This is a five weeks course for students and other life scientists who are just starting with bioinformatics.
Prerequisites for this course: Although not required, familiarity with python or a coding language is recommended. Participants should bring laptops with working terminals.
Please fill the questionnaire here as soon as possible.
Please follow the steps in the Preparation Page before the course starts.
We’ll start by exploring the most used bioinformatics resources for variety of different data sets, continue with practices on genomics, spatial transcriptomics and single cell sequencing. We’ll cover the best practices and common challenges in this practice as a foundation to the understanding of bioinformatics pipelines. Rest of the course, you’ll be working in smaller project groups. You’ll be able to choose projects on clustering, immunobiology, and cancer genomics, images etc. As you can see, majority of the course will be hands-on allowing you to practice your acquired knowledge.
At the end participants will
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realize the wealth of bioinformatics database structures and the -omic tools
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understand how to download and use data from bioinformatics databases
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learn best practices and common challenges in genomics, single cell sequencing, spatial transcriptomics technologies
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explore downstream analyses approaches for bioinformatics datasets
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work on a project to practice acquired knowledge on a topic of interest
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work on datasets provided by real life science researchers on clustering, images, immunobiology, molecular biology, and cancer genomics
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present their findings
17:30 - 18:00 introductions
18:00 - 18:30 introduction to bioinformatics and databases (UCSC Genome browser, biomart, oma, string and others from SIB)
18:30 - 18:45 break
18:45 - 19:30 introduction to genomics
19:30 - 19:45 break
19:45 - 20:30 preparations for the genomics practice session
17:30 - 19:30 genomics practice questions and discussion
19:30 - 19:45 break
19:45 - 20:30 introduction to transcriptomics
17:30 - 18:30 Mutations and their study in omics
18:30 - 18:45 break
18:45 - 19:45 introduction to spatial and single cell data analysis
19:45 - 20:00 break
20:00 - 20:30 practice on the clustering with single cell and spatial data
17:30 - 18:30 Project selection
18:30 - 18:45 break
18:45 - 20:30 meeting-up with the project supervisors and project work kick-off
17:30 - 18:00 last check with the project leaders
18:00 - 19:00 project presentations
19:00 - 19:15 break
19:15 - 20:15 project presentations
20:15 - 20:30 wrap-up, feedback
The module will consist of lectures and practical exercises. In addition to lectures, participants will be required to self-study selected topics. Participants will work in groups on a data challenge and present their results at the end of the course.
Exercises during the course: 50% Data challenge: 50% The course is taught in English. We’ll be working in bash. You may also use python, R etc. depending on the projects. No prior knowledge in coding is required although familiarity with a coding language will be helpful. Please bring laptops. If you have questions, feel free to email Tugce.