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+ | 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. | ||
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Revision as of 13:49, 26 September 2016
★ ALERT!
This page is used by the judges to evaluate your team for the Best Model award.
Delete this box in order to be evaluated for this medal. See more information at Instructions for Pages for awards.
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 .