|
|
Studying lymphocyte development using mass cytometry
Novák, David ; Stuchlý, Jan (advisor) ; Špidlen, Josef (referee)
Studying lymphocyte development using mass cytometry Abstract Development of mature lymphocytes, a white blood cell subtype, is crucial for the correct function of the human immune system. Currently, developmental pathways of lymphocytes can be studied using high-throughput single-cell measurements. In particular, mass cytometry enables the study of immunologically relevant pheno- typic and functional markers on a vast scale. In this work I present my individual contribution to tviblindi, a powerful software tool for analysis of cytometric data aimed at uncovering developmental trajectories. tviblindi is a package written in R, Python and C++. It provides a means to integrate prior knowledge with data analyses grounded in graph theory and algebraic topology. tviblindi is accessible to biological researchers without background in computer science or mathematics. It is an addition to the expanding field of trajectory inference in single-cell data. Furthermore, I review current knowledge of T-cell development and conduct a tviblindi analysis thereof using human thymus and peripheral blood datasets and evaluate the results. 1
|
|
|
Studying lymphocyte development using mass cytometry
Novák, David ; Stuchlý, Jan (advisor) ; Špidlen, Josef (referee)
Studying lymphocyte development using mass cytometry Abstract Development of mature lymphocytes, a white blood cell subtype, is crucial for the correct function of the human immune system. Currently, developmental pathways of lymphocytes can be studied using high-throughput single-cell measurements. In particular, mass cytometry enables the study of immunologically relevant pheno- typic and functional markers on a vast scale. In this work I present my individual contribution to tviblindi, a powerful software tool for analysis of cytometric data aimed at uncovering developmental trajectories. tviblindi is a package written in R, Python and C++. It provides a means to integrate prior knowledge with data analyses grounded in graph theory and algebraic topology. tviblindi is accessible to biological researchers without background in computer science or mathematics. It is an addition to the expanding field of trajectory inference in single-cell data. Furthermore, I review current knowledge of T-cell development and conduct a tviblindi analysis thereof using human thymus and peripheral blood datasets and evaluate the results. 1
|
|
|
Basics on persistent homology
Novák, Jakub ; Šťovíček, Jan (advisor) ; Hrbek, Michal (referee)
Abstract:In this work, the reader is introduced to the theory of persistent ho- mology and its applications. In the first chapter we will show the basics of sim- plicial and singular homology and we will prove the basic relations, especially the independence of simplicial homological groups on the chosen △-complex and isomorphism between homological groups of homotopic spaces. In the second chapter, we explain the motivation behind persistent homology, describe its al- gebraic structure and how it can be visually represented. We describe and prove the corectness of the algorithm for its calculation. We then illustrate the theory on an example. 1
|
guest ::
