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Maloadis

http://maloadis.sysu-software.com

Environment

  • OS: Ubuntu 18.04
  • SDKs & Softwares: MySQL 8.0.22, Python 3.7, .NET 5 RC2 SDK, gcc-10, g++-10, nodejs 13, yarn
  • Important Notes: Please make sure your MySQL installation has a user named root with no password.

Install Packages

sudo apt install libboost-dev libboost-all-dev libmysqlcppconn-dev libjsoncpp-dev cmake git build-essential
python -m pip install keras==2.3.1 tensorflow==1.15.4 opencv-python Pillow matplotlib numpy==1.18.5 flask flask-cors mysql-connector-python Bayesian-Optimization scikit-learn==0.22.2 sh pySBOL fuzzywuzzy scipy

Build Software

cd Search/roadmapSearch
mkdir build && cd build
cmake .. -DCMAKE_CXX_FLAGS=-std=c++2a
make -j8

cd ../GenenetSearch
mkdir build && cd build
cmake .. -DCMAKE_CXX_FLAGS=-std=c++2a
make -j8
cp genenet_search ../../Backend/genenet/search

Import Database

cd Database/genenetDB
unzip genenetDB-dumps.zip
mysql -u root < genenetDB-dumps.sql

cd ../
unzip roadmapDB-dumps.zip
mysql -u root < roadmapDB-dumps.sql

Run Server

Run Backend

cd Backend
dotnet run -c Release --urls http://0.0.0.0:5000

Run Search Service

cd Search/SearchAPI/src
python app.py

Run Object Detection Service

cd Backend/yolov4
python predict.py

Configure Designer

In Designer/src/config.ts, please replace the following lines with your actual server http address:

const Config = {
    searchUri: '<your server http address>:5001',
    regonUri: '<your server http address>:5000'
};

export default Config;

Assuming your server address is http://123.123.123.123, you should modify the file to:

const Config = {
    searchUri: 'http://123.123.123.123:5001',
    regonUri: 'http://123.123.123.123:5000'
};

export default Config;

If you are doing above things on your local computer, you can use http://localhost as your server http address hence your config file should be:

const Config = {
    searchUri: 'http://localhost:5001',
    regonUri: 'http://localhost:5000'
};

export default Config;

Run Designer

cd Designer
yarn
yarn start

Congratulations! Now you are ready to go, to use the software, you can access http://localhost:3000.

iGEM-CNN-Regression: Deep Learning: TF & Binding Sites Affinity Prediction.

Make prediction within one line!

python predict.py YOUR_TF YOUR_DNA

We've made it a sepreated open-source project, source codes in iGEM-CNN-Regression directory of this repository is the first version and may be relatively old.

For the latest version, please refer to our project repository iGEM-CNN-Regression.

Our deep learning frame is shown below:
CNN_pic