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Pingzhao Hu
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Journal Articles
- 2024
- [j22]Leann Lac, Carson K. Leung, Pingzhao Hu
:
Computational frameworks integrating deep learning and statistical models in mining multimodal omics data. J. Biomed. Informatics 152: 104629 (2024) - 2023
- [j21]Chengyou Liu, Yan Sun, Rebecca L. Davis, Silvia T. Cardona, Pingzhao Hu:
ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction. J. Cheminformatics 15(1): 29 (2023) - [j20]Eric Lin, Boyuan Liu, Leann Lac, Daryl L. X. Fung, Carson K. Leung
, Pingzhao Hu
:
scGMM-VGAE: a Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data. Mach. Learn. Sci. Technol. 4(3): 35013 (2023) - 2022
- [j19]Jasper Zhongyuan Zhang, Wei Xu, Pingzhao Hu
:
Tightly integrated multiomics-based deep tensor survival model for time-to-event prediction. Bioinform. 38(12): 3259-3266 (2022) - [j18]Hamid Hadipour, Chengyou Liu
, Rebecca L. Davis, Silvia T. Cardona, Pingzhao Hu
:
Deep clustering of small molecules at large-scale via variational autoencoder embedding and K-means. BMC Bioinform. 23-S(4): 132 (2022) - [j17]Judah Zammit, Daryl L. X. Fung, Qian Liu, Carson Kai-Sang Leung
, Pingzhao Hu
:
Semi-supervised COVID-19 CT image segmentation using deep generative models. BMC Bioinform. 23(7): 343 (2022) - [j16]Yongye Su
, Qian Liu, Wentao Xie, Pingzhao Hu
:
YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms. Comput. Methods Programs Biomed. 221: 106903 (2022) - [j15]Qian Liu, Bowen Cheng, Yongwon Jin
, Pingzhao Hu:
Bayesian tensor factorization-drive breast cancer subtyping by integrating multi-omics data. J. Biomed. Informatics 125: 103958 (2022) - [j14]Chengyou Liu
, Andrew M. Hogan, Hunter Sturm, Mohd Wasif Khan, Md. Mohaiminul Islam, A. S. M. Zisanur Rahman
, Rebecca L. Davis, Silvia T. Cardona, Pingzhao Hu
:
Deep learning-driven prediction of drug mechanism of action from large-scale chemical-genetic interaction profiles. J. Cheminformatics 14(1): 12 (2022) - [j13]A. S. M. Zisanur Rahman
, Chengyou Liu
, Hunter Sturm, Andrew M. Hogan
, Rebecca L. Davis, Pingzhao Hu
, Silvia T. Cardona
:
A machine learning model trained on a high-throughput antibacterial screen increases the hit rate of drug discovery. PLoS Comput. Biol. 18(10): 1010613 (2022) - 2020
- [j12]Qian Liu
, Carson K. Leung
, Pingzhao Hu
:
A Two-Dimensional Sparse Matrix Profile DenseNet for COVID-19 Diagnosis Using Chest CT Images. IEEE Access 8: 213718-213728 (2020) - [j11]Zexuan Sun, Shujun Huang, Peiran Jiang, Pingzhao Hu
, Zhiyong Lu:
DTF: Deep Tensor Factorization for predicting anticancer drug synergy. Bioinform. 36(16): 4483-4489 (2020) - 2019
- [j10]Jiaying You, Robert D. McLeod, Pingzhao Hu
:
Predicting drug-target interaction network using deep learning model. Comput. Biol. Chem. 80: 90-101 (2019) - 2018
- [j9]Ryohei Eguchi, Mohammad Bozlul Karim, Pingzhao Hu
, Tetsuo Sato, Naoaki Ono, Shigehiko Kanaya, Md. Altaf-Ul-Amin:
An integrative network-based approach to identify novel disease genes and pathways: a case study in the context of inflammatory bowel disease. BMC Bioinform. 19(1): 264:1-264:12 (2018) - 2015
