Exploring genomic medicine using integrative biology

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2004.

Bibliographic Details
Main Author: Butte, Atul J
Other Authors: Isaac Kohane.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2006
Subjects:
Online Access:http://hdl.handle.net/1721.1/33680
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author Butte, Atul J
author2 Isaac Kohane.
author_facet Isaac Kohane.
Butte, Atul J
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spelling mit-1721.1/336802019-04-12T12:40:05Z Exploring genomic medicine using integrative biology Butte, Atul J Isaac Kohane. Harvard University--MIT Division of Health Sciences and Technology. Harvard University--MIT Division of Health Sciences and Technology. Harvard University--MIT Division of Health Sciences and Technology. Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2004. Includes bibliographical references (p. 215-227). 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. (cont.) I evaluated this system by finding genes significantly involved in multiple experiments directly and indirectly related to diabetes and adipogenesis and found genes known to be involved in these diseases and processes. As a model first step into integrative biology, I then took known quantitative trait loci in the rat involved in glucose metabolism and build an expert system to explain possible biological mechanisms for these genetic data using the modeled genomic data. The system I have created can link diseases from the ICD-9 billing code level down to the genetic, genomic, and molecular level. In a sense, this is the first automated system built to study the new field of genomic medicine. by Atul Janardhan Butte. Ph.D. 2006-07-31T15:22:57Z 2006-07-31T15:22:57Z 2004 2004 Thesis http://hdl.handle.net/1721.1/33680 64584227 eng 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. http://dspace.mit.edu/handle/1721.1/7582 227 p. 12369532 bytes 12379139 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
spellingShingle Harvard University--MIT Division of Health Sciences and Technology.
Butte, Atul J
Exploring genomic medicine using integrative biology
title Exploring genomic medicine using integrative biology
title_full Exploring genomic medicine using integrative biology
title_fullStr Exploring genomic medicine using integrative biology
title_full_unstemmed Exploring genomic medicine using integrative biology
title_short Exploring genomic medicine using integrative biology
title_sort exploring genomic medicine using integrative biology
topic Harvard University--MIT Division of Health Sciences and Technology.
url http://hdl.handle.net/1721.1/33680
work_keys_str_mv AT butteatulj exploringgenomicmedicineusingintegrativebiology