Planar Subgraph Extraction Algorithms as Biological Graph Filters

Advisor Information

Hesham Ali

Location

UNO Criss Library, Room 231

Presentation Type

Oral Presentation

Start Date

4-3-2016 11:00 AM

End Date

4-3-2016 11:15 AM

Abstract

There are many real-world systems consisting of interacting entities that can be modeled by the powerful abstraction of graphs. Large-scale systems such as social networks, biological networks, and transportation networks are a few examples. These networks hold a wealth of much-needed information, but that information is often difficult to extract due to the size and complexity of the networks. One method used to handle this is the application graph filters. Graph filters intelligently remove pieces of the graph to reduce its size and complexity, while preserving desirable properties. The aim of this project is to analyze the potential use of planar subgraphs as a graph filter. Our specific focus is the domain of bioinformatics. Our main research goal is to provide convincing evidences that a planar graph filter preserves critical biologically relevant substructures, such as biological pathways, while greatly reducing network size.

Additional Information (Optional)

Winner of Honorable Mention Undergraduate Oral Presentation

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COinS
 
Mar 4th, 11:00 AM Mar 4th, 11:15 AM

Planar Subgraph Extraction Algorithms as Biological Graph Filters

UNO Criss Library, Room 231

There are many real-world systems consisting of interacting entities that can be modeled by the powerful abstraction of graphs. Large-scale systems such as social networks, biological networks, and transportation networks are a few examples. These networks hold a wealth of much-needed information, but that information is often difficult to extract due to the size and complexity of the networks. One method used to handle this is the application graph filters. Graph filters intelligently remove pieces of the graph to reduce its size and complexity, while preserving desirable properties. The aim of this project is to analyze the potential use of planar subgraphs as a graph filter. Our specific focus is the domain of bioinformatics. Our main research goal is to provide convincing evidences that a planar graph filter preserves critical biologically relevant substructures, such as biological pathways, while greatly reducing network size.