- The Doctoral Programme in Biomedicine coordinates the course.
- This is an optional course.
- The course is part of the Field-Specific Studies module.
- The course is available to students of other degree programmes.
The course will cover high-content screening pipeline including imaging, image analysis and data processing. The course introduces the analysis of cell cultures using high-content screening and then focuses on image-based screening of hundreds of drugs in patient-derived cancer cells. The goal of the course is to teach the basics and demonstrate the capabilities of high-content screening to the students.
PhD students and MSc (if space). Lectures open for entire scientific community. In the spring term, the course is not organised annually.
The course includes one day symposium and two days of practical demonstrations
Monday 21.10, Biomedicum 1
High-Content Screening Symposium
Tuesday 22.10, FIMM Biomedicum 2U
High-content screening and QC practicals
09.00-10.00 Lecture, Cornelia Steinhauer, University of Copenhagen
10.00-10.15 Information about practicals and forming groups
10.15-10.45 Intro tour to the core units at FIMM
10.45-11.45 Optimization & automatization of cell seeding
11.45-12.45 Lunch break
12.45-13.30 Breeze and QC data analysis
13.30-16.00 Automated staining and microscopy imaging of multi-well plates (4 groups rotate, ~30min each demo) 1. Demo: Multi-well staining 2. Demo: Imaging with PE Opera Phenix high-content microscope 3. Demo: Imaging with Cytation5 4. Demo: Trouble-shooting session and Coffee
Wednesday 23.10, FIMM Biomedicum 2U
High-content image analysis
09.00-10.00 Lecture, Pekka Ruusuvuori, Tampere University
10.00-10.15 Intro to demos and forming groups
10.15-11.45 Image analysis demonstrations (4 groups rotate, ~45min each demo) 1. Demo: Image analysis using CellProfiler 2. Demo: Cell classification and regression with Advanced Cell Classifier 3. Demo: Image-based profiling using deep learning 4. Demo:
11.45-12.30 Lunch break
12.30-14.00 Demos continue
14.00-15.00 Visit to Aiforia, Machine learning image analysis service demo
Pass/fail, attendance required
Please note, participants will be selected to the course based on the information asked within the registration in WebOodi
Feedback form: https://elomake.helsinki.fi/lomakkeet/99648/lomake.html
The course will be organised as contact teaching (attendance required).