Experts

Dr. Zovoilis is since January 2024 an Associate Professor of Bioinformatics at the Department of Biochemistry and Medical Genetics at the University of Manitoba and a senior scientist at the Paul Albrechtsen Research Institute at CCMB. Dr Zovoilis holds a doctorate from the University of Goettingen (Germany), postgraduate training in bioinformatics from the University of Manchester (UK), and expertise in bioinformatics of next generation sequencing from his time as research fellow at Vancouver Genome Sciences Centre (Canada), a research fellow at Harvard Medical School (USA), a Canada Research Chair in RNA Bioinformatics and Genomics at the University of Lethbridge and the director of its bioinformatics core facility. He has been the founding director of the Southern Alberta Genome Sciences Center (SAGSC) and also the academic lead of the Alberta Bioinformatics Network (BioNet), and currently of its successor, the Bioinformatics Network (BioNet) Prairie. He is the director of the Bioinformatics Platform at Cancer Care Manitoba Research Institute and co-director of the Statistical Genomics and Bioinformatics Platform at the Rady Faculty of Health Sciences at the University of Manitoba. Dr. Zovoilis’ research combines translational research in medicine, in particular aging associated diseases such as cancer and dementia, with basic research in bioinformatics. His expertise in bioinformatics of next-generation sequencing (NGS) is demonstrated by multiple leading or senior author scientific publications in distinguished journals such as Cell, Science, Elife, PNAS and EMBO Reports. Being the Academic Lead of BioNet Prairie, he works to foster research collaborations and partnerships in the fields of bioinformatics and computational biology in the prairie provinces and across Canada.

Themes Symbiotic bacteria and fungi Genome and gene evolution Bioinformatics, Genomics, Transcriptomics and Proteomics SYMBIOTIC BACTERIA AND FUNGI Multicellular organisms like plants and animals frequently interact with symbiotic microbes. They range from beneficial to pathogenic, and may live within tissues, within cells, or be in external contact. We are particularly interested in beneficial plant symbionts, to understand how they cooperate with their host, by sequencing and analyzing their genomes, transcriptomes and proteomes. This project is far-reaching for sustainable agriculture – replacement of agrochemicals by bio-pesticides, and mineral fertilizers by biofertilization. GENOME AND GENE EVOLUTION Understanding genome architecture, gene content and gene expression – in an evolutionary context – is the basis for understanding living organisms. We are interested in a wide range of bacteria, fungi and unicellular eukaryotes, in particular plant symbiotic species, and primitive eukaryotes that allow tracing back the origin of eukaryotes. Our comparative genomics approach regularly permits to identify innovative molecular mechanisms, such as RNA editing, trans-splicing or ribosomal hopping. BIOINFORMATICS TOOLS FOR GENOME ANALYSIS We are developing bioinformatics approaches for genome assembly, gene finding and functional annotation. Our research is multi-disciplinary, based on national and international collaborations.

Dr. Benjamin Haibe-Kains is a Senior Scientist at the Princess Margaret Cancer Centre (PM), University Health Network, and Professor in the Medical Biophysics Department of the University of Toronto. Dr. Haibe-Kains earned his PhD in Bioinformatics at the Université Libre de Bruxelles (Belgium). Supported by a Fulbright Award, he did his postdoctoral fellowship at the Dana-Farber Cancer Institute and Harvard School of Public Health (USA). He is now the Canada Research Chair in Computational Pharmacogenomics and the Scientific Director of the Cancer Digital Intelligence Program at PM. Dr. Haibe-Kains’ research focuses on the integration of high-throughput data from various sources to simultaneously analyze multiple facets of carcinogenesis. Dr. Haibe-Kains’ team analyzes large-scale radiological and (pharmaco)genomic datasets to develop new prognostic and predictive models to improve cancer care.

University of Munich School of Medicine (1978-1985); Max-Planck Institute for Biochemistry (1985-1994); Gene Center of the University of Munich (1995-2001); University of Toronto (since 2001). I wish to understand complexity in adaptive systems. Complexity arises from the context dependent behaviour of system components, and in biochemistry we observe it in the hierarchies of structure formation, and the generation of function, across molecular, cellular and organismal scales. Recent scholarly work (since 2017, with Yi CHEN) has focussed on complexity in human relationality, ethics and aesthetics. Most recently (2022) I have founded the “Sentient Syllabus Project” as an international, public-good collaborative to address how academia can re-imagine itself in the face of our new wave of Artificial Intelligence capabilities. My teaching focuses on inquiry.

Brian Fristensky attended the College of Arts and Sciences at Cornell University, where he completed his A.B. in Biology in 1980. After graduation he worked as a technician with Dr. Ray Wu. where he authored the Cornell Sequence Analysis Package, one of the first packages of sequence programs. In 1982 he joined the lab of Lee Hadwiger at Washington State University, in one of the first attempts to clone plant defense genes. In 1987 he was awarded his Ph.D. in Genetics and Cell Biology. On a postdoctoral fellowship from the North Carolina Biotechnology Center, he worked on light­ regu­lated gene expression with Dr. William F. Thompson at North Carolina State University. In 1990 he joined the University of Manitoba Plant Science Department, where he is currently an Associate Professor. Publications topics include disease resistance in plants, genetic engineering of disease resistance, machine learning and bioinformatics software.

Our research interests are in the area of bioinformatics, molecular evolution and DNA sequence analysis. Our research attempts to understand how the processes of evolution act to cause the changes observed between molecules, between genes and between genomes. The recent advances in molecular genetics provide a storm of new data on DNA sequences, on gene structure and higher order genomic structure. However, the implications of these new data are not always clear.

Cancer genomics researcher working on pediatric leukemia.

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.

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.

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.