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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Main Author: Saraf, Pritha.
Other Authors: School of Chemical and Biomedical Engineering
Format: Final Year Project
Language:English
Published: 2012
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Online Access:http://hdl.handle.net/10356/50162
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Bioengineering
DRNTU::Science::Medicine::Biomedical engineering
spellingShingle DRNTU::Engineering::Bioengineering
DRNTU::Science::Medicine::Biomedical engineering
Saraf, Pritha.
Modeling erythropoiesis.
description 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.
author2 School of Chemical and Biomedical Engineering
author_facet School of Chemical and Biomedical Engineering
Saraf, Pritha.
format Final Year Project
author Saraf, Pritha.
author_sort 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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