pemt

Source code and data files for "PEMT: A patent enrichment tool with applicability in drug discovery"

https://github.com/fraunhofer-itmp/pemt

Science Score: 65.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 10 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
    Organization fraunhofer-itmp has institutional domain (www.itmp.fraunhofer.de)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.4%) to scientific vocabulary

Keywords

drug-discovery patent-landscape patent-search
Last synced: 7 months ago · JSON representation ·

Repository

Source code and data files for "PEMT: A patent enrichment tool with applicability in drug discovery"

Basic Info
  • Host: GitHub
  • Owner: Fraunhofer-ITMP
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 9.79 MB
Statistics
  • Stars: 13
  • Watchers: 2
  • Forks: 3
  • Open Issues: 2
  • Releases: 3
Topics
drug-discovery patent-landscape patent-search
Created almost 4 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation Authors

README.md

PEMT: A tool for extracting patent literature in drug discovery
Documentation Status PEMT on PyPI MIT [![DOI:10.1093/bioinformatics/btac716](http://img.shields.io/badge/DOI-110.1093/bioinformatics/btac716-B31B1B.svg)](https://doi.org/10.1093/bioinformatics/btac716)

[!WARNING]
Currently SureCHEMBL has undergone a major restructuring. The tool might not function in that case. The tool will be updated in soon!!

Table of Contents

General Info

PEMT is a patent extractor tool that enables users to retrieve patents relevant to drug discovery. The overall workflow of the tool can be seen in the figure below:

Installation

[comment]: <> (The code can be installed from [PyPI](https://pypi.org/project/clep/) with:)

shell $ pip install pemt

The most recent code can be installed from the source on GitHub with:

shell $ pip install git+https://github.com/Fraunhofer-ITMP/PEMT.git

Alternatively, for developer the tool can be installed in an editable mode as shown below:

shell $ git clone https://github.com/Fraunhofer-ITMP/PEMT.git $ conda create --name pemt python=3.8 $ conda activate pemt $ cd PEMT $ pip install pemt

For developers, the repository can be cloned from GitHub and installed in editable mode with:

shell $ git clone https://github.com/Fraunhofer-ITMP/PEMT.git $ cd PEMT $ pip install -e .

Documentation

Read the official docs for more information.

Input Data Formats

Data

For running PEMT from the gene level, you need the input file with the following structure:

| symbol | uniprot | | ------ | -------- | | HGNCSymbol1 | UniprotID1 | HGNCSymbol2 | UniprotID2 | HGNCSymbol3 | UniprotID3

For running PEMT from the chemical level, you need the input file with the following structure:

| chembl |
| ------ | | ChEMBLID1 | ChEMBLID2 | ChEMBLID3

Note: The data must be in a comma or tab separated file format. If not so, the file should have at least one of the columns shown above.

Usage

In-order to use PEMT, an installation of chromedriver is required.

As mentioned above, the tool has a two-step approach. Each of these steps can be run individually as well as together as show belwo:

  1. Chemical enrichment The following command links chemicals to genes of interest based on causality. In this command it is necessary to indicate whether the file contains uniprot ids or not with the --uniprot or --no-uniprot parameter.

```shell $ pemt run-chemical-extractor --name= --data= --input-type= --uniprot

```

  1. Patent enrichment The following command interlinks chemicals to patent literature publicly available.

shell $ pemt run-patent-extractor --name=<ANALYSIS NAME> --chromedriver-path=<PATH TO CHROMEDRIVER> --os=<OS NAME> --no-chemical

We also allow the flexibility to start the pipeline from this step, if the user has list of chemicals in the right format as indicated above. The user then has to use the tag --chemical and provide a respective --chemical-data path.

  1. PEMT workflow The following command generates the patent enrichment on the gene data where the gene data file is a TSV file containing uniprot identifiers.

shell $ pemt run-pemt --name=<ANALYSIS NAME> --data=<DATA FILE PATH> --input-type=<DATA FILE SEPARATOR> --chromedriver-path=<PATH TO CHROMEDRIVER> --os=<OS NAME>

Issues

If you have difficulties using PEMT, please open an issue at our GitHub repository.

