Methods in Cell Analysis and Laboratory Automation (Fall 2023)

In preparation for the course:

• Download and extract the complete course material → pc2023/
• Install Python following the instructions in pc2023/Python.pdf, chapter 1.2.
• Create the `iaf-env` conda environment following the instructions in pc2023/Python.pdf, chapter 1.4.

Please note: the zip file contains all needed material (with the exception of the homework). However, individual files can also be downloaded from the links below.

First day: Theoretical session (Room: BSS E 21)

• Quick and partial theoretical introduction to the main concepts of the course.
• Course text: pc2023/Theory.pdf.
• Couse slides: Theory_slides.pdf.

Second day: Practical session /I (Room: BSS E 21)

• Introduction to Python and the basics of Image Processing in Python.
• Course text: pc2023/Python.pdf, chapters 2 - 6.
• Code: pc2023/code/python.
• Analysis of data from a (fictitious) drug discovery study (part I: image processing).
• Assignment: pc2023/Analysis_Hands_On.pdf.
• Dataset: pc2023/data/hands-on/plate01.zip.

Third day: Practical session /II (Room: BSS E 21)

• Introduction to simple data analysis.
• Course text: pc2023/Python.pdf, chapters 7.
• Analysis of data from a (fictitious) drug discovery study (part II: data analysis).
• Assignment: pc2023/Analysis_Hands_On.pdf.
• Dataset: your results from the previous day.

Homework

• To successfully complete the Image Analysis Fundamentals course, you must solve and submit this homework for review.
• Dataset: U2OS.zip.
• In the assignment (section "Your submission"), you can find all information on submission deadline and how to upload your solution. Have fun!