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Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling.
Dissertation (MSc(Electronic Engineering))--University of Pretoria, 2021.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2022
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| _version_ | 1867613475053764608 |
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| access_status_str | Open Access |
| author2 | de Villiers, J.P. |
| author_browse | de Villiers, J.P. |
| author_facet | de Villiers, J.P. |
| collection | Thesis |
| dc_rights_str_mv | © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc(Electronic Engineering))--University of Pretoria, 2021. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/83731 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:43.949Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/83731 Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. de Villiers, J.P. u12021343@tuks.co.za Pepper, M.S. Dowling, Riaan Deon Bayesian inference cell differentiation haematopoiesis Gibbs sampler Gaussian process gene expression bifurcation points Dissertation (MSc(Electronic Engineering))--University of Pretoria, 2021. Cell differentiation is a fundamental process in biology by which cells progress through different stages of maturation to become specialised cell types. Owing to the importance of understanding the process of cell differentiation various mathematical models have been developed to represent cell behaviour during its developmental process. Advancements in these models are owed to researchers being able to obtain single-cell gene expression data with high throughput genome-scale sequencing methods. Here we present BAGEL: Bayesian Analysis of Gene Expression Lineages, which is a novel statistical model. It allows researchers to gain new insights into the process of cell differentiation based on (i) a sound Bayesian inference approach to model cell differentiation as a continuous process; and (ii) an effective projection method which opens the door to visualise and investigate the similarities and differences between intra- and inter-species single-cell gene expression datasets. Although the main focus of this manuscript is on haematopoiesis, BAGEL should hold for various single-cell gene expression datasets. Electrical, Electronic and Computer Engineering MSc(Electronic Engineering) Unrestricted 2022-02-09T12:01:40Z 2022-02-09T12:01:40Z 2022-07-15 2021 Dissertation * S2021 http://hdl.handle.net/2263/83731 en © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | Bayesian inference cell differentiation haematopoiesis Gibbs sampler Gaussian process gene expression bifurcation points Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title | Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title_full | Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title_fullStr | Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title_full_unstemmed | Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title_short | Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian process and Gibbs sampling. |
| title_sort | bayesian inference of haematopoietic stem progenitor cell differentiation phenotypic manifolds and their bifurcation points using gaussian process and gibbs sampling |
| topic | Bayesian inference cell differentiation haematopoiesis Gibbs sampler Gaussian process gene expression bifurcation points |
| url | http://hdl.handle.net/2263/83731 |