Advances in benchmarking methodologies for systems biology

Abstract: In this dissertation entitled "Advances in Benchmarking Methodologies for Systems Biology," a series of methodological improvements within the field of systems biology are developed to contribute to a deeper understanding of complex biological phenomena through computational analyses. These approaches and techniques span various research areas, including molecular signaling pathways, parameter estimation, proteomics, and statistics providing practical solutions to current research hurdles. These methodological approaches increase the reproducibility, accessibility, and reliability of scientific findings.
A new standardized, versatile, and user-friendly file format called "PEtab" for parameter estimation problems in systems biology is introduced. PEtab promotes reusability, reproducibility, and interoperability between different modeling toolboxes, fostering an interdisciplinary and collaborative research environment, and promoting good scientific practice. The "Realistic Simulation of Time-Course Measurements" solves the challenge of benchmarking methods in cases with limited experimental data. This method allows a realistic simulation of diverse experimental setups and data characteristics, enhancing the systematic evaluation and validation of methods. This considerably contributes to the reliability and credibility of research outcomes in systems biology.
Using mathematical modeling, the fundamental mechanisms during tissue regeneration, such as spatially distinct signaling activities, bistable pattern formation, and "Mutual Repression Between JNK and JAK/STAT" are explored. These findings deepen the understanding of wound healing processes in acute injuries, chronic damages, and tumor environments, providing a foundation for further studies aimed at developing new therapeutic interventions and medication strategies targeting these signaling pathways. This project underscores the potential of mathematical modeling in unraveling complex biological phenomena. The implementation of the "Rcall" interface enables the integration of two commonly used powerful programming languages, R and MATLAB, and therewith expands the repertoire of applicable computational analysis methods. Furthermore, the application of the Rcall interface enables the assessment and comparison of methods from both programming languages. The "Data-Driven Selection of an Imputation Algorithm (DIMA)" addresses the persistent challenge of handling missing data in omics data analysis. DIMA provides an empirical approach to automatically select the most suitable imputation algorithm based on specific data characteristics. By applying this approach, DIMA enhances the reliability of data analysis and, consequently, of research findings. Each project of this thesis addresses a critical aspect of methodological research, from defining a standardized data set, simulating a realistic data set, and understanding cellular responses in tissue repair to integrating computational methods and selecting the most suitable. This research contributes to the field of systems biology by providing practical tools, methodological techniques, and biological insights, promoting informed decisions and research quality. "Progress in science depends on new techniques, new discoveries and new ideas, probably in that order." – Sydney Brenner In accordance with the quote by Sydney Brenner, a Nobel laureate in the genetic regulation of organ development and co-discoverer of mRNA, this dissertation underscores the trinity of "new techniques, new discoveries, and new ideas," the core of scientific progress.
Each project in this dissertation addresses important aspects of methodological techniques, promotes the reliability of biological discoveries, and, in doing so, creates opportunities for future innovative research ideas

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Universität Freiburg, Dissertation, 2024

Klassifikation und Themen

• Schlagwort: Systembiologie ; Benchmark ; Mathematisches Modell ; Parameterschätzung ; Mathematische Modellierung ; Gewöhnliche Differentialgleichung ; Systembiologie ; Statistik ; Imputationstechnik ; Proteomanalyse ; Parameterschätzung ; Parameter ; Versuchsplanung

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Freiburg
• (wer): Universität
• (wann): 2024
• Urheber: Egert, Janine
• Beteiligte Personen und Organisationen: Kreutz, Clemens ; Schilling, Oliver ; Timmer, Jens ; Institut für Medizinische Biometrie und Statistik. Freiburg im Breisgau ; Albert-Ludwigs-Universität Freiburg. Medizinische Fakultät

Weitere Informationen

• DOI: 10.6094/UNIFR/258551
• URN: urn:nbn:de:bsz:25-freidok-2585519
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:23 MESZ