Metadata-Version: 2.1
Name: adabmDCA
Version: 0.1.5
Summary: Python implementation of Direct Coupling Analysis
Home-page: https://github.com/spqb/adabmDCA
Author: Lorenzo Rosset, Roberto Netti, Anna Paola Muntoni, Francesco Zamponi, Martin Weigt
Author-email: rosset.lorenzo@gmail.com
Maintainer: Lorenzo Rosset
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib ==3.9.2
Requires-Dist: numpy ==2.1.3
Requires-Dist: pandas ==2.2.3
Requires-Dist: torch ==2.5.1
Requires-Dist: tqdm ==4.67.0

# adabmDCA 2.0 - Direct Coupling Analysis in Python

**Authors:**  
- **Lorenzo Rosset** (Sorbonne Université, Sapienza Università di Roma)
- **Roberto Netti** (Sorbonne Université)
- **Anna Paola Muntoni** (Politecnico di Torino)
- **Martin Weigt** (Sorbonne Université)
- **Francesco Zamponi** (Sapienza Università di Roma)
  
**Maintainer:** Lorenzo Rosset

## Overview

**adabmDCA 2.0** is a flexible yet easy-to-use implementation of Direct Coupling Analysis (DCA) based on Boltzmann machine learning. This package provides tools for analyzing residue-residue contacts, predicting mutational effects, scoring sequence libraries, and generating artificial sequences, applicable to both protein and RNA families. The package is designed for flexibility and performance, supporting multiple programming languages (C++, Julia, Python) and architectures (single-core/multi-core CPUs and GPUs).  
This repository contains the Python GPU version of adabmDCA, maintained by **Lorenzo Rosset**.

The project's main repository can be found at [adabmDCA 2.0](https://github.com/spqb/adabmDCA.git).

## Features

- **Direct Coupling Analysis (DCA)** based on Boltzmann machine learning.
- Support for **dense** and **sparse** generative DCA models.
- Available on multiple architectures: single-core and multi-core CPUs, GPUs.
- Ready-to-use for **residue-residue contact prediction**, **mutational-effect prediction**, and **sequence design**.
- Compatible with protein and RNA family analysis.

## Installation

### Option 1: Install from PyPI
Open a terminal and run
```bash
pip install adabmDCA
```

### Option 2: Install from the GitHub repository
Clone the repository locally and then install the requirements and the package. In a terminal, run:

```bash
git clone git@github.com:spqb/adabmDCApy.git
cd adabmDCApy
pip install .
```

## Usage

After installation, all the main routines can be launched though the script `adabmDCA.sh` or directly form the terminal using the command `adabmDCA`.

To get started with adabmDCA in Python, please refer to the [Documentation](https://spqb.github.io/adabmDCApy/) or the [Colab notebook](https://colab.research.google.com/drive/1l5e1W8pk4cB92JAlBElLzpkEk6Hdjk7B?usp=sharing).

## License

This package is open-sourced under the MIT License.

## Citation

If you use this package in your research, please cite:

> Rosset, L., Netti, R., Muntoni, A.P., Weigt, M., & Zamponi, F. (2024). adabmDCA 2.0: A flexible but easy-to-use package for Direct Coupling Analysis.

## Acknowledgments

This work was developed in collaboration with Sorbonne Université, Sapienza Università di Roma, and Politecnico di Torino.


