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Toward a Predictive Understanding of Developmental Decision-Making

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Abstract

The main objective of this thesis is to advance a quantitative understanding of the developmental genetic network. Three projects are presented toward this goal. The first project involves the quantitative dissection of transcription factor dynamics and gene regulation focusing on optogenetics to examine and manipulate transcription factors within a multicellular organism. This project provides a precise understanding of how transcription factors regulate target gene expression.

The second project explores the concept of bistability in autoactivation network motifs, focusing on how feedback loops contribute to binary cell fate decisions. Using a combination of mathematical modeling and experimental validation, this work elaborates on the dynamics governing cellular behavior and its implications for better understanding medical therapies related to cell development.

The final project investigates the flexible design principles governing the binding-site organization within enhancers. This entails unraveling the enhancer sequence's essential role in gene regulation, an insight that could inform the design of synthetic regulatory sequences for biotechnological applications and the development of novel therapeutic strategies.

In conclusion, this thesis provides insights into the developmental genetic network, contributing toward predicting complex biological processes based on specific genetic network parameters. This work may ultimately improve our understanding of organismal development and inform therapeutic strategies for developmental disorders.

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This item is under embargo until September 12, 2025.