Team:Heidelberg/Project SaO
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- | :<span style="font-size:10mm;">T</span>he emergence of interest in manipulatable eukaryotic systems has posed much pressure on the development of methods to help understand and characterise eukaryotic gene regulation. Those methods go beyond the already rather sophisticated methodology still being established in prokaryotes to investigate and thereafter engineer these cells as needed.[[Team:Heidelberg/ | + | :<span style="font-size:10mm;">T</span>he emergence of interest in manipulatable eukaryotic systems has posed much pressure on the development of methods to help understand and characterise eukaryotic gene regulation. Those methods go beyond the already rather sophisticated methodology still being established in prokaryotes to investigate and thereafter engineer these cells as needed.[[Team:Heidelberg/Project_SaO#References|[1]]]. For one thing, the design of promoters exclusively responsive to one transcription factor (TF) within eukaryotic cells could certainly help improve our understanding of the key components of one pathway or the other, while eliminating the cross-talk often observed with many naturally occurring promoters. Such promoters have often posed a challenge to researchers studying signal transduction in eukaryotic systems because of the different types of TF a single regulatory element can bind, and a single TF having multiple target regulatory regions (Transcriptional Regulation in Eukaryotes: Concepts, Strategies, and Techniques By Michael Carey, Stephen T. Smale, CSHL press,18-25, 2000, NY). With the emergence of systemized research and attempts for modelling biological systems, the availability of data with minimal experimental variability and highly accurate experimental conditions has also contributed to the need for such finely-tuned promoters. Once such exclusive promoters could be available and methods for their characterization established, it is not so hard to imagine the revolutionary effect they could have on eukaryotic research. Some of many applications could be: |
:*Understanding disease within a network context. | :*Understanding disease within a network context. |
Revision as of 11:41, 19 October 2009
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