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pyton package for accessing protein distribution data.

Project description

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protein-distribution: protein variability of CYP, UGT, ABC and SLC in human liver

GitHub Actions CI/CD Status Current PyPI Version Supported Python Versions GNU Lesser General Public License 3 Codecov Black mypy

The objective of this project is to provide a systematic overview of protein variability of CYP450, UGT, ABC and SLC isoforms in the human liver. Relationships within protein isoforms (e.g., subgroups such as sex or ethnicity) and between CYP450 isoforms (e.g., correlations) will be studied. The project will provide an important resource to elucidate factors affecting individual drug metabolism and for computational modeling of drug detoxification by the liver.

An interactive web application is available from https://github.com/matthiaskoenig/protein-distribution-app.

License

The protein-distribution source is released under both the GPL and LGPL licenses version 2 or later. You may choose which license you choose to use the software under.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License or the GNU Lesser General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Funding

Matthias König is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054) and by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151 “QuaLiPerF (Quantifying Liver Perfusion-Function Relationship in Complex Resection - A Systems Medicine Approach)” by grant number 436883643 and by grant number 465194077 (Priority Programme SPP 2311, Subproject SimLivA).

© 2022-2023 Afruja Hossain, Sophie Silberhorn & Matthias König

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