Plugin for reconstructing Boolean models of signaling

• Main Author: Ashok, Pranav.
• Other Authors: School of Computer Engineering
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering::Mathematics of computing::Discrete mathematics
• Online Access: http://hdl.handle.net/10356/52013
• Institution: Nanyang Technological University

In today’s era of faster and powerful computers, the steep increase in high-throughput data needs computational tools capable of integrating data of various types and facilitating recognition of biologically meaningful patterns within them. Since the time when networks of protein-protein interaction were discovered, more than ten years ago, they have been analyzed mainly in their topological aspects. Recently, there have been suggestions of the functional models of these networks, varying from constraint-based ones to Boolean networks. The purpose of this project is to make a plugin that helps in finding out the Boolean model of growth and inflammatory signaling systems and see how the phase of learning can better the model fit to experimental data, and lead to better understanding of the networks. The plugin is made on the programming language Java on the Cytoscape environment as a plugin and LpSolve will be the open source Integer Linear Programming library, which is used for implementing the Integer Linear Programming (ILP) in the algorithm.