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Title: | IDENTIFYING MECHANISMS THAT DIRECT TGFβ SIGNALING OUTCOME IN CELLS | Authors: | NG WEE KIAT JEREMY | Keywords: | TGFB, multi-omics, breast cancer, cell signalling, machine learning | Issue Date: | 25-Sep-2020 | Citation: | NG WEE KIAT JEREMY (2020-09-25). IDENTIFYING MECHANISMS THAT DIRECT TGFβ SIGNALING OUTCOME IN CELLS. ScholarBank@NUS Repository. | Abstract: | TGFB is a family of growth factors that regulates a range of cellular and physio- logical functions, and its dysregulation leads to various diseases including fibrosis and cancers. TGFB signaling outcome is cell-context specific. However, there remains a lack of insights into the underlying drivers of cell-specific signaling outcome. In this thesis, we analyze next-generation sequencing data to dissect the role of chromatin accessibility and epigenetic modification in restricting cellular reponse to TGF𝛽 treatment. From chromatin contexts, we then developed a model of transcription factor binding site prediction to predict TGF𝛽 target genes. This is followed by an attempt to model the regulatory effect of transcription factor binding. Finally, this thesis presents a novel optogenetic system that was developed for the interrogation of how signaling dynamics can shape TGFB signaling outcome. | URI: | https://scholarbank.nus.edu.sg/handle/10635/190581 |
Appears in Collections: | Ph.D Theses (Open) |
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