We are surrounded by complex systems and their understanding, mathematical description, and interpretation are major challenges of the 21st century. In this course, students will be introduced into the world of networks and their application in the analysis of biomedical data. A human body consists of more than 37 billion cells and our existence depends on the harmonious interaction between thousands of genes, proteins and metabolites within our cells. Networks are the ideal tool to capture, explore and evaluate these interactions. The course covers both the fundamental graph theory concepts and their application in network biology. After completing this course, the student is able to analyse biomedical research data using network science approaches. Additionally, the student will be aware of best practises in network visualisation to facilitate interpretation and communication of research results. In the skills training, held in the computer rooms, the students will apply the topics discussed in the lectures and tutorials. The content of the training will be directly linked to tutorials. Importantly, in the final project the students will apply the acquired skills to answer their biological research question.
1. Understanding basic concepts of graph theory and network science 2. Understanding and applying of network algorithms to investigate network properties 3. Using and evaluating online resources for biological network data 4. Performing analyses with biomedical research data using network science approaches 5. Learning how to use Cytoscape to analyse, visualise and interpret biological networks 6. Creating intuitive visualisation for network interpretation
1. Network Science Book, Albert-László Barabási http://barabasi.com/networksciencebook/ 2. Relevant papers will be provided during the course