Signals and Noise in Complex Biological Systems

• Main Author: Rung, Johan
• Format: Doctoral Thesis
• Language: English
• Published: Uppsala universitet, Fysikalisk-kemiska institutionen 2007
• Subjects: Engineering physics; complex systems; computational biology; gene networks; genome-wide; stochastic resonance; microarray; diabetes; association study; transcription regulation; gene expression; Teknisk fysik
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7862; http://nbn-resolving.de/urn:isbn:978-91-554-6888-0

In every living cell, millions of different types of molecules constantly interact and react chemically in a complex system that can adapt to fluctuating environments and extreme conditions, living to survive and reproduce itself. The information required to produce these components is stored in the genome, which is copied in each cell division and transferred and mixed with another genome from parent to child. The regulatory mechanisms that control biological systems, for instance the regulation of expression levels for each gene, has evolved so that global robustness and ability to survive under harsh conditions is a strength, at the same time as biological tasks on a detailed molecular level must be carried out with good precision and without failures. This has resulted in systems that can be described as a hierarchy of levels of complexity: from the lowest level, where molecular mechanisms control other components at the same level, to pathways of coordinated interactions between components, formed to carry out particular biological tasks, and up to large-scale systems consisting of all components, connected in a network with a topology that makes the system robust and flexible. This thesis reports on work that model and analyze complex biological systems, and the signals and noise that regulate them, at all different levels of complexity. Also, it shows how signals are transduced vertically from one level to another, as when a single mutation can cause errors in low level mechanisms, disrupting pathways and create systemwide imbalances, such as in type 2 diabetes. The advancement of our knowledge of biological systems requires both that we go deeper and towards more detail, of single molecules in single cells, as well as taking a step back to understand the organisation and dynamics in the large networks of all components, and unite the different levels of complexity.