Open Principal Odor Map

Replication of the Principal Odor Map paper by Brian K. Lee et al. (2023) [1]. The model is implemented such that it integrates with DeepChem.

Benchmarks

Installation (Python 3.9 and above)

PyPI based installation

1. pip install openpom

openpom requires cuda verion of dgl libraries
For cuda 11.7, steps below can be followed:

2. pip install dgl==1.1.1 -f https://data.dgl.ai/wheels/cu117/repo.html

Note: If you are using Amazon Linux 2 based OS on EC2 instance, use:

pip install  dgl==1.1.2 -f https://data.dgl.ai/wheels/cu117/repo.html

Github fork based installation

1. Fork the OpenPOM repository and clone the forked repository

git clone https://github.com/YOUR-USERNAME/openpom.git
cd openpom

2. Setup conda environment

   conda create -n open_pom python=3.9
   conda activate open_pom

3. Install openpom

pip install .

or (for developing)

python setup.py develop

4. Install DGL cuda libs

   pip install dgl==1.1.1 -f https://data.dgl.ai/wheels/cu117/repo.html

Getting started

Example notebooks for model training and finetuning are available here.

Contributors:

Aryan Amit Barsainyan, National Institute of Technology Karnataka, India: code, data cleaning, model development
Ritesh Kumar, CSIR-CSIO, Chandigarh, India: data cleaning, hyperparameter optimisation
Pinaki Saha, University of Hertfordshire, UK: discussions and feedback
Michael Schmuker, University of Hertfordshire, UK: conceptualisation, project lead

References:

[1] A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception.

Brian K. Lee, Emily J. Mayhew, Benjamin Sanchez-Lengeling, Jennifer N. Wei, Wesley W. Qian, Kelsie A. Little, Matthew Andres, Britney B. Nguyen, Theresa Moloy, Jacob Yasonik, Jane K. Parker, Richard C. Gerkin, Joel D. Mainland, Alexander B. Wiltschko

Science381,999-1006(2023).DOI: 10.1126/science.ade4401
bioRxiv 2022.09.01.504602; doi: https://doi.org/10.1101/2022.09.01.504602