A methodology for the construction of predictive empirical models of physiological characteristics from microarray data is presented. The method, applied here to the study of the development of diabetes and insulin resistance, can be further expanded to other cases and to also include a variety of other data, such as protein expression, or metabolic flux data. The importance of several of the genes identified by the modeling methodology can be verified by comparison with results from prior literature. This implies potentially significant roles in diabetes for several of the uncharacterized genes discovered during the modeling procedure. / Singapore-MIT Alliance (SMA)
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/3788 |
| Date | 01 1900 |
| Creators | Misra, J., Alevizos, I., Bullen, J., Blueher, S., Mantzoros, C., Stephanopoulos, Gregory |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Article |
| Format | 214097 bytes, application/pdf |
| Relation | Molecular Engineering of Biological and Chemical Systems (MEBCS); |
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