| dc.contributor.author | Shrestha, Sarjan | |
| dc.description.abstract | 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. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Protein-Function Prediction Using a Graph-Matching Algorithm | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2014-09-30T17:55:01Z | |
| dc.date.available | 2014-09-30T17:55:01Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | http://hdl.handle.net/10365/24078 | |
| dc.subject.lcsh | Proteins -- Analysis -- Data processing. | en_US |
| dc.subject.lcsh | Proteomics -- Data processing. | en_US |
| dc.subject.lcsh | Computer graphics. | en_US |
| dc.subject.lcsh | Graph algorithms. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Yan, Changhui | |
