Signal Transduction Pathways Construction and Visualization by the TRANSPATH Database
Date Issued
2011
Date
2011
Author(s)
Lin, Chien-Chih
Abstract
Signal transduction pathways provide a lot of important information in systems biology, which identify the functional relationships among molecular components, such as gene, gene product and protein. Furthermore, we can form the biological network by multiple pathways, which provide comprehensive concepts of biological process and reveals the complex causation. However, if we can provide researchers with related networks immediately, we can also assist them to retrieve knowledge effectively and obtain the concrete concept from the biological network. It will save researchers a lot of time and improve their efficiency. Therefore, to provide the biological network rapidly and properly is an important issue.
Based on the above arguments, the main purpose of this thesis is to provide researchers in the biomedical field with signal transduction pathways networks concretely and comprehensively. In this research, the data source comes from the BIOBASE TRANSPATH database. First of all, we apply Breadth-First Search algorithm to construct the tree data structure and we construct the pathway by the concept of two molecules in the same path. After constructing the pathways, we apply Dijkstra’s algorithm to find the shortest path, and finally Adobe Flex Development Tools is used to design visualization of the graphical user interface. This graphical user interface is used to integrate related information and provide visualization of biological networks. In this thesis, we compare the network of VEGF signaling pathway constructed by our methods to the network by KEGG, and we prove that the network constructed by our methods has a certain degree of integrity and usability.
Subjects
Signal Transduction Pathways
Visualization
Network
Breadth-First Search Algorithm
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-100-R98548054-1.pdf
Size
23.54 KB
Format
Adobe PDF
Checksum
(MD5):59c1de5f57ccf179f30c7ead350312ca