Faculty Member

Pingzhao Hu PhD,Statistical Genetics and Bioinformatics

Email Address(es)
pingzhao.hu(at)utoronto.ca
Website(s)
Lab Website: http://www.hu-bioinformaticslab.org
Curriculum Vitae
Download
Division(s)/Office
Biostatistics Division
Position
Assistant Professor
SGS Status
Associate Member
Appointment Status
Status Only

Research Interests

My research program focuses on developing and applying artificial intelligence (AI, e.g. novel deep learning tools) and large-scale statistical techniques for integrative analysis of big multimodal health data (omics data, imaging data, administrative and electronic medical records) for precision medicine. My group also collaborates very closely with local, national and international life science scientists and clinicians on different omics projects. Current PhD/MSc students’ thesis projects are in the research areas: radiogenomics, medical imaging, rare disease diagnosis using facial photos and phenotypes, drug discovery, microbiome, single cell RNA sequencing and omics data integration.

  • 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.

My lab also remotely hosts senior undergraduate students in genetics, mathematics, statistics and computer science from the University of Toronto.

Leadership in Professional Association

2018 August – 2020 June        Chair of Case Studies in Data Analysis Committee,                                                                               Statistical Society of Canada (SSC)

Honours & Awards

  • 2020 September, Terry G. Falconer Memorial Rh Institute Foundation Emerging Researcher Award (Interdisciplinary Category). The Winnipeg Rh Institute Foundation and University of Manitoba. The most prestigious award for junior faculty members at the University of Manitoba, which is awarded to the one who made Outstanding Contributions to Scholarship and Research in the Interdisciplinary Category in the University of Manitoba.
  • 2020 May, MMSF Allen Rouse Basic Science Career Development Research Award. The Manitoba Medical Service Foundation (MMSF).
  • 2019 March, Best Oral Presentation Paper Award (Corresponding author) in 2019 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 Grants

2017 May – 2023 Apr: Visual and Automated Disease Analytics (VADA), NSERC Collaborative Research and Training Experience (CREATE) Program

2020 Jul – 2022 Jun,  Manitoba-based breast cancer screening mammography using artificial intelligence, CancerCare Manitoba Foundation, Research Grant

2020 Feb – 2025 Feb: Identification of novel antibiotic molecules by chemogenetic analysis and machine learning, Canada Institutes of Health Research (CIHR), Project Grant Fall 2019

2020 Jan – 2023 Dec: Prediction and prevention of rheumatoid arthritis in First Nations people, CIHR Team grant: human immunology Initiative: Research Teams

2019 Sep – 2024 Aug:   EpiGen marks for human sepsis,  Canada Institutes of Health Research (CIHR), Project Grant Spring 2019

2018 Aug – 2023 Jul:  Role of taste signaling and host-microbial interactions on caries risk in young children, Canada Institutes of Health Research (CIHR), Project Grant Spring 2018

2018 Nov – 2020 Oct:   Antibiotic discovery for Burkholderia cepacia complex,
Cystic Fibrosis Foundation (CFF), USA, Pilot and Feasibility Awards – Spring Cycle

2019 Apr – 2022 Mar: Finding novel antibiotics against Burkholderia cepacia complex by genome-wide fitness and machine learning,
Cystic Fibrosis Canada, Basic and Clinical Research Grants

2015 Apr – 2021 Mar:
Developing novel machine learning algorithms for network Biology, Natural Sciences and Engineering Research Council of Canada, Discovery Grant

2020 Jan – 2020 Dec: Deep learning for prioritizing small molecule candidates for drug repositioning, Natural Sciences and Engineering Research Council of Canada, Engage Grant

Selected External Grant Reviews

2020 Jul-Aug                       Canadian Institute of Health Research (CIHR) – Project Grant: Spring 2020 Competition –Peer Reviewer and Member on the Genetics Committee.

2020 Mar – 2020 Apr           National Science Center, Poland, Review Panel for the Computer Science and Informatics.

2019 Nov – 2020 Jan            Juvenile Diabetes Research Foundation (JDRF), Review Panel for the Repositioning Drugs to Improve Metabolic Control in Established Type 1 Diabetes Competition, New York, USA

2019 Oct                             Florida Department of Health’s Ed & Ethel Moore Alzheimer’s Disease Research program, Oak Ridge Associated Universities, USA

2019 Jul                              Wellcome Trust / DBT Fellowship (1 Proposal). Note: This is a partnership between the Wellcome Trust (UK) and the Department of Biotechnology (Government of India).

