Supporting content for the Living Bacterial Reservoir Computers for Information Processing and Sensing paper

This repository contains code to support the Living Bacterial Reservoir Computers for Information Processing and Sensing publication. See the citation section for details.

Table of Contents

• 1. Repository structure
• 2. Installation
• 3. Citation

1. Repository structure

├── Data        < placeholder for data files >
│   └── ..
├── Library     < supporting code for notebook >
│   └── ..
├── Model       < trained models >
│   └── ..
├── Result
│   └── ..
├── amn.ipynb
├── dataset_species.ipynb
├── ecoli_reservoir.ipynb
├── features_to_media.ipynb
├── plots.ipynb
├── README.md
└── requirements.yml

2. Installation

The following steps will set up a bacterial_rc conda environment.

0. Install Conda

   The conda package manager is required. If you do not have it installed, you can download it from here. Follow the instructions on the page to install Conda. For example, on Windows, you would download the installer and run it. On macOS and Linux, you might use a command like:

   bash ~/Downloads/Miniconda3-latest-Linux-x86_64.sh

   Follow the prompts on the installer to complete the installation.

1. Install dependencies

   1.1. Windows & Linux

   conda env create -f requirements.yml
   conda activate bacterial_rc

   1.2. macOS (Intel processors)

   conda env create -f requirements.yml
   conda activate bacterial_rc
   pip install tensorflow-macos tensorflow-metal

   1.3. macOS (Apple Silicon Mx processors)

   conda env create --platform osx-64 -f requirements.yml
   conda activate bacterial_rc
   conda env config vars set CONDA_SUBDIR=osx-64
   conda deactivate
   conda activate bacterial_rc
   pip install tensorflow-macos tensorflow-metal

2. Download data

   Trained models and most important datasets are available as a Zenodo archive: https://doi.org/10.5281/zenodo.14961167. Extract the files and place them in the Data, Model, Result directory.

3. Citation

If you use this software, please cite it as below.

Living Bacterial Reservoir Computers for Information Processing and Sensing. Paul Ahavi; Thi-Ngoc-An Hoang; Philippe Meyer; Sylvie Berthier; Federica Fiorini; Florence Castelli; Olivier Epaulard; Audrey Le Gouellec; Jean-Loup Faulon. Preprint: https://doi.org/10.1101/2024.09.12.612674.