Cytoscape application for predicting missing links in protein interaction networks

In the area of bio-Informatics, recent research has suggested that an entire protein proteome seems to be more highly interconnected than what was initially expected; hence looking at the proteome as a whole seems to be able to offer more information than just focusing on one protein on its own. How...

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Bibliographic Details
Main Author: Maisurah Muslim
Other Authors: Rajapakse Jagath Chandana
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/70095
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Institution: Nanyang Technological University
Language: English
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Summary:In the area of bio-Informatics, recent research has suggested that an entire protein proteome seems to be more highly interconnected than what was initially expected; hence looking at the proteome as a whole seems to be able to offer more information than just focusing on one protein on its own. However it was also noted that current knowledge of the interactome is both incomplete and noisy. Thus, it will be beneficial if there is a method devised to generate a possible architecture structure for the entire network. This project will look into the research paper “Resolving the Structure of interactomes with Hierarchical agglomerative clustering” as it proposes a method, HAC, which is described as being able to predict the missing links through identifying groups to be merged and clustered together. Based on the algorithm, we will be able to generate a possible architecture for protein interactions and hence providing a more complete picture of the interactome. The algorithm will be broken down, analysed and then implemented in this project. On top of implementing the algorithm, a Cytoscape plugin will be developed to implement the above mentioned algorithm and its expected to aid in predicting the new proteins from an existing network. The predicted proteins will then be displayed in Cytoscape as a hierarchical graph of binary tree.This visualization of graph hopes to be able to further enhance the user understanding and aid in their analytical work of studying the networks better. The plugin is coded in java on the Cytoscape environment, as a Maven project.