Pre-Release AdventML

Pre-release of adventml: advanced optimal enzyme temperature prediction. Models and pipeline will be added soon, keep an eye out!

Pipeline/Update Coming Soon!

Welcome to AdventML!

Table of Contents

• Features
• Prerequisites
• Installation
  • Using Conda Environment with Package Versions
  • Using Conda Environment without Package Versions
  • Using requirements.txt
• Usage
  • Command Line Interface
  • Streamlit Web Interface
• Project Structure
• Contributing
• License
• Contact

Features

• Accurate Predictions: Utilizes advanced machine learning models to predict enzyme temperatures.
• Flexible Input Methods: Supports uploading FASTA files or entering sequences manually.
• Multiple Embedding Types: Choose between esm1b and ProtTransT5XLU50 embeddings.
• GPU Acceleration: Option to leverage GPU for faster computations.
• User-Friendly Interface: Accessible via command line or an intuitive Streamlit web app.

Prerequisites

Before getting started, ensure you have the following installed on your system:

• Conda: Download and install Conda if you haven't already.
• Git: To clone the repository. Download Git if needed.
• CUDA (Optional): If you plan to use GPU acceleration, ensure CUDA is installed and properly configured.

Installation

Follow the steps below to set up your AdventML environment and install the necessary dependencies.

Using Conda Environment with Package Versions

This method ensures reproducibility by installing exact package versions.

1. Clone the Repository

   git clone https://github.com/LegallyOverworked/prerelease_adventml.git
   cd prerelease_adventml