Citation

If you have found PEMT useful in your work, please consider citing: PEMT: A patent enrichment tool for drug discovery.

Yojana Gadiya, Andrea Zaliani, Philip Gribbon, Martin Hofmann-Apitius, PEMT: a patent enrichment tool for drug discovery, Bioinformatics, 2022;, btac716, https://doi.org/10.1093/bioinformatics/btac716

Disclaimer

PEMT is a scientific tool that has been developed in an academic capacity, and thus comes with no warranty or guarantee of maintenance, support, or back-up of data.

Funding

This project has been funded by EOSC-Life which has received funding from the European Union's Horizon 2020 programme under grant agreement number 824087.

Owner

  • Name: Fraunhofer-Institut für Translationale Medizin und Pharmakologie ITMP
  • Login: Fraunhofer-ITMP
  • Kind: organization
  • Location: Germany

ScreeningPort | Schnackenburgallee 114, 22525 Hamburg

Citation (CITATION.cff)

cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Gadiya"
  given-names: "Yojana"
  orcid: "https://orcid.org/0000-0002-7683-0452"
  affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
- family-names: "Andrea"
  given-names: "Zaliani"
  orcid: "https://orcid.org/0000-0002-1740-8390"
  affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
- family-names: "Gribbon"
  given-names: "Philip"
  orcid: "https://orcid.org/0000-0001-7655-2459"
  affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
- family-names: "Hofmann-Apitius"
  given-names: "Martin"
  orcid: "https://orcid.org/0000-0001-9012-6720"
  affiliation: "Fraunhofer-Institutszentrum Schloss Birlinghoven"
title: "Patent EnrichMent tool (PEMT)"
version: 0.0.2
doi: 10.1093/bioinformatics/btac716
date-released: 2022-07-14
url: "https://github.com/Fraunhofer-ITMP/PEMT"
license: MIT License
preferred-citation:
  type: article
  authors:
  - family-names: "Gadiya"
    given-names: "Yojana"
    orcid: "https://orcid.org/0000-0002-7683-0452"
    affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
  - family-names: "Andrea"
    given-names: "Zaliani"
    orcid: "https://orcid.org/0000-0002-1740-8390"
    affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
  - family-names: "Gribbon"
    given-names: "Philip"
    orcid: "https://orcid.org/0000-0001-7655-2459"
    affiliation: "Fraunhofer Institute of Translation Medicine and Pharmacology"
  - family-names: "Hofmann-Apitius"
    given-names: "Martin"
    orcid: "https://orcid.org/0000-0001-9012-6720"
    affiliation: "Fraunhofer-Institutszentrum Schloss Birlinghoven"
  doi: "10.1093/bioinformatics/btac716"
  journal: "Bioinformatics"
  month: 11
  title: "PEMT: A patent enrichment tool for drug discovery"
  year: 2022

GitHub Events

Total
  • Issues event: 1
  • Watch event: 2
  • Push event: 2
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1
Last Year
  • Issues event: 1
  • Watch event: 2
  • Push event: 2
  • Pull request event: 2
  • Fork event: 1
  • Create event: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 3
  • Total pull requests: 3
  • Average time to close issues: 2 days
  • Average time to close pull requests: 10 minutes
  • Total issue authors: 3
  • Total pull request authors: 1
  • Average comments per issue: 0.67
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 26 minutes
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • YojanaGadiya (1)
  • VarIr (1)
  • pacific-ruler (1)
Pull Request Authors
  • YojanaGadiya (3)
Top Labels
Issue Labels
bug (1) enhancement (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 3 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
pypi.org: pemt

A tool for extractor patent literature in drug discovery

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 3 Last month
Rankings
Dependent packages count: 6.6%
Forks count: 17.3%
Stargazers count: 20.5%
Average: 23.0%
Dependent repos count: 30.6%
Downloads: 40.1%
Maintainers (1)
Last synced: 7 months ago

Dependencies

.github/workflows/code-formatter.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v1 composite
setup.py pypi