Data driven approaches to infer the regulatory mechanism shaping and constraining levels of metabolites in metabolic networks
Dissertation, Universität Potsdam, 2018
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Körperschaft: | |
| Weitere Verfasser: | , , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Potsdam
2018
|
| Schlagworte: | |
| Online Zugang: | Inhaltsverzeichnis |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen | Zusammenfassung: | Dissertation, Universität Potsdam, 2018 Systems biology aims at investigating biological systems in its entirety by gathering and analyzing large-scale data sets about the underlying components. Computational systems biology approaches use these large-scale data sets to create models at different scales and cellular levels. In addition, it is concerned with generating and testing hypotheses about biological processes. However, such approaches are inevitably leading to computational challenges due to the high dimensionality of the data and the differences in the dimension of data from different cellular layers. This thesis focuses on the investigation and development of computational approaches to analyze metabolite profiles in the context of cellular networks. This leads to determining what aspects of the network functionality are reflected in the metabolite levels. With these methods at hand, this thesis aims to answer three questions: (1) how observability of biological systems is manifested in metabolite profiles and if it can be used for phenotypical comparisons; (2) ... |
|---|---|
| Beschreibung: | kumulative Dissertation |
| Beschreibung: | 109 Seiten Illustrationen, Diagramme |