/newma-md

Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)

Primary LanguageJupyter NotebookMIT LicenseMIT

Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)

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This repository contains the script to reproduce the results of the blog post Coronavirus “SARS-CoV-2” conformational change-points detected with optical random features as well as the results of Optical Random Features versus SARS-CoV-2 Glycoprotein Trajectory: Round#2.

Requirements

We advise creating a virtualenv before running these commands. You can create one with python3 -m venv <venv_name>. Activate it with source <path_to_venv>/bin/activate before proceeding. We used python 3.7for all the simulations.

  • Clone the repository and then do pip install -r requirements.txt.
  • Download the dataset from this page. You should put the dataset in the same folder as the repository. Otherwise, make sure to update the variable path traj.

Replicate our results

For replicating the results of Coronavirus “SARS-CoV-2” conformational change-points detected with optical random features: start by running

python newma_coronavirus.py

This outputs a numpy zipped archive. To analyse the results and create your own plot, use the notebook notebooks/corona_exploration.ipynb.

For replicating the results of Optical Random Features versus SARS-CoV-2 Glycoprotein Trajectory: Round#2: start by running

python newma_coronavirus_DESRES.py

This outputs a numpy zipped archive. To analyse the results and create your own plot, use the notebook notebooks/corona_exploration_DESRES.ipynb.

Access to Optical Processing Units

To request access to LightOn Cloud and try our photonic co-processor, please visit: https://cloud.lighton.ai/

For researchers, we also have a LightOn Cloud for Research program, please visit https://cloud.lighton.ai/lighton-research/ for more information.

Hardware Specifications

All our results were obtains on a Intel(R) Xeon(R) Gold 6128 CPU @3.40GHz with 12 cores.