Yaohang Li
Yaohang Li
Department of Computer Science, Old Dominion University
Verified email at
Cited by
Cited by
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
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
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
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
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
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
Drug repositioning based on bounded nuclear norm regularization
M Yang, H Luo, Y Li, J Wang
Bioinformatics 35 (14), i455-i463, 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
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
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
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
Context-based features enhance protein secondary structure prediction accuracy
A Yaseen, Y Li
Journal of chemical information and modeling 54 (3), 992-1002, 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
Improving Performance via Computational Replication on a Large-Scale Computational Grid.
Y Li, M Mascagni
CCGRID 3, 442, 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
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
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
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
RCD+: Fast loop modeling server
JR López-Blanco, AJ Canosa-Valls, Y Li, P Chacón
Nucleic acids research 44 (W1), W395-W400, 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
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