Author(s)

David Carbonetta

Date Approved

9-23-2014

Embargo Period

9-23-2016

Document Type

Thesis

Degree Name

M.S. Electrical and Computer Engineering

Department

Electrical and Computer Engineering

College

Henry M. Rowan College of Engineering

First Advisor

Tang, Ying

Subject(s)

Information visualization;Computational biology

Disciplines

Electrical and Computer Engineering

Abstract

There has been steady increase in the amount of molecular data generated by experiments and computational methods performed on biological networks. There is a growing need to obtain an insight into the organization and structure of the massive and complex biological networks formed by the interacting molecules. To that end, this work presents the development of an integrated network visualization and graph analysis plugin within the Cytoscape framework. The plugin is capable of computing and visualizing a comprehensive set of dyad, node, and graph level statistics. The evaluation of the plugin on a range of biological networks and its memory performance is conducted. The plugin, proven to be scalable, is an interactive and highly customizable application that expects no prior knowledge in graph theory from the user.

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