Year: 2011
Type: dissertation
Abstract: Stem cells are able to regenerate and to give rise to specialized cell types.Due to these unique properties, stem cells represent a huge opportunity in the treatment of severe diseases such as dementia or leukemia.The hematopoietic stem cells residing in the bone marrow are the origin of blood regeneration and have been studied for many years.However, the processes driving hematopoiesis on cellular as well as molecular level are not fully understood.A major question to be elucidated is, at which generation after entering differentiation a hematopoietic progenitor cell is committing to the erytroid or myeloid lineage and which cellular factors are involved in this decision.Continuous imaging of living hematopoietic stem cells and all their progeny in vitro allows detailed insights into differentiation.The vast amount of data and information generated in these experiments render it necessary to apply computational methods for quantification and analysis.In this thesis, we present a method capable of predicting a hematopoietic stem cell's decision to commit to the erytroid or myeloid lineage.Based on experiments from the Institute of Stem Cell Research at the Helmholtz Zentrum Munich, an automated image processing pipeline is established.The pipeline analyses 14 morphological properties of hematopoietic stem cells and all their progeny in brightfield images.In addition, fluorescence intensities of eYFP-labeled PU.1 molecules, a transcription factor that is thought to play a key role in lineage decision, are quantified.All features, intensities and annotations per cell are then utilized to train a random forest classifier that is able to predict the fate of unlabeled cells.Evaluation by ten-fold cross-validation results in a macro-averaged f1-measure of 0.83.Based on randomly drawn differentiation trees it is shown, that fate prediction is applicable for formerly unknown trees.The methods developed in this thesis can be adapted to other cell types, which could allow detailed analysis of stem cell behavior over their entire lifetime.
Source: Site cant be reached
Author: Buggenthin, Felix
Language: German
Subfield: Biophysics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6999213355