Models of Biological Regulation

  • Metabolism is thought to be robust against multiple types of perturbations since organisms have survived millions of years of selective evolution. Some of the challenges handled by metabolic systems are the transport, transformation and storage of compounds. All biochemical processes in a cell have to occur at physiological conditions, maintain energy levels and tolerate fluctuating environmental conditions. The organization and regulation of these processes is thus of great interest to the field of logistics where solutions to the dynamic control of complex systems are desperately needed. As a basis, the metabolism and transcriptional regulatory network of Escherichia coli, a thoroughly studied experimental model organism, are compared with company networks gleaned from actual production data. A number of results are established: (i) A direct relation between the unit components of the metabolic and logistics systems. This involves the biochemical reactions and manufacturing steps involved with the material flow on the networks, as well as a concept for the regulatory elements. (ii) Potentially beneficial structural elements of metabolic networks are discussed and the composition of few-node subgraphs as one such indicator is explored in E. coli’s metabolic network. (iii) The structure of networks tasked with specific patterns of flow distribution and robust to particular types of local damages are investigated. A clear relation between shared sub-patterns and the occurrence of modular structures is observed. (iv) The large-scale organization of regulation in wild type E. coli and two mutants is confirmed to be dominated by the two counterbalancing aspects of digital (transcriptional) and analog (physico- chemical) control over the course of E. coli’s growth cycle. (v) A case is made for the recording of results as a function of the increasing amount of knowledge available about objects of study.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Moritz Beber
Referee:Marc-Thorsten Hütt, Georgi Muskhelishvili, Katja Windt, Stefan Bornholdt
Advisor:Marc-Thorsten Hütt
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1007318
Document Type:PhD Thesis
Language:English
Date of Successful Oral Defense:2015/04/17
Date of First Publication:2017/08/02
Academic Department:Life Sciences & Chemistry
PhD Degree:Bioinformatics
Focus Area:Health
Call No:Thesis 2015/62

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