Welcome to CO-RAD!

Introduction

CO-RAD is a Collaborative Optimization platform with functions of Recommendation，Analysis and Design. Here are the functions in CO-RAD:

• Novel Numerical Simulation. Helpful tool for prediction on the behavior of genetic circuits.
• Search & Recommendation System. The source of your inspiration for synbio design.
• Circuit Designer. Visual toolkit for circuit construction.
• Synchronization Sketchpad. A fantastic remote cooperation platform.
• Management Studio. Your reliable assistant for managing your synbio design!

Powerful toolkit for synthetic biology! Open your a web browser and type in http://sysu-corad.com, and start with CO-RAD public server!

Setup

To set up your own server, please follow the installation guide below:

Dependency

To run CO-RAD, you should get prepared on your server as follow:

1. Make sure your server has over 8GB memory available, while 16GB is recommended. This is crucial for our search system.
2. Python>= 3.6, with main following packages installed:

• Django>= 2.0
• pySBOL==2.3.0.
• tensorflow==1.11.0
• Numpy, xlrd, pandas, sklearn Details for these packages are listed below.

3. (Not required) To activate the search engine based on neutral network, please make sure you have enough available memory (>8GB). Then click here to download the supportive data, unzip and save it at the [ProjectDirectory]\igem2018\search\nn_search, where [ProjectDirectory] is the path of this project.

Installation

• Get Repo Clone the repository from github. With git install, you can type git clone https://github.com/igemsoftware2018/SYSU-Software-2018 in your terminal. Or you can visit our repository and download the source file, unzip it and copy it to your custom directory.

• Installation The main installation process is packed into scripts. Run setup.sh (setup.bat for Windows) for installation. It may take several minutes to load ocean of data to the database. After finishing, simply run runserver.sh(runserver.bat on windows) to let CO-RAD get started to run!

Library

Backend

• Python 3: https://www.python.org/
• Django: https://www.djangoproject.com/
• xlrd: https://github.com/python-excel/xlrd
• pySBOL: https://github.com/SynBioDex/pySBOL
• pandas: https://pandas.pydata.org/
• scikit-learn: http://scikit-learn.org/stable/
• NumPy: http://www.numpy.org/
• SciPy: https://www.scipy.org/

Frontend

• Semantic UI: https://semantic-ui.com/
• jQuery: https://jquery.com/
• jQuery UI: http://jqueryui.com/
• jQuery Mousewheel: https://github.com/jquery/jquery-mousewheel
• jsPlumb: https://jsplumbtoolkit.com/
• eCharts: https://ecomfe.github.io/echarts-doc/public/en/index.html
• D3.js: https://d3js.org/
• AngularJS: https://angularjs.org/
• Angular Plasmid: http://angularplasmid.vixis.com/
• html2canvas: https://html2canvas.hertzen.com/