Modeling erythropoiesis.
In erythropoiesis growth factors like stem cell factor (SCF) and erythropoietin (EPO) react with intrinsically expressed receptors, c-kit and EPO receptor (EPOR) [1] respectively to regulate cell survival, differentiation and proliferation. Yet even today the exact mechanism of these processes rema...
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sg-ntu-dr.10356-501622023-03-03T15:40:15Z Modeling erythropoiesis. Saraf, Pritha. School of Chemical and Biomedical Engineering Mayasari Lim DRNTU::Engineering::Bioengineering DRNTU::Science::Medicine::Biomedical engineering In erythropoiesis growth factors like stem cell factor (SCF) and erythropoietin (EPO) react with intrinsically expressed receptors, c-kit and EPO receptor (EPOR) [1] respectively to regulate cell survival, differentiation and proliferation. Yet even today the exact mechanism of these processes remains unclear. Biological models in silico play a significant role in this field as it guides researchers to conduct experiments and test theories behind the regulatory mechanisms of cellular function. The first half of this project focused on improvising a previously hypothesized model, which accounted for synergistic effects between SCF and EPO in erythropoiesis. We were able to reduce the Hill coefficients used in this model to a more biologically probable number. A sensitivity analysis on this model revealed that the coefficients accounting for the positive feedback loops are more critical while the synergistic contribution of each factor is less significant. The second half of the project explored another model simulating a multi-compartment dynamics of erythropoiesis. The framework of this model has two components. The first component is the cellular system that is being triggered by growth factors and gives out a signal which is a function of the number of receptors on its surface; this response is converted to a probability of it differentiating. The second component is the multi-compartment model that uses the probability function to simulate the dynamics of erythropoiesis. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2012-05-30T07:02:56Z 2012-05-30T07:02:56Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/50162 en Nanyang Technological University 85 p. application/pdf |
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DRNTU::Engineering::Bioengineering DRNTU::Science::Medicine::Biomedical engineering Saraf, Pritha. Modeling erythropoiesis. |
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In erythropoiesis growth factors like stem cell factor (SCF) and erythropoietin (EPO) react with intrinsically expressed receptors, c-kit and EPO receptor (EPOR) [1] respectively to regulate cell survival, differentiation and proliferation. Yet even today the exact mechanism of these processes remains unclear. Biological models in silico play a significant role in this field as it guides researchers to conduct experiments and test theories behind the regulatory mechanisms of cellular function.
The first half of this project focused on improvising a previously hypothesized model, which accounted for synergistic effects between SCF and EPO in erythropoiesis. We were able to reduce the Hill coefficients used in this model to a more biologically probable number. A sensitivity analysis on this model revealed that the coefficients accounting for the positive feedback loops are more critical while the synergistic contribution of each factor is less significant.
The second half of the project explored another model simulating a multi-compartment dynamics of erythropoiesis. The framework of this model has two components. The first component is the cellular system that is being triggered by growth factors and gives out a signal which is a function of the number of receptors on its surface; this response is converted to a probability of it differentiating. The second component is the multi-compartment model that uses the probability function to simulate the dynamics of erythropoiesis. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Saraf, Pritha. |
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Final Year Project |
author |
Saraf, Pritha. |
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Saraf, Pritha. |
title |
Modeling erythropoiesis. |
title_short |
Modeling erythropoiesis. |
title_full |
Modeling erythropoiesis. |
title_fullStr |
Modeling erythropoiesis. |
title_full_unstemmed |
Modeling erythropoiesis. |
title_sort |
modeling erythropoiesis. |
publishDate |
2012 |
url |
http://hdl.handle.net/10356/50162 |
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1759857721288425472 |