Pingzhao Hu

发表

Discriminative learning of generative models: large margin multinomial mixture models for document classification

Hui Jiang, Zhen-Yu Pan, Pingzhao Hu, 2014, Pattern Analysis and Applications.

Incorporating Correlations among Gene Ontology Terms into Predicting Protein Functions

Hui Jiang, Pingzhao Hu, Andrew Emili, 2011 .

Deep Learning Models for Predicting Phenotypic Traits and Diseases from Omics Data

Yang Wang, Pingzhao Hu, Md. Mohaiminul Islam, 2018, Artificial Intelligence - Emerging Trends and Applications.

An empirical test of the competing destinations model

Pingzhao Hu, Jim Pooler, J. Pooler, 2002, J. Geogr. Syst..

Integrative Analysis of Gene Expression Data Including an Assessment of Pathway Enrichment for Predicting Prostate Cancer

Joseph Beyene, Pingzhao Hu, Celia M.T. Greenwood, 2006, Cancer informatics.

Somatic Copy Number Alteration-Based Prediction of Molecular Subtypes of Breast Cancer Using Deep Learning Model

Yang Wang, Michael Domaratzki, Chen Chi, 2017, Canadian Conference on AI.

Using the ratio of means as the effect size measure in combining results of microarray experiments

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2009, BMC Systems Biology.

Statistical Methods for Meta-Analysis of Microarray Data: A Comparative Study

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2006, Inf. Syst. Frontiers.

Integrating Affymetrix microarray data sets using probe-level test statistic for predicting prostate cancer

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Genome-Wide Canonical Correlation Analysis-Based Computational Methods for Mining Information from Microbiome and Gene Expression Data

Pourang Irani, Pingzhao Hu, Rayhan Shikder, 2019, Canadian Conference on AI.

Predicting protein functions by relaxation labelling protein interaction network

Hui Jiang, Pingzhao Hu, Andrew Emili, 2010, BMC Bioinformatics.

An integrative network-based approach to identify novel disease genes and pathways: a case study in the context of inflammatory bowel disease

Naoaki Ono, Pingzhao Hu, Shigehiko Kanaya, 2018, BMC Bioinformatics.

Gene network modular-based classification of microarray samples

Hui Jiang, Pingzhao Hu, Shelley B. Bull, 2012, BMC Bioinformatics.

Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models

Joseph Beyene, Pingzhao Hu, Celia M. T. Greenwood, 2005, BMC Bioinformatics.

A flexible approximate likelihood ratio test for detecting differential expression in microarray data

Joseph Beyene, Pingzhao Hu, Ahmed Hossain, 2009, Comput. Stat. Data Anal..

Drug-Target Interaction Network Predictions for Drug Repurposing Using LASSO-Based Regularized Linear Classification Model

Robert D. McLeod, Pingzhao Hu, Md. Mohaiminul Islam, 2018, Canadian Conference on AI.

Predicting intrusions with local linear models

Malcolm I. Heywood, Pingzhao Hu, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

SNVerGUI: a desktop tool for variant analysis of next-generation sequencing data

Wei Wang, Zhi Wei, Fang Hou, 2012, Journal of Medical Genetics.

Machine learning approaches for network-based prediction of disease outcomes and protein functions

Pingzhao Hu, 2012 .

Gene Network Modules-Based Liner Discriminant Analysis of Microarray Gene Expression Data

Hui Jiang, Pingzhao Hu, Shelley B. Bull, 2011, ISBRA.

Mapping three versions of the international classification of diseases to categories of chronic conditions

Mohammad Jafari Jozani, Pingzhao Hu, Lisa M. Lix, 2021, International journal of population data science.

Discovering MicroRNA-Regulatory Modules in Multi-Dimensional Cancer Genomic Data: A Survey of Computational Methods

Pingzhao Hu, P. Hu, C. Walsh, 2016, Cancer informatics.

Tests for differential gene expression using weights in oligonucleotide microarray experiments

Joseph Beyene, Pingzhao Hu, Celia MT Greenwood, 2006, BMC Genomics.

Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

Pingzhao Hu, P. Hu, C. Walsh, 2015, Microarrays.

A deep neural network based regression model for triglyceride concentrations prediction using epigenome-wide DNA methylation profiles

Yang Wang, Pingzhao Hu, Md. Mohaiminul Islam, 2018, BMC Proceedings.

Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival

Pingzhao Hu, P. Hu, Nikta Feizi, 2018, Front. Genet..

Ras Signaling Is a Key Determinant for Metastatic Dissemination and Poor Survival of Luminal Breast Cancer Patients.

Pingzhao Hu, Xue Mei, Sean E. Egan, 2015, Cancer research.

Prenatal Exposure to Maternal Cigarette Smoking and DNA Methylation: Epigenome-Wide Association in a Discovery Sample of Adolescents and Replication in an Independent Cohort at Birth through 17 Years of Age

Tom R. Gaunt, Zdenka Pausova, Pingzhao Hu, 2014, Environmental health perspectives.

Brain-expressed exons under purifying selection are enriched for de novo mutations in autism spectrum disorder

Daniele Merico, Pingzhao Hu, Christian R Marshall, 2014, Nature Genetics.

Association Analysis of Deep Genomic Features Extracted by Denoising Autoencoders in Breast Cancer

Qian Liu, Pingzhao Hu, P. Hu, 2019, Cancers.

A high-resolution copy-number variation resource for clinical and population genetics

Pingzhao Hu, John Wei, Christian R Marshall, 2014, Genetics in Medicine.

Computational prediction of cancer-gene function

Pingzhao Hu, Andrew Emili, Dennis A. Wigle, 2007, Nature Reviews Cancer.

Using a higher criticism statistic to detect modest effects in a genome-wide study of rheumatoid arthritis

Mathieu Lemire, David Tritchler, Elena Parkhomenko, 2009, BMC proceedings.