Date of Award

2014

Publisher

North Dakota State University

Document Type

Master's Paper

Degree Awarded

Master of Science (MS)

Program

Computer Science

Department

Computer Science

College

Engineering

Faculty Advisor

Yan, Changhui

Description

Proteins are the basic building blocks for biological life. Proteins interact with other proteins or molecules to carry out various functions. The active region in the protein molecule is the functional site. Today, most research work has been done to establish sequence-based, structure-based, and machine-learning approaches for prediction of protein’s functional site. This paper describes a tool for identifying the functional site of protein using a graph-based approach. Each protein structure is represented as a graph. Each protein residue represents a vertex, and the relationship between residues represents the edges of the graph. The tool compares proteins to identify the functional site in the form of maximum common subgraphs using McGregor’s subgraph algorithm. Functional sites for new proteins can be predicted using the subgraphs. The graph-based approach is computationally efficient and accurate due to the wide range of protein properties that are taken into consideration.

Rights

NDSU Policy 190.6.2

Rights Link

https://www.ndsu.edu/fileadmin/policy/190.pdf

Handle Identifier

https://hdl.handle.net/10365/24078

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