Exploring genomic medicine using integrative biology

Instead of focusing on the cell, or the genotype, or on any single measurement modality, using integrative biology allows us to think holistically and horizontally. A disease like diabetes can lead to myocardial infarction, nephropathy, and neuropathy; to study diabetes in genomic medicine would require reasoning from a disease to all its various complications to the genome and back. I am studying the process of intersecting nearly-comprehensive data sets in molecular biology, across three representative modalities (microarrays, RNAi and quantitative trait loci) out of the more than 30 available today. This is difficult because the semantics and context of each experiment performed becomes more important, necessitating a detailed knowledge about the biological domain. I addressed this problem by using all public microarray data from NIH, unifying 50 million expression measurements with standard gene identifiers and representing the experimental context of each using the Unified Medical Language System, a vocabulary of over 1 million concepts. I created an automated system to join data sets related by experimental context.

Department dc:contributor.department

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

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Butte, Atul J

Advisor dc:contributor.advisor

• Isaac Kohane.

• 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/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/33680

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/33680