Difference between revisions of "Sponsors/MathWorks"
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<hx1 style="font-size:120%; color:#000000; font-weight:bold"> MATLAB and SimBiology in Past iGEMs </hx1> | <hx1 style="font-size:120%; color:#000000; font-weight:bold"> MATLAB and SimBiology in Past iGEMs </hx1> | ||
Revision as of 19:03, 23 March 2016
MathWorks is pleased to sponsor the 2016 iGEM competition. As an iGEM partner, MathWorks will provide complimentary software and technical support to all iGEM teams for use in the competition. Please complete the Software Request Form (must be completed by faculty advisor) to request the complimentary software kit. Learn more about our sponsorship and request complimentary software for use in the competition visit our iGEM competition page.
The complementary software kit includes the following 12 products:
- MATLAB
- Simulink
- SimBiology
- Curve Fitting Toolbox
- Symbolic Math Toolbox
- Optimization Toolbox
- Global Optimization Toolbox
- Bioinformatics Toolbox
- Statistics and Machine Learning Toolbox
- Partial Differential Equation Toolbox
- Image Processing Toolbox
- Computer Vision Toolbox
Getting Started!
Interested in using MATLAB for your in silico projects? We have put together a few video tutorials to help you get started.
- SimBiology and MATLAB for Modeling Synthetic Biology Systems
- Getting started with MATLAB
- Drag-and-drop model-building in SimBiology
- Solving nonlinear differential equations in MATLAB
- SimBiology for modeling and simulating dynamics of synthetic biology systems
For more resources, check out the competition page, product pages, webinars, and additional tutorials.
Technical Mentoring
Can't find what you are looking for? Have a specific question about using MATLAB tools for your iGEM work? We are here to help. Feel free to contact Fulden Buyukozturk via email at fulden.buyukozturk AT mathworks.com to request assistance.
Good luck with your projects!
See how former iGEMers used MathWorks tools, such as MATLAB and SimBiology, for a variety of modeling and simulation projects. A few examples from previous years!
- Team Oxford built stochastic and deterministic models of genetic circuits in order to tackle environmental pollution by developing a device for the detection and degradation of the hazardous yet indispensable solvent dichloromethane (DCM).
- Team KU Leuven modelled the pathway leading to Methyl Salicylate (MeS) production and performed sensitivity analysis, in order to predict MeS production and find the rate limiting steps.
- Team Carnegie Mellon derived an ODE model and used it with experimental time-course data to estimate key parameters like transcriptional and translational efficiency.
- Team Slovenia performed parameter scans to better characterize the effects of the parameters space on the behavior their bistable system, Switch IT.
