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Content provider
- European Bioinformatics Institute (EBI)1
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Scientific topic
- Active learning1
- Biological modelling1
- Biological system modelling1
- Data integration1
- Data integration and warehousing1
- Data warehousing1
- Ensembl learning1
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- Reinforcement learning1
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- Systems biology1
- Systems modelling1
- Unsupervised learning1
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Event type
- Workshops and courses1
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Target audience
- This course is aimed at advanced PhD students and post-doctoral researchers who are currently working with large-scale omics datasets with the aim of discerning biological function and processes. Ideal applicants should already have some experience (ideally 1-2 years) working with systems biology or related large-scale multi-omics data analyses. Applicants are expected to have a working knowledge of the Linux operating system and the ability to use the command line. Experience of using a programming language (i.e. Python) is highly desirable, and while the course will make use of simple coding or streamlined approaches such as Python notebooks, higher levels of competency will allow participants to focus on the scientific methodologies rather than the practical aspects of coding and how they can be applied in their own research. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Python turorial: https://www.w3schools.com/python/ R tutorial: https://www.datacamp.com/courses/free-introduction-to-r Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
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