BioCondAI is an open-source project aimed at utilizing artificial intelligence to assist researchers in analyzing and predicting the behavior of biological condensates. This tool combines multi-dimensional features of biological data and applies machine learning methods to provide in-depth insights into the formation, functions, and roles of condensates in diseases.
- Data Integration: Integrates biological small molecule data from various sources, including protein interactions, nucleic acid sequences, and more.
- Condensate Prediction: Utilizes machine learning models to predict the formation of condensates under various conditions.
- Functional Analysis: Offers tools to analyze the potential biological functions of condensates and their roles in diseases.
- Interactive Interface: Provides a user-friendly interface allowing researchers to easily upload data and interpret results.
- Educational Resources: Supplies resources to help users understand the biological background of condensates and the methods for data analysis.
- Clone the repository to your local machine:
git clone https://github.com/yourusername/BioCondAI.git
- Install dependencies:
cd BioCondAI
pip install -r requirements.txt
- Run the application:
python app.py
- Open a browser and visit http://localhost:5000 to start using BioCondAI.
Refer to the User Manual for instructions on how to use BioCondAI for data uploading, model execution, and result analysis.
We welcome all forms of contributions, including but not limited to new feature proposals, code submissions, bug reports, and documentation improvements. Please read our Contribution Guidelines for more information.
This project is licensed under the MIT License. See the LICENSE file for details.
Thanks to all researchers, developers, and users who contributed to BioCondAI.
If you have any questions or suggestions, please submit them through issues or contact the project maintainers.