large-Scale Computational Grid. Y Li, M Mascagni CCGRID 3, 442, 2003	68	2003
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	66	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	61	2019
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	54	2018
SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning M Zeng, C Lu, F Zhang, Y Li, FX Wu, Y Li, M Li Methods 179, 73-80, 2020	53	2020
RCD+: Fast loop modeling server JR López-Blanco, AJ Canosa-Valls, Y Li, P Chacón Nucleic acids research 44 (W1), W395-W400, 2016	53	2016
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	50	2018

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