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Collaborations and top research areas from the last five years
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A Note on the Identifiability of the Degree-Corrected Stochastic Block Model
Park, J., Zhao, Y. & Hao, N., Jun 2025, In: Stat. 14, 2, e70067.Research output: Contribution to journal › Article › peer-review
Open Access -
A reference-guided iterative approach to polish the nanopore sequencing basecalling for therapeutic RNA quality control
Wang, Z., Tu, M. J., Liu, Z., Wang, K. K., Fang, Y., Hao, N., Zhang, H. H., Que, J., Sun, X., Yu, A. M. & Ding, H., Dec 2025, In: Communications biology. 8, 1, 1406.Research output: Contribution to journal › Article › peer-review
Open Access -
Dynamic Supervised Principal Component Analysis for Classification
Ouyang, W., Wu, R., Hao, N. & Zhang, H. H., 2025, In: Journal of Computational and Graphical Statistics. 34, 4, p. 1446-1455 10 p.Research output: Contribution to journal › Article › peer-review
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Training data diversity enhances the basecalling of novel RNA modification-induced nanopore sequencing readouts
Wang, Z., Liu, Z., Fang, Y., Zhang, H. H., Sun, X., Hao, N., Que, J. & Ding, H., Dec 2025, In: Nature communications. 16, 1, 679.Research output: Contribution to journal › Article › peer-review
Open Access12 Link opens in a new tab Scopus citations -
Adapting nanopore sequencing basecalling models for modification detection via incremental learning and anomaly detection
Wang, Z., Fang, Y., Liu, Z., Hao, N., Zhang, H. H., Sun, X., Que, J. & Ding, H., Dec 2024, In: Nature communications. 15, 1, 7148.Research output: Contribution to journal › Article › peer-review
Open Access16 Link opens in a new tab Scopus citations
Datasets
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Raw data for Training Data Diversity Enhances the Basecalling of Novel RNA Modification-Induced Nanopore Sequencing Readouts
Wang, Z. (Creator), Fang, Y. (Contributor), Zhang, H. H. (Contributor), Sun, X. (Contributor), Hao, N. (Contributor), Que, J. (Contributor) & Ding, H. (Creator), University of Arizona Research Data Repository, 2024
DOI: 10.25422/azu.data.27976647.v2, https://arizona.figshare.com/articles/dataset/Raw_data_for_i_Training_Data_Diversity_Enhances_the_Basecalling_of_Novel_RNA_Modification-Induced_Nanopore_Sequencing_Readouts_i_/27976647/2
Dataset
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Interaction Screening for Ultrahigh-Dimensional Data
Hao, N. (Creator) & Zhang, H. H. (Creator), figshare, 2018
DOI: 10.6084/m9.figshare.7037666, https://tandf.figshare.com/articles/Interaction_Screening_for_Ultrahigh-Dimensional_Data/7037666
Dataset
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Raw data for Training Data Diversity Enhances the Basecalling of Novel RNA Modification-Induced Nanopore Sequencing Readouts
Wang, Z. (Creator), Fang, Y. (Contributor), Zhang, H. H. (Contributor), Sun, X. (Contributor), Hao, N. (Contributor), Que, J. (Contributor) & Ding, H. (Creator), University of Arizona Research Data Repository, 2024
DOI: 10.25422/azu.data.27976647, https://arizona.figshare.com/articles/dataset/Raw_data_for_i_Training_Data_Diversity_Enhances_the_Basecalling_of_Novel_RNA_Modification-Induced_Nanopore_Sequencing_Readouts_i_/27976647
Dataset
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Interaction Screening for Ultrahigh-Dimensional Data
Hao, N. (Creator) & Zhang, H. H. (Creator), Taylor & Francis, 2018
DOI: 10.6084/m9.figshare.7037666.v1, https://tandf.figshare.com/articles/Interaction_Screening_for_Ultrahigh-Dimensional_Data/7037666/1
Dataset