Presentation Title

Dynamic System Analysis of HIV infection in CD4+ T-cells

Advisor Information

Tomas Helikar

Location

UNO Criss Library, Room 231

Presentation Type

Oral Presentation

Start Date

6-3-2015 9:45 AM

End Date

6-3-2015 10:00 AM

Abstract

Cell pathways form a complex web of protein interactions that are almost impossible to understand without some sort of aid. Using The Cell Collective and review of published papers on the topic, I was able to create a large scale detailed model of how HIV infection occurs in a CD4+ T-cell. This model can dynamically simulate the infection and show the effects it has on the cell as a whole. By comparing the results of the model found from in-silico simulations to phenomena that have been reported in other papers, the models accuracy can be validated. After validation the model is now being used to attempt to predict novel relationships between pathways and predict phenomena to be tested in laboratory studies. The second aspect of the project involved developing software in The Cell Collective to allow any user to conduct large scale analysis of entire models. This analysis performs a knockout study for each individual node in the model. The knockout of a single node can produce a rippling effect through the entire model that is quantified to analyze the entire model dynamics This software is able to calculate the sensitivity of certain proteins in the cell’s pathways and output a result for the entire model as a whole.

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Mar 6th, 9:45 AM Mar 6th, 10:00 AM

Dynamic System Analysis of HIV infection in CD4+ T-cells

UNO Criss Library, Room 231

Cell pathways form a complex web of protein interactions that are almost impossible to understand without some sort of aid. Using The Cell Collective and review of published papers on the topic, I was able to create a large scale detailed model of how HIV infection occurs in a CD4+ T-cell. This model can dynamically simulate the infection and show the effects it has on the cell as a whole. By comparing the results of the model found from in-silico simulations to phenomena that have been reported in other papers, the models accuracy can be validated. After validation the model is now being used to attempt to predict novel relationships between pathways and predict phenomena to be tested in laboratory studies. The second aspect of the project involved developing software in The Cell Collective to allow any user to conduct large scale analysis of entire models. This analysis performs a knockout study for each individual node in the model. The knockout of a single node can produce a rippling effect through the entire model that is quantified to analyze the entire model dynamics This software is able to calculate the sensitivity of certain proteins in the cell’s pathways and output a result for the entire model as a whole.