Courses for PhD students by Core Facilities

The course includes a combination of lectures and practical sessions that introduce the analysis of genomic and proteomic data using bioinformatics tools and public databases (such as NCBI, UCSC and ENSEMBL). It covers DNA sequence alignment, protein expression analysis and pathway analyses.

• Syllabus for Bioinformatics I (en)
• Syllabus for Bioinformatics I (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Arranged by Bioinformatics and Data Centre

The course gives basic theoretical and practical knowledge about the culturing of cells and some different applications. The course is run once every year, usually in the fall. 

Course syllabus

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Arranged by: Mammalian Protein Expression

This graduate course provides an in-depth introduction to modern cellular and molecular microscopy techniques, essential for life science research. Through lectures, group discussions, and live demonstrations, participants will explore fundamental and advanced imaging methods, including fluorescence microscopy (widefield, confocal, multiphoton, high-content screening, and lightsheet), live-cell imaging, super-resolution techniques (SIM, SMLM, STED), electron microscopy (SEM/TEM), and laser capture microdissection. The course also covers sample preparation strategies, equipping students with both theoretical knowledge and practical insights into cutting-edge microscopy applications. Organized by the Centre for Cellular Imaging, Sahlgrenska Academy, University of Gothenburg.

• Course syllabus (en)
• Course syllabus (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Arranged by: Centre for cellular imaging 

The course includes a combination of lectures and practical sessions that introduces proper programming practices to ensure reproducibility, portability, scalability and automation of data analysis processes.

• Syllabus for Programing Practices and Reproducible Code (en)
• Syllabus for Programing Practices and Reproducible Code (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Notes

• The course comprises 54 working hours where you are expected to spend time of your own to complete the exercises (self-studies).
• Participants are required to bring their own computer with the corresponding administrator rights.
• You must have basic experience in the command line or have passed the Unix applied to genomic data (SC00036) course.

Arranged by: Bioinformatics and Data Centre

This full-time two-weeks course explores current trends in proteomics and demonstrates the principles and capabilities of proteomic strategies. It provides an overview of applications and workflows, from study design, experiment planning and sample preparation to MS-analysis and bioinformatic evaluation of results. The course includes lectures, instrument demonstrations, workshops, and hands-on laboratory experiments.

• Course syllabus (en)
• Course syllabus (sv)

Once this full-time course is open for application, you will find practical information and details on requirements, selection as well as how and when to apply on the course portal.

Link to the FUBAS portal above to the right. 

Arranged by Proteomics Core Facility (PCF)

The course covers the basics in R programming, a language and environment for statistical computing and graphics. The course includes a combination of lectures and computer exercises focused on visualization and statistical analysis. No prior knowledge is required.

• Syllabus for R programming (en)
• Syllabus for R programming (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Notes

• This course is a pre-requisite to take Gene expression analysis using R 

• This course is recommended when taking the Analysis of Next Generation Sequencing course.

Arranged by: Bioinformatics and Data Centre

The course includes a combination of lectures, group discussions and computer exercises. Participants are directly performing the analyses of gene expression data from different applications. We focus on developing practical skills; therefore, you need to have experience in R programming.

• Syllabus for Gene expression analysis using R (en)
• Syllabus for Gene expression analysis using R (sv)

   

• Once this full-time course is open for application, you will find practical information and details on requirements, selection as well as how and when to apply on the course portal.

  Link to the FUBAS portal above to the right. 

The course covers the basics in Unix and how to work in the command line to aid in the analysis of large amounts of data and automate such tasks. The course includes a combination of lectures and practical exercises focused on handling genomic data. No prior knowledge is required.

• Syllabus for Unix applied to genomic data (en)
• Syllabus for Unix applied to genomic data (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Notes

• The course comprises 54 working hours, and you are expected to spend time on your own to complete the exercises (self-studies).

• Participants are required to bring their own computer with the corresponding administrator rights

• This course is a pre-requisite to take Analysis of next generation sequencing data course.

Arranged by Bioinformatics and Data Centre

The course includes a combination of lectures and practical sessions to introduce Python as a tool for handling large datasets. No prior Python knowledge is required; however Unix experience is highly recommended.

• Syllabus for Python for biologists (en)
• Syllabus for Python for biologists (sv)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Arranged by Bioinformtics and Data Centre

The course includes a combination of lectures and practical sessions where participants are directly performing bioinformatics analysis of NGS data. From raw data (fastq files) to variant analysis (DNA sequencing), differential gene expression analysis (RNA sequencing) and pathway analysis. We focus on developing practical skills; therefore, you need to have experience in the Linux environment. Experience in R is not mandatory but recommended.

• Syllabus for Analysis of NGS data (en)
• Syllabus for Analysis of NGS data (sv)

Once this course is open for application, you will find practical information and details on requirements, selection as well as how and when to apply on the course portal.

Link to the FUBAS portal above to the right. 

This hands-on course provides a comprehensive introduction to image processing and analysis, focusing on biologically relevant microscopy data, including fluorescence and electron microscopy images. Participants will gain a broad understanding of digital image concepts, fundamental image analysis methods, and the algorithms behind them. Through practical exercises using FIJI (ImageJ2), the course covers essential topics such as image visualization, noise reduction, segmentation, object tracking, and automated analysis of large datasets. Key aspects of image ethics and proper acquisition for analysis are also addressed. Additionally, students will learn to write macros in FIJI and work with data output in Python for basic analysis and visualization. Organized by the Centre for Cellular Imaging, Sahlgrenska Academy, University of Gothenburg.

• Course syllabus (en)

Once this course is open for application next you will find practical information and details on requirements, selection as well as how and when to apply on the course portal. Link to the FUBAS portal above to the right.

Notes:

No computer is required, the course is given in a computer room at Medicinaregatan.

Arranged by Centre for Cellular Imaging