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CMPT 984 G100 Special Topics in Databases, Data Mining, Computational Biology

Graduate Studies and Professional Development
Professor / Instructor
Ester, Martin; Libbrecht, Maxwell
Sept 10 - Dec 7, 2021

This course introduces machine learning methods for the life-sciences, focusing on molecular-level data, in particular genomic data. Such data plays a crucial role in precision medicine, e.g. drug response prediction, and in public health, e.g. the tracking of infectious diseases. However, genomic data poses special challenges to machine learning, due to the small number of examples (e.g. patients with clinical information) and great complexity of every example (e.g., SNP, CNV, RNA-seq, omics). The instructors will start the course with a few tutorial-style introductions of foundations. Students will prepare and give presentations on a state-of-the-art research paper. Students will, in small groups, perform a course research project in which they reproduce and extend the results of a recent paper from one of the four given focus areas (see the Topics below). In the last phase of the course, students will present the results of their projects. General guidelines and strategies for writing clearly and giving good talks will be given, and students will receive constructive feedback on their presentations and project reports from the instructor and other students.

You are applying for a $500 scholarship towards a qualifying course at one of our post-secondary education partners: BCIT, Northeastern University, SFU or UBC. Applicants must be either Canadian Citizens, BC permanent residents or working towards obtaining one of these.

Please only apply for this scholarship once you have been enrolled or waitlisted in an applicable course. We will be confirming all student details with instructors.

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To be eligible for this scholarship, you must be a woman (or identify as a woman), and currently live in BC, Canada. Do you meet both of these criteria?