- [j8]Hui Jiang, Zhen-Yu Pan, Pingzhao Hu
:
Discriminative learning of generative models: large margin multinomial mixture models for document classification. Pattern Anal. Appl. 18(3): 535-551 (2015) - 2012
- [j7]Pingzhao Hu, Shelley B. Bull, Hui Jiang:
Gene network modular-based classification of microarray samples. BMC Bioinform. 13(S-10): S17 (2012) - 2010
- [j6]Pingzhao Hu
, Hui Jiang, Andrew Emili:
Predicting protein functions by relaxation labelling protein interaction network. BMC Bioinform. 11(S-1): 64 (2010) - 2009
- [j5]Pingzhao Hu
, Celia M. T. Greenwood
, Joseph Beyene:
Using the ratio of means as the effect size measure in combining results of microarray experiments. BMC Syst. Biol. 3: 106 (2009) - [j4]Ahmed Hossain
, Joseph Beyene, Andrew R. Willan, Pingzhao Hu
:
A flexible approximate likelihood ratio test for detecting differential expression in microarray data. Comput. Stat. Data Anal. 53(10): 3685-3695 (2009) - 2006
- [j3]Pingzhao Hu
, Celia M. T. Greenwood, Joseph Beyene:
Statistical Methods for Meta-Analysis of Microarray Data: A Comparative Study. Inf. Syst. Frontiers 8(1): 9-20 (2006) - 2005
- [j2]Pingzhao Hu
, Celia M. T. Greenwood
, Joseph Beyene:
Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models. BMC Bioinform. 6: 128 (2005) - 2002
- [j1]Pingzhao Hu
, Jim Pooler:
An empirical test of the competing destinations model. J. Geogr. Syst. 4(3): 301-323 (2002)
Conference and Workshop Papers
- 2023
- [c8]Wentao Xie
, Qian Liu
, Yongye Su
, Yi Yan
, Shujun Huang
, Qin Kuang
, Pingzhao Hu
:
Patch-based deep learning models for breast mammographic mass classification. ICBBT 2023: 13-22 - 2022
- [c7]Yan Sun, Md. Mohaiminul Islam, Ehsan Zahedi, Mélaine Kuenemann, Hassan Chouaib, Pingzhao Hu:
Molecular Property Prediction based on Bimodal Supervised Contrastive Learning. BIBM 2022: 394-397 - 2019
- [c6]Rayhan Shikder, Pourang Irani, Pingzhao Hu
:
Genome-Wide Canonical Correlation Analysis-Based Computational Methods for Mining Information from Microbiome and Gene Expression Data. Canadian AI 2019: 511-517 - [c5]Xinyu Hou
, Jiaying You, Pingzhao Hu
:
Predicting Drug-Drug Interactions Using Deep Neural Network. ICMLC 2019: 168-172 - 2018
- [c4]Jiaying You, Md. Mohaiminul Islam, Liam Grenier, Qin Kuang, Robert D. McLeod, Pingzhao Hu
:
Drug-Target Interaction Network Predictions for Drug Repurposing Using LASSO-Based Regularized Linear Classification Model. Canadian AI 2018: 272-278 - 2017
- [c3]Md. Mohaiminul Islam, Rasif Ajwad, Chen Chi, Michael Domaratzki
, Yang Wang, Pingzhao Hu
:
Somatic Copy Number Alteration-Based Prediction of Molecular Subtypes of Breast Cancer Using Deep Learning Model. Canadian AI 2017: 57-63 - 2011
- [c2]Pingzhao Hu
, Shelley B. Bull, Hui Jiang:
Gene Network Modules-Based Liner Discriminant Analysis of Microarray Gene Expression Data. ISBRA 2011: 286-296 - 2006
- [c1]Pingzhao Hu
, Celia M. T. Greenwood, Joseph Beyene:
Integrating Affymetrix microarray data sets using probe-level test statistic for predicting prostate cancer. CIBCB 2006: 1-8
Coauthor Index
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