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Feel free to use these slides and their content for any purpose under the cc-by license.
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Caveats regarding course and slide content:
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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...
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Topic selection is biased toward my personal interests (and research).
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Some slides are reflecting my personal views that might be controversial/provocative. Happy to debate :-)
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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.
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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
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Course video recordings are publicly available here
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