Lin, Hao

Ipro54-pseknc: A sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition

Lin, H., Deng, E.-Z., Ding, H., Chen, W., & Chou, K.-C. (2014) · Nucleic Acids Research

Machine Learning in BioinformaticsGenomics and Phylogenetic Studies

Cited by 508

Inuc-pseknc: A sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition

Guo, S.-H., Deng, E.-Z., Xu, L.-Q., Ding, H., Lin, H., Chen, W., & Chou, K.-C. (2014) · Bioinformatics

Machine Learning in BioinformaticsGenomics and Chromatin Dynamics

Cited by 375

iRNA-PseU: Identifying RNA pseudouridine sites

Chen, W., Tang, H., Ye, J., Lin, H., & Chou, K.-C. (2016) · Molecular Therapy - Nucleic Acids

RNA modifications and cancerMachine Learning in Bioinformatics

Cited by 291

Identification of Antioxidants from Sequence Information Using Naïve Bayes

Feng, P.-M., Lin, H., & Chen, W. (2013) · Computational and Mathematical Methods in Medicine

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 109

Sequence-based predictive modeling to identify cancerlectins

Lai, H.-Y., Chen, X.-X., Chen, W., Tang, H., & Lin, H. (2017) · Oncotarget

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 94

Identifying antioxidant proteins by using optimal dipeptide compositions

Feng, P., Chen, W., & Lin, H. (2016) · Interdisciplinary Sciences: Computational Life Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 60

RepliChrom: Interpretable machine learning predicts cancer‐associated enhancer‐promoter interactions using DNA replication timing

Dao, F., Lebeau, B., Ling, C. C. Y., Yang, M., Xie, X., Fullwood, M. J., Lin, H., & Lyu, H. (2025) · iMeta

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 23

scRiskCell: A single‐cell framework for quantifying islet risk cells and their adaptive dynamics in type 2 diabetes

Xie, X., Wu, C., Dao, F., Deng, K., Yan, D., Huang, J., Lyu, H., & Lin, H. (2025) · iMeta

Pancreatic function and diabetesSingle-cell and spatial transcriptomics

Cited by 22

Detecting key genes relative expression orderings as biomarkers for machine learning-based intelligent screening and analysis of type 2 diabetes mellitus

Xie, X., Wu, C., Ma, C., Gao, D., Su, W., Huang, J., Deng, K., Yan, D., & Lin, H. (2024) · Expert Systems with Applications

Gene expression and cancer classificationPancreatic function and diabetes

Cited by 17

Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes

Xie, X., Wu, C., Yang, Y., Su, W., Dao, F., Huang, J., Shi, Z., Lyu, H., & Lin, H. (2025) · Cardiovascular Diabetology

Pancreatic function and diabetesSingle-cell and spatial transcriptomics

Cited by 10