Team:USTC-Software

From 2011.igem.org

(Difference between revisions)
(Sponsorship)
Line 568: Line 568:
     </div> <!-- end of content --><!-- end of sidebar -->
     </div> <!-- end of content --><!-- end of sidebar -->
      
      
-
   <div class="cleaner"></div>  
+
   <div class="cleaner"></div>
 +
<br/><br/><br/><br/>
-
</div> <div id="content_wrapper_bottom"></div> <!-- end of content_wrapper -->
+
  <h2>Sponsorship</h2>
 +
 
 +
 
 +
  <p align="left"> <img src="https://static.igem.org/mediawiki/2011/b/ba/USTC_Software_IF_LOGO.jpg" width="146" height="142"><strong><em>The University of Science and Technology of China Initiative Foundation</em></strong></p>
 +
  <p align="left"><img src="https://static.igem.org/mediawiki/2011/1/11/USTC_Software_TAO_LOGO.png" width="364" height="71"><strong><em>School of Life Sciences, USTC</em></strong></p>
 +
  <p align="left"><img src="https://static.igem.org/mediawiki/2011/d/d3/USTC_Software_sols.png" width="365" height="63"><strong><em>Teaching Affair Office, USTC</em></strong></p>
 +
  <p align="left"> <img src="https://static.igem.org/mediawiki/2011/e/ef/USTC_Software_ADGE_LOGO.png" width="367" height="68"><strong><em>Graduate School, USTC</em></strong></p>
 +
    </div>
 +
<div id="content_wrapper_bottom"></div> <!-- end of content_wrapper -->
<div id="mfooter">
<div id="mfooter">

Revision as of 03:16, 3 August 2011


USTC_Software 2011

Lachesis

 

view

Assembly View

 

view

Network View

 

view

Behavior View

Project Description

image

USTC 2011 DRY TEAM as a one has worked diligently on designing and implementing a user friendly and interacting-prone software which will get nearer to biology reality and free synthetic biologist from considering unnecessary minutia as well as help both layman and expert draw deep understanding of the mechanism on how the gene circuit run.

We offer a visualizing tool which give insight into the dynamics of a biology network. User dominated parameter adjustment process is also provided to assist in getting the required behavior. In order to assess the network’s immunology to parameter perturbation, a PCA analysis approach is exploited to depict the structure of a “good” behaved region.   




Sponsorship

The University of Science and Technology of China Initiative Foundation

School of Life Sciences, USTC

Teaching Affair Office, USTC

Graduate School, USTC