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A Systems Biology Approach for Modeling Microbiomes Using Split Graphs
Advisor Information
Hesham Ali
Location
UNO Criss Library, Room 225
Presentation Type
Oral Presentation
Start Date
2-3-2018 2:15 PM
End Date
2-3-2018 2:30 PM
Abstract
Recent studies have shown that the composition of microorganisms inside different part of our bodies as well as in diverse components in our environment contribute to our overall health in a significant way. Since the presence of such organisms as well as the interactions among them play critical roles on the health of all living beings in their ecosystems, proper analysis is needed to reveal these significant relationships. In this study, we propose a systems biology approach using a split graph model to analyze the composition of microbiomes and the impact of such composition on the health and growth of organisms living in associated environments. The proposed model allows us to explore features of various types of microorganisms in their ecosystems including the level of co-occurrence of groups of bacteria and how clusters of bacteria impact host phenotypes. The model not only enables us to analyze them together, but also independently. Here, we conduct several case studies related to the composition of microbiomes in different ecosystems and their impact on various host phenotypes. Early results of the study show that certain groups of bacteria are significantly associated with various host phenotypes. We also identify bacterial clusters that provide insights to the functional relevance of these bacteria and their contribution to their microbial ecosystem.
A Systems Biology Approach for Modeling Microbiomes Using Split Graphs
UNO Criss Library, Room 225
Recent studies have shown that the composition of microorganisms inside different part of our bodies as well as in diverse components in our environment contribute to our overall health in a significant way. Since the presence of such organisms as well as the interactions among them play critical roles on the health of all living beings in their ecosystems, proper analysis is needed to reveal these significant relationships. In this study, we propose a systems biology approach using a split graph model to analyze the composition of microbiomes and the impact of such composition on the health and growth of organisms living in associated environments. The proposed model allows us to explore features of various types of microorganisms in their ecosystems including the level of co-occurrence of groups of bacteria and how clusters of bacteria impact host phenotypes. The model not only enables us to analyze them together, but also independently. Here, we conduct several case studies related to the composition of microbiomes in different ecosystems and their impact on various host phenotypes. Early results of the study show that certain groups of bacteria are significantly associated with various host phenotypes. We also identify bacterial clusters that provide insights to the functional relevance of these bacteria and their contribution to their microbial ecosystem.