Faculty Member

Pingzhao Hu PhD,Statistical Genetics and Bioinformatics

Email Address(es)
Lab Website: http://www.hu-bioinformaticslab.org
Curriculum Vitae
Biostatistics Division
Assistant Professor
SGS Status
Associate Member
Appointment Status
Status Only

Research Interests

  • Deep learning and visual analytics
  • Radiogenomics, medical imaging and electronic medical records
  • Genetic epidemiology and statistical genetics
  • Tensor-based multidimensional omics data integration
  • Machine Learning and big data science

We are looking for excellent candidates (MSc and PhD) to join our NSERC CREATE Graduate Training Program in Visual and Automated Disease Analytics (VADA).  The candidates should have strong backgrounds in computer science and/or (bio)statistics. The positions are fully funded. 

To apply for the positions, please send a CV, transcripts and related reports/publications written in English to Dr. Pingzhao Hu at pingzhao.hu@utoronto.ca or pingzhao.hu@umanitoba.ca. More details can be found at http://www.hu-bioinformaticslab.org/positions.html.

Leadership in Professional Association

2018 Aug – Present        Chair of Case Studies in Data Analysis Committee, Statistical Society of Canada

Honours & Awards

  • 2019 March, Best Oral Presentation Paper Award (Corresponding author) in2019 IEEE 7th International Conference on Bioinformatics and Computational Biology
  • 2019 February, Best Presentation Paper Award (Corresponding author) in 2019 11th International Conference on Machine Learning and Computing
  • 2018 May, The Interstellar Initiative Award by New York Academy of Sciences and Japan Agency for Medical Research and Development. The award recognizes “the world’s most promising Early Career Investigators in the fields of cancer, neuroscience and artificial intelligence”.
  • 2015 Jul, New Principal Investigator Award, Careers in Cancer Research Development Program by CIHR Institute of Cancer Research and Canadian Cancer Society Research The award recognizes the research excellence of new investigators in Canada.

Select Publications

* indicates co-first author or equal contribution and ** indicates co-corresponding author. Boldface underlined names are the HQP I supervised or co-supervised and boldface name is my name.

