Academic Calendar 2023-2024

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PATH 411 Applied Data Science in Molecular Medicine

PATH 411  Applied Data Science in Molecular Medicine  Units: 3.00  

The course introduces data science tools and methods to handle, process and extract knowledge and insights from large molecular medicine datasets. The focus will be on applying statistics, machine learning and related methods for the analysis of various research datasets and digital pathology.

Learning Hours: 120 (18L12pC, 84 Group Learning, 6 Online Activity, 36 Private Study)  
Requirements: Prerequisite BIOL 243/3.0 or ECON 250/3.0 or GPHY 247/3.0 or HSCI 190/3.0 or NURS 323/3.0 or POLS 285/3.0 or PSYC 202/3.0 or SOCY 211/3.0 or STAT 263/3.0 or STAM 200/3.0.  
Offering Faculty: Faculty of Health Sciences  

Pathology and Molecular Medicine

Pathology is a study of disease and the mechanisms leading to injury. It involves a wide range of biochemical, molecular, cellular and clinical approaches. Fields of interest in the department include: cancer biology, drug resistance, metastasis, programmed cell death and cell cycle regulation, transgenic mouse models of gene function, cell differentiation and gene regulation, hemostasis/thrombosis, amyloidosis and Alzheimer's disease, disturbances in protein synthesis, and human genetics (including human gene mapping). Detailed information on faculty research interests is presented in a brochure which is available on request. See also the Department of Pathology WEB Page: .

Pathology and Molecular Medicine (PATH)

PATH 822 Experimental Cancer Therapeutics Intended for students engaged or interested in pre-clinical cancer research. Both medical and basic science trainees are encouraged to take this course. Specific areas to be covered include introduction to new drug development, molecular basis of oncogenic transformation and signalling pathways, challenges with current cancer therapeutics, molecular approaches to profiling human cancers as tools for identifying biochemical and genetic abnormalities and developing criteria for reliable prognostic indicators; strategies for novel target and drug discovery, as well as experimental drug delivery; novel imaging approaches to enhance the sensitivity of preclinical testing and selection of responsive patients; preclinical (in vitro and animal) models for validating experimental targets; clinical drug development and testing of novel anti-cancer drugs; and the molecular basis for variability in tumour responses. Half course, lectures and seminars.  PREREQUISITES: Recommended courses: ANAT 311, BCHM 310, PHAR 340, MICR 360, PATH 310, CANC 440, or equivalents, or with permission of the department. The number of students may be restricted.