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# Welcome to QC-Selector's Documentation! | ||
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[selector](https://github.com/theochem/Selector) is a free, open-source, and cross-platform Python library designed to help you effortlessly identify the most diverse subset of molecules from your dataset. Please use the following citation in any publication using selector library: | ||
[Selector](https://github.com/theochem/Selector) is a free, open-source, and cross-platform Python library designed to help you effortlessly identify the most diverse subset of molecules from your dataset. Please use the following citation in any publication using Selector library: | ||
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**"QC-Selector: A Generic Python Package for Subset Selection"**, Fanwang Meng, Alireza Tehrani, Valerii Chuiko, Abigail Broscius, Abdul, Hassan, Maximilian van Zyl, Marco Martínez González, Yang, Ramón Alain Miranda-Quintana, Paul W. Ayers, and Farnaz Heidar-Zadeh" | ||
**"TO be added"** | ||
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The selector source code is hosted on [GitHub](https://github.com/theochem/Selector) and is released under the [GNU General Public License v3.0](https://github.com/theochem/Selector/blob/main/LICENSE). We welcome any contributions to the selector library in accordance with our Code of Conduct; please see our [Contributing Guidelines](https://qcdevs.org/guidelines/QCDevsCodeOfConduct/). Please report any issues you encounter while using selector library on [GitHub Issues](https://github.com/theochem/Selector/issues). For further information and inquiries please contact us at [email protected]. | ||
The Selector source code is hosted on [GitHub](https://github.com/theochem/Selector) and is released under the [GNU General Public License v3.0](https://github.com/theochem/Selector/blob/main/LICENSE). We welcome any contributions to the Selector library in accordance with our Code of Conduct; please see our [Contributing Guidelines](https://qcdevs.org/guidelines/QCDevsCodeOfConduct/). Please report any issues you encounter while using Selector library on [GitHub Issues](https://github.com/theochem/Selector/issues). For further information and inquiries please contact us at [email protected]. | ||
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## Why QC-Selector? | ||
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In the world of chemistry, selecting the right subset of molecules is critical for a wide range of applications, including drug discovery, materials science, and molecular optimization. QC-Selector offers a cutting-edge solution to streamline this process, empowering researchers, scientists, and developers to make smarter decisions faster. | ||
Selecting diverse and representative subsets is crucial for the data-driven models and machine | ||
learning applications in many science and engineering disciplines, especially for molecular design | ||
and drug discovery. Motivated by this, we develop the Selector package, a free and open-source Python library for selecting diverse subsets. | ||
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The Selector library implements a range of existing algorithms for subset sampling based on the | ||
distance between and similarity of samples, as well as tools based on spatial partitioning. In | ||
addition, it includes seven diversity measures for quantifying the diversity of a given set. We also | ||
implemented various mathematical formulations to convert similarities into dissimilarities. | ||
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## Key Features | ||
1. Import Your Dataset: Simply import your molecule dataset in various file formats, including SDF, SMILES, and InChi, to get started. | ||
2. Define Selection Criteria: Specify the desired level of diversity and other relevant parameters to tailor the subset selection to your unique requirements. | ||
3. Run the Analysis: Let QC-Selector's powerful algorithms process your dataset and efficiently select the most diverse molecules. | ||
4. Export: Explore the diverse subset and export the results for further analysis and integration into your projects. | ||
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