• Heidelberg

 

Organized by Heidelberg University, de.NBI Heidelberg Center for Human Bioinformatics (HD-HuB) and Core Facility Platform Mannheim (CFPM).

Educators:
Leonid Kostrykin (HD-HuB), Qi Gao (CFPM), Kerem Celikay (HD-HuB), Karl Rohr (HD-HuB)

Date:
3.8.2023 – 4.8.2023 
10:00-18:00 and 9:00-15:00

Location:
Heidelberg University
IPMB (Institute of Pharmacy and Molecular Biotechnology)
Im Neuenheimer Feld 364

Contents:
The course gives an introduction into the field of microscopy image analysis for cell biology and the use of software tools for automated processing of image data. Basic methods for computer-based analysis of microscopy images are introduced such as image preprocessing, segmentation, feature extraction, classification, and colocalization. Concepts of software platforms and workflow systems for automating image analysis pipelines with focus on ImageJ and Galaxy and their use for analyzing cell microscopy image data are also taught. The course consists of lectures and practical sessions. Participants should bring their laptops for the practical sessions. The target group are researchers with a background in biology or medicine that need to analyze their data and have little or no experience in automated image analysis.

Learning goals:
- Introduction into cell microscopy image analysis
- Application of software tools for automated analysis of image data

Prerequisites:
Basic knowledge in using software tools for image analysis is helpful but not mandatory 

Keywords:
Computer-based image analysis, image preprocessing, segmentation, feature extraction, classification, colocalization

Tools:
ImageJ, Galaxy

Registration closes on 3.7.2023.

The capacity is limited to 15 participants and applicants will be selected after registration closed. You will be notified of the outcome by e-mail on 10.7.2023.

Attendance is free of charge. No show or late cancellation without a proper reason and without informing the organizers is unfair to applicants not selected for participation. If cancellation is unavoidable (e.g., due to sickness), please send an email as earlier as possible to the contact address provided below.

Contact:
Leonid Kostrykin
This email address is being protected from spambots. You need JavaScript enabled to view it.

Registration:
https://forms.gle/x7YaAct71Ztt2YE87