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Feel free to use these slides and their content for any purpose under the cc-by license. 

Caveats regarding course and slide content:

  1. I am preparing slides on a week-to-week "survival mode". The class material and slides are not polished and will be improved next (and the following) years...

  2. Topic selection is biased toward my personal interests (and research).

  3. Some slides are reflecting my personal views that might be controversial/provocative. Happy to debate :-) 

  4. I am reaching out to researchers for slides and integrate them into my presentations. This means that some of the topics are heavily biased toward the work from specific labs. I plan to improve this aspect in future rounds of the course. Please reach out if you have a topic / specific research paper/s to suggest for the course. 

Course slides:

Lecture 1: Course overview 

Lecture 2: Cell biology & microscopy. Guest lecture by Natalie Elia 

Lecture 3: Typical challenges in image analysis. Guest lecture by Jean-Yves Tinevez 

Lecture 4: Deep learning in microscopy

Lecture 5: Deep learning in microscopy

Lecture 6: Image-based high content cell phenotyping 

Lecture 7: Image-based high content cell phenotyping

Lecture 8: Image-based high content cell phenotyping

Lecture 9: Computer vision in cell imaging. Guest lecture by Tammy Riklin-Raviv

Lecture 10: Information processing in multicellular systems 

Lecture 11: Importing ideas from systems biology. Guest lecture by Tal Shay

Lecture 12: Integrating microscopy and omics. Guest lecture by Paul Villoutreix

Lecture 13: Summary and atlases, public data repositories, and data reuse

Course video recordings are publicly available here

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