2019 May-Jun                     Operating Grant, Deutsche Forschungsgemeinschaft (German Research Foundation), German.

2019 Dec – 2020 Jan           Individual Discovery Grant, Natural Sciences and Engineering Research Council (NSERC)

2019 Nov –Dec                    Expert Reviewer for John R. Evans Leaders Fund, Canada Foundation for Innovation (CFI)

2019 Aug                            Cancer Early Detection -2018/19 Competition, Alberta Cancer Foundation

2018 Aug-Sep                     Grand Challenges Canada Transition to Scale program, Round 8 and Canadian Institute of Health Research (CIHR)

2018 Aug                            Collaborative Research and Development Grant, Natural Sciences and Engineering Research Council (NSERC)

2018 Apr                             Scholar Program, The Michael Smith Foundation for Health Research (MSFHR)

2017 Oct –                           Canadian Institute of Health Research (CIHR) – 2017 Catalyst Grant: Personalized Health Catalyst Grants

2017 Feb                             Canadian Institute of Health Research (CIHR) – Project Grant Program 2016 Fall Competition

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. MM Islam, S Huang, R Ajwad, C Chi, Y Wang, P Hu (2020). An integrative deep learning framework for classifying molecular subtypes of breast cancer. Computational and Structural Biotechnology Journal. 18:2185-2199.
  2. Z Sun, S Huang, P Jiang, P Hu. (2020) DTF: Deep tensor factorization for predicting anticancer drug synergy. Bioinformatics. btaa287, https://doi.org/10.1093/bioinformatics/btaa287 [SRA]
  3. YW Jin, P Hu (2020). Tumor-Infiltrating CD8 T Cells Predict Clinical Breast Cancer Outcomes in Young Women. Cancers. 12:1076.
  4. P Jiang*, S Huang*, Z Sun, Z Fu, T Lakowski, P Hu. (2020) Deep graph embedding for prioritizing synergistic anticancer drug combinations. Computational and Structural Biotechnology Journal. 18:427-438 [SRA]
  5. VCruz de Jesus, R Shikder, D Oryniak, K Mann, A Alamri, BA Mittermuller, K Duan, P Hu**, RJ Schroth** and P Chelikani** (2020).Sex-based diverse plaque microbiota in children with severe caries. Journal of Dental Research. 99(6):703-712.
  6. S Frenkel, CN Bernstein, M Sargent, W Jiang, Q Kuang, W Xu, P Hu (2020). Copy number variation-based gene set analysis reveals cytokine signaling pathways associated with psychiatric comorbidity in patients with inflammatory bowel disease. Genomics, 112(1): 683-693.
  7. Q Liu, A Junker, K Murakami, P Hu (2019). Automated counting of cancer cell by ensembling deep features. Cells, 8:1019.
  8. 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.
  9. 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.
  10. 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.
  11. J You, R McLeod, P Hu (2019). Predicting drug-target interaction network using deep learning model. Computational Biology and Chemistry, 80:90-101.
  12. L Grenier, P Hu (2019). Computational drug repurposing for inflammatory bowel disease using genetic information. Computational and Structural Biotechnology Journal, 17: 127-135.
  13. 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.
  14. 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.
  15. 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.
  16. C Chi, LC Murphy, P Hu (2018). Recurrent copy number alterations in young women with breast cancer. Oncotarget, 9:11541-11558.
  17. 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.
  18. 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.
  19. 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. .
  20. 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.
  21. 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.
  22. P Hu, S Bull, H Jiang (2012). Gene network modular-based classification of microarray samples. BMC Bioinformatics13 (Suppl 10): S17.
  23. 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.
  24. 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.
  25. 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.
  26. P Hu, H Jiang, A Emili (2010). Predicting protein functions by relaxation labeling protein interaction network. BMC Bioinformatics 11(Suppl):S64.
  27. 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.
  28. 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.
  29. P Hu, G Bader, DA Wigle, A Emili (2007). Computational Prediction of cancer gene function. Nature Reviews Cancer 7:23-34.
  30. 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.
  31. P Hu, J Beyene, CMT Greenwood (2006). Testing for differential gene expression in oligonucleotide microarray experiments using weights. BMC Genomics 7:33.
  32. P Hu, CMT Greenwood, J Beyene (2005). Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models. BMC Bioinformatics 6:128.