Difference between revisions of "Team:Marburg/Model"

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                   href="https://2019.igem.org/Team:Marburg/Human_Practices#standardization" target="_blank">different
 
                   href="https://2019.igem.org/Team:Marburg/Human_Practices#standardization" target="_blank">different
 
                 laboratories use different protocols</a> when preparing them. After gathering
 
                 laboratories use different protocols</a> when preparing them. After gathering
                 <a href="https://2019.igem.org/Team:Marburg/Experiments#abstract1" target="_blank">protocols</a>, we decided on four promising ones and tested them we (Figure 7). Off those four media, the
+
                 <a href="https://2019.igem.org/Team:Marburg/Experiments#protocols" target="_blank">protocols</a>, we decided on four promising ones and tested them we (Figure 7). Off those four media, the
 
                 one supporting rapid growth the best was BGM, which was adopted as the main growth medium and replaced
 
                 one supporting rapid growth the best was BGM, which was adopted as the main growth medium and replaced
 
                 BG11. BGM conferred
 
                 BG11. BGM conferred

Revision as of 19:13, 7 December 2019

M O D E L L I N G


The Unreasonable Effectiveness of Mathematics in the Natural Sciences" is the title of a very well-known article published by nobel laureate Eugene Wigner in the 1960s. Although this dictum is common reality in fields such as physics, many biologists still neglect the usefulness of these rigorous methods. This year, our interdisciplinary team has worked hard to change this impression and incorporated many state-of-the-art methods from various scientific fields into the project. We put a high emphasis on standardization which has emerged from a yearning for a meticulous quantitative approach to cyanobacterial research. In particular, our interest laid in determining the optimal growth parameters of our organism S. elongatus as these differed greatly in literature. The development of a state-of-the-art machine learning model allowed us to rapidly speed up this process and guide us towards our ultimate goal. In order to extend our standardization efforts, we additionally implemented a light model to properly predict light intensities for our cultures. Furthermore, modelling played a crucial role in both the search/design of suitable genome integration sites as well as the construction of a synthetic terminator library based on an extensive biophysical model. Without these rigorous analytical methods our project would have been unfeasible.


Growth Curve Model


artificial Neutral integration
Site options


Terminator Model