Summer School in Bioinformatics and High-Dimensional Statistics
This one-week intensive summer school in Bioinformatics and High-Dimensional Statistics will embrace a broad spectrum of topics, from statistical learning to data analysis, high throughput biology, and medical informatics.
The course is intended for researchers who are familiar with omics experimental technologies and their applications in biology, have had some exposure with R, and who want to learn and expand their skills in bioinformatics and data analysis. The main language for the lectures will be English.
The course will cover underlying theory and practical hands-on exercises.
At the end of the course, participants should be able to run analysis workflows on their own omics data, adapt and combine different tools and make informed choices about bioinformatics data analysis strategies.
Organizer: IMBEI, University Medical Center Mainz
- Elements of statistics and machine learning
- Genomics and Genome Wide Association Studies
- Principles of experimental design
- Phylogenetics, Protein structure & visualization
- Transcriptome analysis
- Molecular Databases & Gene Ontology
- Introduction to Single cell RNA-sequencing
- Artificial Intelligence in medicine, Machine learning, Image recognition
- Knowledge extraction
- Introduction to R
- Reproducible research and R Markdown
- Data visualization
- Become familiar with statistical learning and data analysis, and their application in high throughput biology and medical informatics
- Acquire knowledge in Genetic Epidemiology
- Improve the knowledge of the R language, and broaden the bioinformatics skillset
- Understand the key concepts and steps of RNA sequencing data analysis
- Learn what database resources are available for commonly performed analyses
- Become confident in analysing own (omics) data, aware of the potential pitfalls of high-dimensional data analysis
- Make informed choices about experimental design, and properly apply bioinformatics data analysis strategies
- Be able to create plots and reports with modern reproducible research tools
- Miguel Andrade
- Daan Apeldoorn
- Susanne Gerber
- Federico Marini
- Irene Schmidtmann
- Charlotte Soneson
- Konstantin Strauch
- Dativa Tibyampansha
Date & Time outline: to be announced
The course will take place during the whole week, approximately from 9:00 to 17:30 .
For each day, 4 sessions (effective duration 1:30h) will be allocated.
Lunch break is expected approximately at 12:30.
At the end of each lunch break, a short session will allow the participants to present their current work - in the format of a poster/short slideset, and interact with the others.
At the end of each day, a wrap up session, including Q&As from the audience, will be held.
Technology: to be held online/virtual
Participants are required to use their own laptop with the most recent release versions of R and Bioconductor installed: R-4.0.x and Bioconductor 3.11.
Please make sure that your computer’s hardware is sufficiently powered (>4 GB RAM, > 2 GB free disk space) and that you have administrator rights.
Please follow these software installation instructions before the workshop.
The course material (lectures and practicals) will be made available on the course web page - see https://lms.uni-mainz.de/moodle/course/view.php?id=6801 (requires login with an uni-mainz account).
Registration & Requirements: The participation in this course is free of charge .
Participants are requested to submit a small abstract of their current research project, specifying the motivation to attend this course .
The application has to be sent via email to firstname.lastname@example.org by September, 14 2020 (please specify the subject: [SummerSchool2020])
Please specify your current affiliation (if any), and the preferred means of being contacted.
The notification of attendance will follow in the next few days, to ensure an optimal resource allocation.
For the participation in the Summer School 5 CP can be credited.