Modular architecture in biological networks

In the past decade, biology has been revolutionized by an explosion in the availability of data. Translating this new wealth of information into meaningful biological insights and clinical breakthroughs will require a complete overhaul both in the questions being asked, and the methodologies used to answer them. One of the largest challenges in organizing and understanding the data coming from genome sequencing, microarray experiments, and other high-throughput measurements, will be the ability to find large-scale structure in biological systems. Ideally, this would lead to a simplified representation, wherein the thousands of genes in an organism can be viewed as a much smaller number of dynamic modules working in concert to accomplish cellular functions. Toward demonstrating the importance of higher-level, modular structure in biological systems, we have performed the following analyses: 1. Using computational techniques and pre-existing protein-protein interaction (PPI) data, we have developed general tools to find and validate modular structure. We have applied these approaches to the PPI networks of yeast, fly, worm, and human.

Department dc:contributor.department

Harvard University--MIT Division of Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Ramachandran, Gopal (Gopal Sebastian)

Advisor dc:contributor.advisor

• Bonnie A. Berger.

• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/39734
• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Identifier URI

http://dspace.mit.edu/handle/1721.1/39734

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/39734