Dissertation defence (Computer Science): MSc Nigatu Adossa
Time
13.10.2023 at 12.00 - 16.00
MSc Nigatu Adossa defends the dissertation in Computer Science entitled “Computational approaches for single-cell omics and multi-omics data” at the University of Turku on 13 October 2023 at 12.00 (University of Turku, Medisiina C, Osmo Järvi lecture hall, Kiinamyllynkatu 10, Turku).
Opponent: Professor Sascha Ott (University of Warwick, UK)
Custos: Professor Laura Elo (University of Turku)
Doctoral Dissertation at UTUPub: https://urn.fi/URN:ISBN:978-951-29-9450-2
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Summary of the Doctoral Dissertation:
This thesis studied single-cell omics data analysis methods and utilized these to investigate the cells of the uterus. Single-cell omics technologies allow the study of tissues with single-cell resolution, offering profound insights into fundamental biology and various disease conditions. The first part of the thesis was dedicated to exploring methodologies in single-cell tranomics. In single-cell tranome analysis, the cell type identification is based on accurate clustering of the cells. Consequently, clustering plays a pivotal role in the analysis pipeline. The first study of the thesis compared different types of Dirichlet Process mixture models. This investigation underscored the value of Dirichlet process mixture models as valuable additions to the clustering analysis of single-cell tranomic data. It was demonstrated that their utility is heavily dependent on the characteristics of the data under examination. The second study within the thesis involved an assessment of strategies and challenges related to the integrative analysis of single-cell multi-omic data. This study also proposed approaches for effectively integrating different types of single-cell data, such as tranomics, epigenomics, and proteomics.
The second part of the thesis utilized integrative analysis of single-cell tranomics to study the roles played by distinct uterine cell types in the occurrence of late-onset and early-onset preeclampsia, two devastating pregnancy disorders. Based on the results, deficiencies in the differentiation of uterine stromal cells are notably implicated in late-onset preeclampsia, as the activation of specific immune cells, known as uterine natural killer cells, plays a specific role in early-onset preeclampsia. Furthermore, through gene regulatory network analysis of these cell types, crucial factors governing maternal immunotolerance, essential for a successful pregnancy, were identified. These factors may also contribute to pregnancy-related disorders.
Opponent: Professor Sascha Ott (University of Warwick, UK)
Custos: Professor Laura Elo (University of Turku)
Doctoral Dissertation at UTUPub: https://urn.fi/URN:ISBN:978-951-29-9450-2
***
Summary of the Doctoral Dissertation:
This thesis studied single-cell omics data analysis methods and utilized these to investigate the cells of the uterus. Single-cell omics technologies allow the study of tissues with single-cell resolution, offering profound insights into fundamental biology and various disease conditions. The first part of the thesis was dedicated to exploring methodologies in single-cell tranomics. In single-cell tranome analysis, the cell type identification is based on accurate clustering of the cells. Consequently, clustering plays a pivotal role in the analysis pipeline. The first study of the thesis compared different types of Dirichlet Process mixture models. This investigation underscored the value of Dirichlet process mixture models as valuable additions to the clustering analysis of single-cell tranomic data. It was demonstrated that their utility is heavily dependent on the characteristics of the data under examination. The second study within the thesis involved an assessment of strategies and challenges related to the integrative analysis of single-cell multi-omic data. This study also proposed approaches for effectively integrating different types of single-cell data, such as tranomics, epigenomics, and proteomics.
The second part of the thesis utilized integrative analysis of single-cell tranomics to study the roles played by distinct uterine cell types in the occurrence of late-onset and early-onset preeclampsia, two devastating pregnancy disorders. Based on the results, deficiencies in the differentiation of uterine stromal cells are notably implicated in late-onset preeclampsia, as the activation of specific immune cells, known as uterine natural killer cells, plays a specific role in early-onset preeclampsia. Furthermore, through gene regulatory network analysis of these cell types, crucial factors governing maternal immunotolerance, essential for a successful pregnancy, were identified. These factors may also contribute to pregnancy-related disorders.
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