dc.contributor.authorAshok, Pranav.
dc.description.abstractIn 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.en_US
dc.format.extent47 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineering::Mathematics of computing::Discrete mathematicsen_US
dc.titlePlugin for reconstructing Boolean models of signalingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.researchBioinformatics Research Centreen_US
dc.contributor.supervisor2Zheng Jieen_US

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