Abstract
The development of cancer reflects the complex interactions and properties of many proteins functioning as part of large biochemical networks within the cancer cell. Although traditional experimental models have provided us with wonderful insights on the behavior of individual proteins within a cancer cell, they have been deficient in simultaneously keeping track of many proteins and their interactions in large networks. Computational models have emerged as a powerful tool for investigating biochemical networks due to their ability to meaningfully assimilate numerous networkproperties. Using the well-studied Ras oncogene as an example, we discuss the use of models to investigate pathologic Ras signaling and describe how these models could play a role in the development of new cancer drugs and the design of individualized treatment regimens.
Original language | English |
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Pages (from-to) | 1510-1513 |
Number of pages | 4 |
Journal | Clinical Cancer Research |
Volume | 15 |
Issue number | 5 |
DOIs | |
State | Published - Mar 1 2009 |