Analysis of high-throughput data and modelling in systems biology

Abstract: This thesis comprises contributions to two central pillars of systems biology: the analysis of high- dimensional omics data and the modelling of biological dynamics.
For the first pillar, the diverse characteristics of quantitative data generated by various omics technologies were comprehensively analyzed, addressing the impact on downstream analyses. Fur- thermore, this work supports the extraction of complex information from biological omics data by introducing new tools for omics preprocessing in the form of missing value handling and normal- ization. Additionally, this thesis includes comparisons of different analysis workflows for data-inde- pendent acquisition proteomics data and of deep learning-based integration methods for single- cell multi-omics data. The second pillar focuses on the modelling of dynamics typically observed in signalling pathways using the ’Retarded Transient Function’ (RTF) approach.
Overall, this thesis seeks to expand the toolkit available to biologists working with omics and time- resolved data, offering tools for data processing, decision support regarding analysis strategies, and intuitive modelling of time course data

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
Universität Freiburg, Dissertation, 2024

Keyword
Datenanalyse
Systembiologie
High throughput screening
Systembiologie
Omics-Technologie
Mathematische Modellierung
Bioinformatik

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2024
Creator
Contributor

DOI
10.6094/UNIFR/261002
URN
urn:nbn:de:bsz:25-freidok-2610023
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 2:41 AM CEST

Data provider

This object is provided by:
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Time of origin

  • 2024

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