Identifying insulin exocytosis events in live-cell TIRFM recordings

Thesis Proposal Details

Supervisor: Morten Gram Pedersen

Creation Date: 06/06/2025 09:09

Description

The projects will develop machine learning methods for classification of exocytosis of insulin granules from live-cell TIRFM recordings of beta-cells expressing fluorescently tagged granule proteins.

Dataset and methods

Dataset type: Already acquired data

Dataset description: TIRFM movies of insulin granules in beta-cells

List of Methods: Image analysis, machine learning classification

Preparatory Courses

Machine Learning for Bioengineering

Tags
Pedersen TIRF beta-cell exocytosis insulin
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