  1. S Frenkel, CN Bernstein, M Sargent, Q Kuang, W Jiang, J Wei, B Thiruvahindrapuram, B Spriggs, SW Scherer, P Hu (2019). Genome-wide analysis identifies rare copy number variations associated with inflammatory bowel disease. Plos One. In Press.
  2. S Frenkel, CN Bernstein, M Sargent, W Jiang, Q Kuang, W Xu, P Hu (2019). Copy number variation-based gene set analysis reveals cytokine signaling pathways associated with psychiatric comorbidity in patients with inflammatory bowel disease. Genomics, https://doi.org/10.1016/j.ygeno.2019.05.001.
  3. R Shikder, P Thulasiraman, P Irani, P Hu (2019). A openAM-based tool for finding longest common subsequence in bioinformatics. BMC Research Notes, 12:220.
  4. Q Liu, P Hu (2019). Association analysis of deep genomic features extracted by denoising autoencoders with breast cancer clinical outcomes. Cancers, 11:494; doi:10.3390/cancers11040494.
  5. J You, R McLeod, P Hu (2019). Predicting drug-target interaction network using deep learning model. Computational Biology and Chemistry, 80:90-101.
  6. L Grenier, P Hu (2019). Computational drug repurposing for inflammatory bowel disease using genetic information. Computational and Structural Biotechnology Journal, 17: 127-135.
  7. J Zhang, X Ye, C Wu, H Fu**, W Xu**, P Hu** (2019). Modelling gene-environment interaction for the risk of non-Hodgkin lymphoma. Frontiers in Oncology, 8:657. **Co-corresponding authors.
  8. L Zhang*, N Feizi*, C Chi, P Hu (2018). Association analysis of somatic copy number alteration burden with breast cancer survival. Frontiers in Genetics, 9:421. *Co-first author.
  9. Y Chen, C Monteiro, A Matos, J You, A Fraga, C Pereira, V Catalán, A Rodríguez, J Gómez-Ambrosi, G Frühbeck, R Ribeiro**, P Hu** (2018). Epigenome-wide DNA methylation profiling of periprostatic adipose tissue in prostate cancer patients with excess adiposity – a pilot study. Clinical Epigenetics, 10:54. **Co-corresponding authors.
  10. C Chi, LC Murphy, P Hu (2018). Recurrent copy number alterations in young women with breast cancer. Oncotarget, 9:11541-11558.
  11. PC Havugimana*, P Hu*, A Emili (2017). Protein complexes: big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks. Expert Review of Proteomics, 14:845-855. *Co-first author.
  12. MM Islam*, Y Tian*, Y Chen, Y Wang, P Hu. A deep learning regression model for phenotype prediction based on GAW20 genome-wide DNA methylation data. Genetic Analysis Workshop (GAW) 20. San Diego, CA, USA, March 2017. BMC Proceedings, 12(Suppl 9):21. *Co-first author.
  13. C Chi, R Ajwad, Q Kuang, P Hu (2016). A graph-based algorithm for detecting recurrent copy number variants in cancer studies. Cancer Informatics, Suppl2: 43-50. .
  14. P Hu, AD Paterson (2014). Dynamic pathway analysis of genes associated with blood pressure using whole genome sequence data. BMC Proceedings 8(Suppl 1): S106. Special issue of Genetic Analysis Workshop (GAW18), Stevenson, WA, USA, October 2012.
  15. P Hu*, X Wang*, JJ Haitsma, S Furmli, H Masoom, M Liu, AS Slutsky, J Beyene, CM Greenwood, CC dos Santos (2012). Microarray meta-analysis identifies acute lung injury biomarkers in donor lungs that predict development of primary graft failure in recipients. Plos One 7:e45506.
  16. P Hu, S Bull, H Jiang (2012). Gene network modular-based classification of microarray samples. BMC Bioinformatics13 (Suppl 10): S17.
  17. W Wang, W Hu, F Hou, P Hu, Z Wei (2012). SNVerGUI: A desktop tool for variant analysis of next-generation sequencing data. Journal of Medical Genetics 12:753-755.
  18. PC Havugimana*, GT Hart*, T Nepusz*, H Yang*, AL Turinsky, Z Li, PI Wang,, DR Boutz, V Fong , S Phanse, M Babu, SA Craig, P Hu, C Wan, J Vlasblom, V Dar, A Bezginov, GW Clark, GC Wu, SJ Wodak, ERM Tillier, A Paccanaro, EM Marcotte, A Emili (2012). A census of human soluble protein complexes. Cell 150:1068-1081.
  19. Z Wei, W Wang, P Hu, GJ Lyon, H Hakonarson (2011). SNVer: a statistical tool for variant calling in analysis of pooling or individual next-generation sequencing data. Nucleic Acids Research 39:e132.
  20. P Hu, H Jiang, A Emili (2010). Predicting protein functions by relaxation labeling protein interaction network. BMC Bioinformatics 11(Suppl):S64.
  21. P Hu, CMT Greenwood, J Beyene (2009). Using the ratio of means as the effect size measure in combining results of microarray experiments. BMC System Biology 3:106.
  22. P Hu*, SC Janga*, M Babu*, JJ Diaz-Mejia*, G Butland*, W Yang, O Pogoutse, X Guo, S Phanse, P Wong, S Chandran, C Christopoulos, A Nazarians-Armavil, NK Nasseri, G Musso, M Ali, N Nazemof, V Eroukova, A Golshni, A Paccanaro, JF Greenblatt, G Moreno-Hagelseib, A Emili (2009). Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins. PLoS Biology 7:e96.
  23. P Hu, G Bader, DA Wigle, A Emili (2007). Computational Prediction of cancer gene function. Nature Reviews Cancer 7:23-34.
  24. T Kislinger*, B Cox*, A Kannan*, C Chung, P Hu, A Ignatchenko, MS Scott, A Gramolini, Q Morris, T Hughes, J Rossant, B Frey, A Emili (2006). Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling. Cell 125:173-186.
  25. P Hu, J Beyene, CMT Greenwood (2006). Testing for differential gene expression in oligonucleotide microarray experiments using weights. BMC Genomics 7:33.
  26. P Hu, CMT Greenwood, J Beyene (2005). Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models. BMC Bioinformatics 6:128.