### Analysis of Complex Biological Systems

### Lecture 1. Introduction

(Slides)

Introduction to Matlab (Slides)

### Lecture 2. Complex systems as graphs

(Slides)

### Lecture 3. Global network organisation: Random, small-world and scale-free networks

(Slides)

### Lecture 4. Local network organisation: Clusters, motifs, Jaccard index, betweenness centrality

(Slides)

### Lecture 5. Network changes over time: development and deconstruction

(Slides)

### Lecture 6. Spreading in networks

(Slides)

### Lecture 7. Dynamical Systems I

(Slides)

### Lecture 8. Dynamical Systems II

(Slides)

### Lecture 9. Dynamical Systems III

(Slides)

### Lecture 10. Dynamical Systems IV

(Slides)

### Lecture 11. Dynamical Systems V

(Slides)

### Lecture 12. Dynamical Systems VI

(Slides)

### Lecture 13. Dynamical Systems VII

(Slides)

### Lecture 14. Dynamical Systems VIII

(Slides)

### Reading material

Kaiser M (2011). A Tutorial in Connectome Analysis: Topological and Spatial Features of Brain Networks. Neuroimage 57:892-907 [Article (PDF)]
Rainhard Diestel: Graph Theory, Springer, Third Edition [First chapter (PDF)]

More information about the book including the download of all chapters is availabel at http://diestel-graph-theory.com/