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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.](https://doi.org/10.1038/s41592-019-0687-1)
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](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). Note that the results on the website were obtained using an [old model](#model-updates).

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

To reproduce analysis and figures presented in the paper [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.](https://doi.org/10.1038/s41592-019-0687-1), use the scripts in `publication_analysis/`.
To reproduce analysis and figures presented in the paper [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning](https://doi.org/10.1038/s41592-019-0687-1), use the scripts in `publication_analysis/`.

Pre-trained models are released with this repo. 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.

### Model updates

We identified an issue in the original datasets used to train the model published in [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.](https://doi.org/10.1038/s41592-019-0687-1). As of February 15, 2023, we have corrected the datasets (released on [figshare (doi:10.6084/m9.figshare.22105529)](https://doi.org/10.6084/m9.figshare.22105529)), and replaced the original models released with this repo with corrected ones. Please verify that you use the corrected models for all predictions (see documentation in `predict/`).
We identified an issue in the original datasets used to train the model published in [Biophysical prediction of protein-peptide interactions and signaling networks using machine learning](https://doi.org/10.1038/s41592-019-0687-1). We have released corrected datasets on [figshare (doi:10.6084/m9.figshare.22105529)](https://doi.org/10.6084/m9.figshare.22105529) (published on February 16, 2023), and replaced the original models released with this repo with corrected ones (on January 9, 2023). Please verify that you use the corrected models for all predictions (see documentation in `predict/`).

## Data

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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](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)).
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)). Note that the results on the website were obtained using an [old model](#model-updates).

## Funding

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