drug-repurposing-datasets

Drug Repurposing Datasets for Collaborative Filtering Methods. Notebooks and code to generate datasets for collaborative filtering-based drug repurposing.

https://github.com/recess-eu-project/drug-repurposing-datasets

Science Score: 67.0%

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 11 DOI reference(s) in README
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Academic publication links
Links to: zenodo.org
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Scientific vocabulary similarity
Low similarity (13.8%) to scientific vocabulary

Keywords

collaborative-filtering dataset drug-repurposing science-reproducibility

Last synced: 6 months ago · JSON representation ·

Repository

Drug Repurposing Datasets for Collaborative Filtering Methods. Notebooks and code to generate datasets for collaborative filtering-based drug repurposing.

Basic Info

Host: GitHub
Owner: RECeSS-EU-Project
License: mit
Language: Jupyter Notebook
Default Branch: master
Homepage: https://recess-eu-project.github.io
Size: 190 KB

Statistics

Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 6

Topics

collaborative-filtering dataset drug-repurposing science-reproducibility

Created over 2 years ago · Last pushed about 2 years ago

Metadata Files

Readme License Citation Codemeta Zenodo

Drug Repurposing Datasets for Collaborative Filtering Methods

This repository is a part of the EU-funded RECeSS project (#101102016), and hosts the notebooks and code files which helped to build the following novel drug repurposing datasets:

TRANSCRIPT dataset
PREDICT dataset

The latest versions (v2.0.0 and v2.0.1 of May 29th, 2023) of those datasets correspond to the current notebooks in folder notebooks/. The notebooks corresponding to the v1.0.0 and v1.0.1 (December 28th, 2022) are hosted in folder notebooks/v1.0.0/. To get more details about the datasets themselves, please refer to the corresponding Zenodo pages.

Running the notebooks

Global variables

Update to your liking the following file paths_global.py. The corresponding files and how to obtain them are detailed in notebooks/FEATURELESS_dataset.ipynb.

Environment

In order to run the notebooks:

conda create -n drug_repurposing python=3.8.5 -y conda activate drug_repurposing python3 -m pip install -r requirements.txt python3 -m pip install notebook>=6.5.4 markupsafe==2.0.1 ## packages for Jupyter notebook conda deactivate conda activate drug_repurposing cd notebooks/ && jupyter notebook

Licence

These datasets and code are under an OSI-approved MIT license. Note that the final matrices for PREDICT are not available, due to the usage rules of the DrugBank dataset. However, one can run the corresponding notebook PREDICT_dataset.ipynb in order to get the final matrices. A partial dataset is downloadable on Zenodo.

Citation

Clémence Réda. (2023). Jupyter Notebooks for building drug repurposing datasets in collaborative filtering (v2.0.0). Zenodo. https://doi.org/10.5281/zenodo.8014774

Community guidelines with respect to contributions, issue reporting, and support

Pull requests and issue flagging are welcome, and can be made through the GitHub interface. Support can be provided by reaching out to recess-project[at]proton.me.

Owner

Name: RECeSS EU project
Login: RECeSS-EU-Project
Kind: user
Location: Rostock, Germany
Company: Universität Rostock

Website: http://recess-eu-project.github.io/
Twitter: recess_eu_proj
Repositories: 1
Profile: https://github.com/RECeSS-EU-Project

The RECeSS (Robust Explainable Controllable Standard for drug Screening) project is funded by a Marie Skłodowska-Curie Postdoctoral Fellowship 2022.

Citation (CITATION.cff)

cff-version: 1.0.0
message: "If you use these notebooks, please cite them as below."
authors:
  - family-names: R\'{e}da
    given-names: Cl\'{e}mence
    orcid: https://orcid.org/0000-0003-3238-0258
title: "Jupyter Notebooks for building drug repurposing datasets in collaborative filtering"
version: 2.0.0
doi: "10.5281/zenodo.8014774"
date-released: 2023-06-07

CodeMeta (codemeta.json)

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "license": "https://spdx.org/licenses/MIT",
  "codeRepository": "git+https://github.com/RECeSS-EU-Project/drug-repurposing-datasets.git",
  "dateCreated": "2023-05-29",
  "datePublished": "2023-05-29",
  "dateModified": "2023-05-29",
  "downloadUrl": "https://github.com/RECeSS-EU-Project/drug-repurposing-datasets/archive/refs/heads/master.zip",
  "issueTracker": "https://github.com/RECeSS-EU-Project/drug-repurposing-datasets/issues",
  "name": "drug-repurposing-datasets",
  "version": "2.0.0",
  "identifier": "10.5281/zenodo.8014774",
  "description": "This repository is a part of the EU-funded RECeSS project (#101102016), and hosts the notebooks and code files which helped to build the following novel drug repurposing datasets: TRANSCRIPT dataset (https://doi.org/10.5281/zenodo.7982969) and PREDICT dataset (https://doi.org/10.5281/zenodo.7982964).",
  "applicationCategory": "Drug development",
  "releaseNotes": "This version is updated with versions of the different databases and knowledge as of May 2023.",
  "funding": "RECeSS - Robust Explainable Controllable Standard for drug Screening (101102016)",
  "developmentStatus": "active",
  "isPartOf": "https://recess-eu-project.github.io/",
  "readme": "https://github.com/RECeSS-EU-Project/drug-repurposing-datasets/blob/master/README.md",
  "softwareVersion": "2.0.0",
  "funder": {
    "@type": "Organization",
    "name": "European Union's Horizon 2020 research and innovation programme"
  },
  "keywords": [
    "collaborative filtering",
    "dataset",
    "drug repurposing",
    "science reproducibility"
  ],
  "programmingLanguage": [
    "Python 3"
  ],
  "softwareRequirements": [
    "nordic>=2.4.2",
    "pandas>=1.1.4",
    "numpy>=1.19.4",
    "scipy>=1.5.4",
    "bs4>=0.0.1",
    "pubchempy>=1.0.4",
    "joblib>=1.0.1",
    "epam.indigo>=1.4.3",
    "scikit-learn>=0.24.0",
    "biopython>=1.78",
    "cmapPy>=4.0.1",
    "selenium>=4.9.1",
    "tqdm>=4.58.0",
    "requests-html>=0.10.0",
    "obonet>=0.3.0",
    "networkx>=2.6.3",
    "nbconvert[qtpdf]"
  ],
  "author": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-3238-0258",
      "givenName": "Clmence",
      "familyName": "Rda",
      "email": "clemence.reda@uni-rostock.de",
      "affiliation": {
        "@type": "Organization",
        "name": "Systems Biology and Informatics, University of Rostock, Rostock, Germany"
      }
    }
  ],
  "maintainer": [
    {
      "@type": "Person",
      "@id": "https://orcid.org/0000-0003-3238-0258",
      "givenName": "Clmence",
      "familyName": "Rda",
      "email": "clemence.reda@uni-rostock.de",
      "affiliation": {
        "@type": "Organization",
        "name": "Systems Biology and Informatics, University of Rostock, Rostock, Germany"
      }
    }
  ]
}

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