Have you ever wondered how cells “know” which genes to express at a given time and place, or how a plant seed “decides” when is the best time to germinate? Or would you like to know what the stripes of a zebra, the fingers on your hand, and the patterning of vegetation in dry ecosystems have in common? The aim of this course is to learn how computational models can be used to help address these questions, and how to use models for questions where experimentation is not possible.
Living systems like those mentioned above are made up of many different interacting elements, from genes, to cells, tissues, organs, organisms, and ecosystems. In this course on Modeling Life you will learn to use computational models to understand how these interactions together produce self-organizing mechanisms, from the gene regulatory networks processing information and making cell fate decisions, to how cell-to-cell communication enables the regular distribution of tissues (i.e., fingers) and organs (e.g. lateral roots in plants), how mechanical processes shape tissues in morphogenesis, and finally, how evolution shapes these and many other processes. Additionally, you will learn how to create models, which model type to pick and how to judge the quality of the model.
This course will consist of lectures (HC) covering various modelling approaches to study life at different levels accompanied by computer practicals (WC) where students will get hands-on experience on running computational models of the development or the evolution of animals, plants, and microbial systems. The students will learn how to formulate a computational model to address specific questions (algorithmic thinking), how to analyze the output of the model, and how to question a model based on the underlying assumptions. The students will learn to use modern tools like AI assisted programming to develop their models.