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Pre-reading for this week will prepare the upcoming lecture and be a topic for thi week's quiz.
Pre-reading
This paper is a good crash-course in concepts of graph theory and their application to biology. It contains a lot of definitions that I don't expect you to learn by heart. But do familiarize yourself with the concepts. I might ask things like: The number of a protein's interaction partners corresponds to its (edges/degree/centrality/color) in the interaction network graph.
| Pavlopoulos et al. (2011) Using graph theory to analyze biological networks. BioData Min 4:10. (pmid: 21527005) |
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[ PubMed ] [ DOI ] AbstractUnderstanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system.
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