Revision as of 14:05, 26 September 2016

Manchester iGEM 2016

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Modeling

Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.

Inspiration

Here are a few examples from previous teams:

Welcome to our modelling section, we have used a novel ensemble modelling approach, to better aid the synergy between wetlab and dry lab teams. You will find on this page an overview of ensemble modelling and our model and what it achieve. Below there is a flowchart showing how the model worked and the different parts, click on them to find out about the theory and in these sections there are links to code analysis of why we did things these ways and how to do them. There is also a section on the story of what we did and how experiment and human practices fed into the model and vica versa.

Follow this github link to see the full code, feel free to use it. It’s meant to be easy to use. If you can make a simple model you can ensemble model. If you use please attribute us .

Questions you may have (click for more info)

The short version……. Instead of running your model once with some specific parameters, you find all the possible parameters in literature and run your model for lots of combinations in a clever way. By doing this you take into account the uncertainty in your parameters and as such make meaningful conclusions. An example of this is what is your exact reaction scheme, you can run these simulations for different models and see which can be consistent with experimental data. Furthermore by testing your specific parameters set fit to data you can find out what values work and relationships between your parameters, better understanding them and providing physical insight.

We focused on modelling the cell free mechanism. See the experimental section for details, but essentially, Alcohol, alcohol oxidase, horseradish peroxidase and abts are mixed together making oxidised abts which is colourful, click here to see the potential reaction schemes. Click here to be taken to a detailed explanation in the experimental section. The process will work for any model however and this was chosen as a simpler example to demonstrate the technique.

Marc Biarnes Carrera

Firstly we narrowed down the potential reaction schemes and increased our knowledge of our rate constants. Secondly we have created a blueprint for using ensemble modelling instead of simple ODE modelling in the hope that it can become standard practice for iGEM.

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 <h5 id="rossbio">
-In 2015 Ross began a PhD at the University of Manchester in the Manchester Institute of Biotechnology, where he works on post-transcriptional control of gene expression in bacteria. He is also interested in biosensing and multivariate Design of Experiments for the optimisation of synthetic metabolic pathways.<br /><br />
+The short version…….
-Ross graduated from the University of Exeter with a B.Sc. Hons in Biology in 2012, during which he gained work experience at Rothamsted Research. Following this he worked in the Exeter Microbial Biofuels Group, before beginning a M.Sc. by Research at the Shell Technology Centre in Houston, Texas in collaboration with Royal Dutch Shell. Here he worked on consolidated bioprocessing of waste material for biofuel production. Ross is an avid rock climber with a passion for the outdoors and travel.
+Instead of running your model once with some specific parameters, you find all the possible parameters in literature and run your model for lots of combinations in a clever way. By doing this you take into account the uncertainty in your parameters and as such make meaningful conclusions. An example of this is what is your exact reaction scheme, you can run these simulations for different models and see which can be consistent with experimental data. Furthermore by testing your specific parameters set fit to data you can find out what values work and relationships between your parameters, better understanding them and providing physical insight.
 </h5>
@@ Line 67: / Line 67: @@
 <h5 id="nickbio">
-Nick gained a B.Sc. (Hons) Molecular Biology from The University of Manchester before completing a Ph.D. in Chemistry & Biochemistry at the University’s Centre of Excellence in Biocatalysis. He currently works at the Manchester of Institute of Biotechnology where he researches the discovery and engineering of enzymes for use in pharmaceutical and fine chemical synthesis. He is involved in teaching courses introductory and organic chemistry as well as in industrial biotechnology, whilst also coordinating the engagement and outreach initiatives of the institute. In his spare time he enjoys trampolining, gymnastics coaching and playing clarinet in the Manchester Wind Orchestra.
+We focused on modelling the cell free mechanism. See the experimental section for details, but essentially, Alcohol, alcohol oxidase, horseradish peroxidase  and abts are mixed together making oxidised abts which is colourful, click here to see the potential reaction schemes. Click here to be taken to a detailed explanation in the experimental section.
+The process will work for any model however and this was chosen as a simpler example to demonstrate the technique.
 </h5>
@@ Line 76: / Line 77: @@
 <h5 id="marcbio">
-Nick gained a B.Sc. (Hons) Molecular Biology from The University of Manchester before completing a Ph.D. in Chemistry & Biochemistry at the University’s Centre of Excellence in Biocatalysis. He currently works at the Manchester of Institute of Biotechnology where he researches the discovery and engineering of enzymes for use in pharmaceutical and fine chemical synthesis. He is involved in teaching courses introductory and organic chemistry as well as in industrial biotechnology, whilst also coordinating the engagement and outreach initiatives of the institute. In his spare time he enjoys trampolining, gymnastics coaching and playing clarinet in the Manchester Wind Orchestra.
+Firstly we narrowed down the potential reaction schemes and increased our knowledge of our rate constants.
+Secondly we have created a blueprint for using ensemble modelling instead of simple ODE modelling in the hope that it can become standard practice for iGEM.
 </h5

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