People

My group’s research focuses on the regulation of gene expression, which is fundamental to our efforts to understand and engineer biological systems, and is a critical aspect of nearly every disease. Our research includes DNA synthesis and omics technology development, algorithm and computer model design, and drug design and discovery.

Dr. Carolina Tropini is an Assistant Professor at UBC in the Department of Microbiology and Immunology, and School of Biomedical Engineering. She is recognized as a Paul Allen Distinguished Investigator and, in 2020, became the first Canadian to receive the Johnson & Johnson Women in STEM2D Scholar award in Engineering. She’s the inaugural Alan Bernstein CIFAR Fellow in the Humans & the Microbiome Program and a Michael Smith Foundation for Health Research Scholar. In 2019, she was selected as a CIFAR Azrieli Global Scholar. Her lab explores the impact of disrupted physical environments, like altered nutrition or intestinal diseases, on microbiota and hosts across multiple scales. This cross-disciplinary team integrates microbiology, bioengineering, and biophysics to study bacterial and microbial community functions, aiming to enhance human health. Dr. Tropini completed her Ph.D. in Biophysics at Stanford University, where she combined computational and experimental methods to study bacterial mechanics and morphogenesis. As a postdoc in Dr. Justin Sonnenburg’s lab at Stanford, she focused on the effects of physical disruptions on gut-associated microbial communities, supported by a James S. McDonnell Foundation Postdoctoral Fellowship Award.

Caryn Geady is a graduate researcher specializing in quantitative imaging and data science. With a Bachelor’s degree in Physics (Medical Physics and Imaging) from Toronto Metropolitan University (TMU) and a Master’s degree in Medical Biophysics from the University of Toronto (UofT), she brings a strong foundation in both theoretical and practical aspects of medical imaging. Caryn is passionate about teaching, having helped launch Supported Learning Groups at TMU to aid students in mastering challenging course concepts. Currently pursuing a Ph.D. at UofT, her research focuses on machine learning techniques for assessing treatment response in advanced cancers.

Ce Zhang is a Ph.D. student in the Department of Mathematical and Statistical Sciences at the University of Alberta, majoring in Statistics. He is co-supervised by Prof. Linglong Kong and Prof. Bei Jiang. His research focuses on constructing efficient prediction bands, with particular interests in differential privacy, transfer learning and subsampling methods.

My research involves developing, improving and applying statistical methods for genetic, genomic and high dimensional data. My over 200 publications include both theoretical developments and applied collaborative projects, collectively cited over 18,000 times. I am Senior Investigator at the Lady Davis Institute for Medical Research (www.ladydavis.ca). At McGill University, I hold a James McGill Professorship, I am co-Director of the Ludmer Centre for Neuroinformatics and Mental Health (ludmercentre.ca), and also the inaugural and current Graduate Program Director of the interdisciplinary PhD in Quantitative Life Sciences (www.mcgill.ca/qls). I am a former president of the International Genetic Epidemiology Society (www.geneticepi.org) and received their Leadership Award in 2022.

Dr. Chad Laing is a Research Scientist and the Head of Bacteriology Research at the National Centre for Animal Diseases, Lethbridge Laboratory, within the Canadian Food Inspection Agency. His research focuses on predictive genomics of bacterial pathogens to improve the health of animals and humans, as well as the safety and security of Canadians. He has dealt extensively with molecular biology, bacterial genomics, bioinformatics, machine learning, and software development. His current research focuses on combining large-scale genomic and metagenomic sequencing with machine learning to enable more rapid identification and characterization of microbial pathogens, including antimicrobial resistance and virulence. He has supervised many graduate and undergraduate students, and is an adjunct professor in the Department of Biological Sciences at the University of Lethbridge.

Chaitra is a computational biologist with experience in software development. During her PhD, she applied mathematical modelling, network analysis and multi-omics integration to study complex diseases. She has contributed to open-source toolboxes (openCOBRA) and developed softwares (EFMviz & ComMet) to analyse genome-scale metabolic models. She currently works in the Bader lab’s MODiL team (Multi Omics Data Integration and Analysis) and with groups at PMCC, where she develops pipelines to analyse various omics data types and discover new drug targets in cancer.

I’m an Assistant Professor in the Division of Oncology, where my focus is on developing and applying computational tools to provide insight into the origins and progression of cancer. I earned Bachelor degrees in Biology and Computer Science from Truman State University and my PhD in Computational Biology from Baylor College of Medicine. My core research interests include understanding the clonal architecture of tumors and how they evolve in response to therapy, with a special focus on hematologic cancers. I also study effective design and targeting of cancer immunotherapies, developing open-source software for interpreting and visualizing genomic data, and integrative analysis that translates multi-dimensional genomic data into both functional and actionable contexts.

Through the computational analysis of genome-wide data, we aim to elucidate mechanisms regulating transcription and RNA processing, their interplay with genetic and epigenetic factors, and how they cause disease. Our main focus is on cancer and brain development, two areas where regulation of gene expression plays a major role, and where unprecedented amounts of data are being produced. Key components of our research are (a) the development of novel strategies to integrate genomic, epigenomic and transcriptomic data across species and disease models, (b) the modeling of dynamic changes over normal cellular differentiation to guide interpretation of disease data, and (c) the use of single-cell technologies to resolve cell-to-cell variation, identify rare cells driving disease progression, and define the effect of the microenvironment in molecular phenotypes.

David works in Guillaume Bourque’s lab on software solutions in bioinformatics for organizing, visualizing and analyzing datasets produced by large-scale projects such as the International Human Epigenome Consortium (IHEC), which maps human epigenomes for a broad spectrum of cell types and diseases. He is also involved in the development of GenAP, a platform that leverages Compute Canada infrastructure to make bioinformatics analysis more accessible to non-bioinformaticians, and reduces data processing bottlenecks.

David S. Guttman is a Professor in the University of Toronto Department of Cell & Systems Biology and Director of the Centre for the Analysis of Genome Evolution & Function. His research focuses on deciphering how bacteria adapt to and manipulate their hosts, emphasizing the evolution of bacterial host specificity and virulence and the dual role of secreted pathogen effectors as both virulence factors and immune elicitors. His group is particularly fascinated by the scope and impact of natural genetic diversity on these host-microbe interactions. The Guttman lab uses a multidisciplinary approach that harnesses comparative and evolutionary genomics, genetics, molecular biology, microbiology, plant biology, pathology, bioinformatics, and statistical genetics to gain insight into how pathogen evolution influences the outcome of host-pathogen interactions.