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<img align="left" src="misc/symbol_name.png" style="width: 25%; height: 25%"/>

This repository implements the hierarchical statistical mechanical (HSM) model described in the paper [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.](nature.com)
This repository implements the hierarchical statistical mechanical (HSM) model described in the paper [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.](https://doi.org/10.1038/s41592-019-0687-1)

An **associated website** is available at [proteinpeptide.io](htttps://proteinpeptide.io). The website is built to facilitate interactions with results from the model including: (1) specific domain-peptide and protein-protein predictions, (2) the resulting networks, and (3) structures colored using the inferred energy functions from the model. Code for the website is available via the parallel repo: [aqlaboratory/hsm-web](https://github.com/aqlaboratory/hsm-web).
An **associated website** is available at [proteinpeptide.io](https://proteinpeptide.io). The website is built to facilitate interactions with results from the model including: (1) specific domain-peptide and protein-protein predictions, (2) the resulting networks, and (3) structures colored using the inferred energy functions from the model. Code for the website is available via the parallel repo: [aqlaboratory/hsm-web](https://github.com/aqlaboratory/hsm-web).

This file documents how this package might be [used](#usage), the [location of associated data](#data), and [other metadata](#reference).

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Options for any script may be listed using the `-h/--help` flag.

Pre-processed / pre-trained data and models may be downloaded from [figshare (doi:10.6084/m9.figshare.11520552)](https://figshare.com/articles/Pre-processed_data_-_Git_Repo_-_HSM/11520552) and should be unpacked at `data/` in this directory. This directory may also be used as an example of how to structure input and output files / directories.
Pre-processed / pre-trained data and models may be downloaded from [figshare (doi:10.6084/m9.figshare.11520552)](https://doi.org/10.6084/m9.figshare.11520552) and should be unpacked at `data/` in this directory. This directory may also be used as an example of how to structure input and output files / directories.

An alternative use case would be to train / re-train a new model in the `train/` code and make new predictions using the `predict/` code.

## Data

As reported, domain-peptide and protein-protein interactions are available via [figshare (doi:10.6084/m9.figshare.10084745)](https://figshare.com/articles/Predictions_-_Domain-Peptide_and_Protein-Protein_Interactions_-_HSM/10084745). In addition, we provide pre-processed data for this repository and the website repository,
As reported, domain-peptide and protein-protein interactions are available via [figshare (doi:10.6084/m9.figshare.10084745)](https://doi.org/10.6084/m9.figshare.10084745). In addition, we provide pre-processed data for this repository and the website repository,

- Raw training data: [figshare - doi:10.6084/m9.figshare.11520297](https://figshare.com/articles/Training_Data_-_Peptide-Binding_Domain-Peptide_Interactions/11520297). Raw domain-peptide training data used to train the core HSM models. Unpack to `data/` in this directory.
- Pre-processed data: [figshare - doi:10.6084/m9.figshare.11520552](https://figshare.com/articles/Pre-processed_data_-_Git_Repo_-_HSM/11520552). Needed to work with this repo.
- Raw training data: [figshare - doi:10.6084/m9.figshare.11520297](https://doi.org/10.6084/m9.figshare.11520297). Raw domain-peptide training data used to train the core HSM models. Unpack to `data/` in this directory.
- Pre-processed data: [figshare - doi:10.6084/m9.figshare.11520552](https://doi.org/10.6084/m9.figshare.11520552). Needed to work with this repo.
- Data supporting the website at [proteinpeptide.io](https://proteinpeptide.io)

## Requirements
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## Reference
Please reference the associated publication:

Cunningham, J.M., Koytiger, G., Sorger, P.K., & AlQuraishi, M. "Biophysical prediction of protein-peptide interactions and signaling networks using machine learning." *Nature Methods* (2020). [doi:](https://doi.org/). ([citation.bib](https://raw.githubusercontent.com/aqlaboratory/hsm/misc/citation.bib))
Cunningham, J.M., Koytiger, G., Sorger, P.K., & AlQuraishi, M. "Biophysical prediction of protein-peptide interactions and signaling networks using machine learning." *Nature Methods* (2020). [doi:10.1038/s41592-019-0687-1](https://doi.org/10.1038/s41592-019-0687-1). ([citation.bib](https://raw.githubusercontent.com/aqlaboratory/hsm/misc/citation.bib))

See also, a **website** at [proteinpeptide.io](https://proteinpeptide.io) for exploring the associated analyses (code: [aqlaboratory/hsm-web](https://github.com/aqlaboratory/hsm-web)).

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