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Department of Pathology and Molecular Medicine at Queen’s University.

Dr. M. Daria Haust Pathology Studentship

The Dr. M. Daria Haust Pathology Studentship funds one or two studentships for Queen’s medical students in the summer immediately after their first or second year of medical school. These students undertake research, clinical, or academic endeavours within the Department of Pathology and Molecular Medicine at Queen’s University.

Application Deadline: February 15, 2024.

haust2023.pdf

and a .doc application form

Applicationform-HaustSummerStudentship2023.docx

Cinq à Sept Research Talks - Dr. Sheth

Cinq à Sept Research Talks - Dr. Sheth

The Lowdown on the Showdown in Your Gut
Dr. Prameet Sheth (Associate Professor, Biomedical and Molecular Sciences)

As a microbiologist who studies infectious diseases, Dr. Prameet Sheth will give you the lowdown on our body’s bacteria and the crisis created by antibiotic overuse. Prepare for a gut check in this eye-opening talk about his discovery that has the potential to treat antibiotic-resistant bacterial infections.  

https://www.youtube.com/playlist?list=PLbVZkH5-hmmEGedb_smEs1H2NzFBZbQu5

 

grapical abstract v11

ScienceDirect publication: Renwick, Tyryshkin, Mousani

RNA-sequencing data can provide valuable insights into physiological and disease processes. However, the sheer size and noisy nature of sequencing data makes it challenging to analyze and find meaningful differences between groups. Traditional methods, like differential expression analysis require large sample sizes, rely on arbitrary significance thresholds, and struggle to model complex gene interactions. In contrast, machine learning overcomes these hurdles and can identify informative features (or genes) that best discriminate between sample groups. These features are then used to develop predictive models that can classify new data, such as in disease diagnosis or prognosis.

In our protocol, we provide a user-friendly approach for data preprocessing, exploration, feature selection, and creation of a hierarchical classification model. Accompanied by open-source code and an interactive ensemble feature selection app, our approach encourages users to explore their data and interpret results from a biological perspective. Requiring minimal programming experience, our protocol allows researchers from diverse backgrounds to apply machine learning in their work. Additionally, the protocol is not limited to RNA-sequencing data but can also be extended to other omics datasets (e.g. proteomics, metabolomics, microarray, etc.)!

The protocol will support researchers in identifying important markers from biomedical data, creating prediction models with clinical relevance, and guide hypothesis generation for future experimental work. For more information on this protocol, please see: https://www.sciencedirect.com/science/article/pii/S2666166723006287

Meet-the-Resident sessions

Dear CaRMS applicants:

Thank you for your interest in our program. 

You are invited to attend an informal Meet-the-Resident session with the Diagnostic and Molecular Pathology residents where you can get more information from a current resident’s perspective.  There will be two available dates and times and you are welcome to join one or both sessions.  Registration ahead of time is required.

When: Thursday, November 16, 2023 at 20:00 AND Sunday, November 19, 2023 at 14:00, Eastern Time (US and Canada)

To register in advance, please visit the CanPREPP Calendar of Events for the days specified above.

With your registration, you will receive a confirmation email with the information to join the meeting a few days prior to the event. 
Should you have any questions or concerns or if you have not received your confirmation within 24 hours of the event, please contact Micheline McDonald, Program Coordinator.

Wishing you every success with the CaRMS process.