The Relationship between Protein Centrality and Essentiality in Saccharomyces cerevisiae
Session Number
C25
Advisor(s)
Manyuan Long, University of Chicago Wenyu Zhang, University of Chicago
Location
B-116
Start Date
28-4-2016 10:15 AM
End Date
28-4-2016 10:40 AM
Abstract
With the recent shift in molecular biology to the study of proteins not as individual elements but as nodes in a larger network, the question arises of the impact of a central protein or gene in these networks. Previous studies have suggested that highly-connected proteins play a more important role in organism fitness. In this investigation, I examined the most highly connected proteins in the Saccharomyces cerevisiae protein network to determine these relationships. I used a variety of data analysis and mapping tools, such as Microsoft Excel, Python, and R, to filter through hundreds of thousands of protein-protein interactions, map these into genetic, physical, and combined networks, and analyze all of the nodes in these networks. The results showed that more essential proteins tend to be more highly connected within the interaction network; furthermore, they showed that older genes tended to have a higher chance of being essential, as well as being more central to the network. These results were especially clear in the physical protein interaction dataset, where a few genes such as YDR172W and YIL021W contained over 300 interactions. However, there were a few anomalies in the data, especially in the genetic network, which warrant more accurate testing in the future.
The Relationship between Protein Centrality and Essentiality in Saccharomyces cerevisiae
B-116
With the recent shift in molecular biology to the study of proteins not as individual elements but as nodes in a larger network, the question arises of the impact of a central protein or gene in these networks. Previous studies have suggested that highly-connected proteins play a more important role in organism fitness. In this investigation, I examined the most highly connected proteins in the Saccharomyces cerevisiae protein network to determine these relationships. I used a variety of data analysis and mapping tools, such as Microsoft Excel, Python, and R, to filter through hundreds of thousands of protein-protein interactions, map these into genetic, physical, and combined networks, and analyze all of the nodes in these networks. The results showed that more essential proteins tend to be more highly connected within the interaction network; furthermore, they showed that older genes tended to have a higher chance of being essential, as well as being more central to the network. These results were especially clear in the physical protein interaction dataset, where a few genes such as YDR172W and YIL021W contained over 300 interactions. However, there were a few anomalies in the data, especially in the genetic network, which warrant more accurate testing in the future.