SUMMARY
In this research, it is discussed how spatiotemporal analysis of single cells can lead to a deeper understanding of stem cell biology. Spatiotemporal analysis is the analysis of cells on the single cell level over time and space. One potential upside this approach to biology helps solve is that it can take into account heterogeneity of cells. Computational pipelines to aid in the spatiotemporal analysis of cells are presented and used on mesenchymal stem cells (MSCs). These pipelines are used to approximate differentiation time from RNA Seq data. Additionally, results from a cytokine assay are analyzed. These pipelines are also used to discuss the distribution of RNA within cell populations.A blur detection algorithm and cell boundary detection algorithm are presented for image processing. RNA-Seq data is used in the evaluation of 3 algorithms to predict differentiation state from gene expression data. Additionally, it is shown that cell culture media affects cytokine secretions and that CCL11 is enriched near the boundaries of umbilical cord mesenchymal stem cells.