People

Aaron Petkau is a bioinformatician working for the Public Health Agency of Canada’s National Microbiology Laboratory and the current Head of Bioinformatics Pipeline Development within the Bioinformatics unit of the laboratory. His work primarily focuses on the development of bioinformatics software for infectious disease genomics. Some of his projects have included: developing tools for comparative genomics (GView and GView Server), phylogenetic analysis of microbial genomes (SNVPhyl), the management of genomics data (IRIDA), and indexing, querying, and visualization of mutations or genes derived from collections of microbial genomes (Genomics Data Index). He is currently focused on the development and integration of a diverse set of bioinformatics pipelines into a larger system for routine use within the Public Health Agency of Canada.

Dr. Alan Moses is a Professor in the Department of Cell and Systems Biology and Computer Science. He completed his Bachelor’s degree at Columbia University and his Ph.D. at the University of California, Berkeley. The Moses Lab seeks to understand how are regulatory networks are encoded in genome sequences. One of the important components of this ‘regulatory code’ has been discovered: ‘regulatory motifs’ in the sequences of DNA, RNA and proteins. One of the major aims of their research is to develop computational and statistical tools to identify these motifs. Just as differential gene activity can explain cellular and physiological diversity within a single organism (nerve cell vs. white blood cell with same genes), it has also been proposed as explanation for physiological and morphological differences between closely related organisms (chimpanzee vs. human with very similar genes). They seek to understand how regulatory networks are sculpted by evolution. They focus on the evolution of regulatory motifs because, by mediating the regulatory interactions, they specify the connections in regulatory networks. Their goal is to translate the evolutionary differences in regulatory motifs to quantitative differences in regulatory networks, and ultimately, to their impact on organismal fitness. In 2015, Dr. Moses was awarded as Canada Research Chair in Computational Biology, which was renewed in 2020.

Alexandre Reynaud obtained a PhD in Neurosciences from Aix-Marseille Université (France) and a MSc in Computer Sciences from Université de Nice Sophia-Antipolis (France). His research focuses on human visual perception and particularly binocular vision. To study those, he develops computer-based psychophysics, behavioral experiments. His research also focuses on a more clinical/translational aspect: the study of amblyopia, a neurodevelopmental condition which emerges during childhood and results in deficit of binocular vision. He tries to understand and develop treatments for this condition based on digital technologies and digital therapies. 

Ali Bashashati’s research area lies at the interface between computational, engineering and biomedical sciences. He is interested in developing machine learning, signal processing algorithms and software infrastructure to combine various sources of omics and imaging data. He has published extensively in cancer genomics, computational pathology, bioinformatics and computational biology and his papers have appeared in top-tier journals such as Nature, Nature Genetics, Nature Communications, and Nature Medicine.

Dr. Aline Talhouk is an assistant professor in the Department of Obstetrics and Gynecology in the Faculty of Medicine at the University of British Columbia (UBC). Dr. Talhouk holds a Ph.D. from UBC and has expertise in computational statistics and machine learning, specifically focusing on developing and implementing predictive models in women’s health and oncology. Her research leverages statistical computing, machine learning and artificial intelligence to translate -omics discoveries into clinical applications and bring individualized care to ovarian and endometrial cancer patients. Dr. Talhouk has also developed a nationally-funded precision prevention program that uses prediction modelling to identify those at high risk for uterine cancer and direct them to risk-reducing interventions, targeted screening and surveillance. Dr. Talhouk is a Michael Smith Health Research BC Scholar and holds several grants from the Canadian Institutes of Health Research, the Canada Foundation for Innovation and the Canadian Cancer Society.

Her research is focused on understanding intratumoral heterogeneity, tumor evolution, and the tumor microenvironment at single cell resolution. She uses computational approaches to analyze, integrate, and interpret large-scale genomic data, with an emphasis on single-cell RNA-sequencing data. She completed a PhD in Genetics in the laboratory of George Church at Harvard Medical School, and a postdoctoral fellowship in Systems Biology with David Botstein at Princeton University. She was Research Faculty under the mentorship of Tim Ley at Washington University and the McDonnell Genome Institute.

Almas is a PhD student in the Medical Biophysics program at the University of Toronto.She is investigating spatial diversity across cancer. Prior to starting at U of T, she completed her Bachelor of Science in Microbiology and Immunology and her Master of Science in Bioinformatics from the University of British Columbia in Vancouver. For her MSc thesis, Almas worked on investigating and correcting for the technical, clinical and biological contributors to variation in placental methylation.

Alysha Cooper is a current PhD candidate in Applied Statistics at the University of Guelph, with her research focusing on optimization of multivariate count outcome models for gut microbiome analyses. Before pursuing her doctoral studies, she gained valuable experience as a data analyst at the Homewood Research Institute in Guelph, ON. Alysha continues to work within the field of mental health and addictions as a part-time data analyst at the Peter Boris Center for Addictions Research in Hamilton, ON.

Amin is a bioinformatician and a PhD student in Dr. Mitchell’s lab in the Department of Cell and Systems Biology at the University of Toronto, focusing on enhancer logic, chromatin accessibility, and 3D genome organization. He uses Python and R to develop computational frameworks that integrate single-cell and bulk epigenomic data, aiming to uncover how genome architecture regulates gene expression. His research is focused on analyzing enhancer-promoter interactions and their role in controlling cell identity during development and disease.