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This is a complimentary wiki, associated with our repository modeliGEM, for iGEM competition. Visit our iGEM page here! Here you will find information about our material and the core software we have developed to simulate our synthetic system. All of our code is completely free, as in free beer and as in free will. You can find our source files here.
Below, we present a comprehensive guide through our material and code. Our main idea is to spread further several techniques on modeling and simulations for synthetic biology. If you have any comments, suggestions or critics, please do not hesitate contacting us. Let this community grow stronger!
For more information on our Team: https://www.facebook.com/brasilusp
Need help with Python?
- Our methodology - A quick overview on how we are tackling our problems and the philosophy behind it.
- Installing Python with Anaconda (Windows) - A tutorial to help anyone installing Anaconda Python distribution, from Continuum Analytics, on Windows.
- Python Introduction - We have prepared a brief introduction to Python language and ipython notebooks.
- Extra: Women in Science data analysis.
Python for Synthetic Biology
- Data analysis - We will fit some data using scipy and scikit-learn.
- Deterministic Modeling - Using dynamical systems, we model and numerically solve gene expression.
- Stochastic modeling
- Cell populations modeling
Interlab Studies
Bioinformatics
- Simple calibration experiment
- Promoter Tests - we have performed tests to try and check how three different promoters behave.
- Exportation tests - .
- K8 tests
Our software
- Main documentation
- Example
If you are looking for good references on how to model biological systems, especially for synthetic biology, we have a list of papers and books that helped us during our learning.
Introduction
Our methodology
Anaconda Tutorial (Windows)
Python Introduction
References
Fundamentals
Data analysis
Deterministic Modeling
Stochastic modeling
Cell populations modeling
Our software
Main documentation
Example