원문정보
초록
영어
Network analysis is one of the hottest areas of research in biotechnology and biomedical research. It is a straight forward method of representing local and global characteristics of biological nodes representing the various biological elements. In network analysis, we use mathematical graph theory to show the interaction among the genes and its product. This represents the various biological activities in the cell. In order to predict the certain activity and interaction among the biological elements, it is necessary to find the optimal path in the network. This optimal path is usually the shortest path, which clearly depicts the key elements involved for the particular reaction. It is also necessary to count the number of shortest paths between the given pairs of genes in the network. This paper describes the need for finding shortest path in the biological network and illustrate the usage of Bellman-Ford algorithm to find the shortest path in Hutchinson-Gilford Progeria Syndrome (HGPS) data sets.
목차
1. Introduction
2. Background and Literature Review
3. Methodology
3.1. Need for Shortest Path Prediction
3.2. Bellman-Ford Algorithm
4. Results and Discussion
5. Conclusion
References