Quantitative methods for linking transcriptional profiles to physiology

Underlying the current drive towards a systemic study of biology is the tacit assumption that a quantitative relationship can be obtained between molecular markers and macro- scale physiological measurements, which can be utilized to construct predictive models of cellular behavior. This thesis explores the evidence for such quantitative relations, and then illustrates one approach for the construction of models linking phenotype and molecular measurements. Specifically, this thesis focuses on the analysis of gene expression data as generated through DNA microarrays. Through the application of dimensional reduction methods such as PCA, and interactive pattern exploration, evidence for the existence of quantitative relations between gene expression signatures and physiological markers is presented. Subsequently, a large-scale experiment is designed and conducted to provide data sufficiently rich to support the construction of predictive models. The specific system probed in this experiment is the development of insulin resistance in mice models. A bootstrap-based regression framework is then developed for the construction and evaluation of predictive models linking age of the mice and serum insulin and leptin levels to transcriptional profiles. A regression framework has the advantage of avoiding complicated and detailed assumptions regarding mechanistic behavior of the genes involved. In addition, the genes identified through the modeling often have important biological significance.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Misra, Jatin, 1976-

Advisor dc:contributor.advisor

• George Stephanopoulos.

• Chemical Engineering.

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/1721.1/29374

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/29374