MSB Training School 2023: Statistical and Machine Learning Modeling of Biological Data in R 

The aim of this training school is to equip students and young researchers working with biological data with the necessary statistical and machine learning tools needed to analyze biological data. 

The program will focus on the application of modern statistics and R programming, to tackle biological challenges effectively. We will offer comprehensive workshops that cater to both beginners and experienced researchers in the field. We believe in learning by doing, so our lectures will emphasize practical applications and real-life projects. Whether you are new to data analysis or seeking to enhance your existing skills, the training modules are tailored to meet your learning needs. 

What You'll Learn:

• Introduction to R and Data Manipulation: Gain a solid understanding of R programming and learn how to effectively manage, clean, and preprocess biological datasets. 

• Biological Data Visualization: Acquire skills in creating visually informative plots and charts to effectively communicate your findings.

• Statistical Analysis in R: Explore a range of statistical methods tailored for biological data analysis, including hypothesis testing, linear models, and multivariate analysis.

• Feature Selection and Dimensionality Reduction: Master the art of selecting relevant features and reducing the complexity of high-dimensional biological datasets.

• Machine Learning Techniques: Discover various machine learning algorithms such as regression, random forests, and support vector machines, and understand how to apply them to biological data.

• Case Studies and Real-World Projects: Work on hands-on projects using actual biological datasets, gaining valuable experience in tackling real-world research problems. 

  A detailed program can be accessed here. 

Onsite participation in this training school is free of charge but limited to 30 participants. Selection will be based on motivation. Several lectures will be streamed online via Zoom for those who can not participate onsite.

Onsite participants will receive a certificate of completion and are required to have their own laptops. A virtual environment, which can be accessed through a web browser, will be used during practical sessions. 

Applications for onsite participation can be submitted here before September 25, 2023. Notification of acceptance will be sent to selected participants by September 30, 2023. Registrations for online participation are open until October 15, 2023.