qsarify


Nameqsarify JSON
Version 0.1.1 PyPI version JSON
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SummaryQSARify: A tool for QSAR model development
upload_time2023-10-25 11:44:26
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keywords qsar cheminformatics machine learning
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            # qsarify

qsarify is a library of tools for the analysis of QSAR/QSPR datasets and models. This library is intended to be used to produce models which relate a set of calculated chemical descriptors to a given numeric endpoint. Many great tools will take the geometry or string data of a given chemical and compute **descriptors**, which are numeric measures of the properties of these, but you can generate some of these with another one of my scripts, [Free Descriptors](https://github.com/StephenSzwiec/free_descriptors).

# Dependencies

- Python 3
- [numpy](https://numpy.org/)
- [pandas](https://pandas.pydata.org/)
- [scikit-learn](https://scikit-learn.org)
- [matplotlib](https://matplotlib.org)


# Installation

`pip install qsarify`

# What is included right now?

- Data preprocessing tools: `data_tools`
- Dimensionality reduction via clustering: `clustering`
- Feature selection:
	- Single threaded: `feature_selection_single`
	- Multi-threaded: `feature_selection_multi`
- Model Export and Visualization: `model_export`
- Cross Valiidation: `cross_validation`

# How to use

The best way to learn how to use this library is to look at the example notebook in the `examples` folder. This notebook will walk you through the workflow of using this library to build a QSAR model.

# Future Plans

- Massively parallel feature selection methods:
	- CUDA acceleration
	- MPI acceleration
- Include Shannon Entropy as a dimensionality reduction metric in clustering
- Embedded kernel methods
- More visualization tools
- More cross validation tools
- Feature selection tools for categorical data

# Contributing


If you would like to contribute to this project, please feel free to fork this repository and submit a pull request. Otherwise, you may also submit an issue. I will try to respond to issues as quickly as possible.

# License


This project is licensed under the GNU GPLv3 license. See the LICENSE file for more details.

# Citation

If you use this library in your work, please cite it as follows:

Szwiec, Stephen. (2023). qsarify: A high performance library for QSAR model development.

BibTex:
```
@misc{szwiec2023qsarify,
  author = {Szwiec, Stephen},
  title = {qsarify: A high performance library for QSAR model development},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/stephenszwiec/qsarify}},
  }
```

            

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