Welcome to QC-Selector’s Documentation!¶
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:
“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”
The selector source code is hosted on GitHub and is released under the GNU General Public License v3.0. We welcome any contributions to the selector library in accordance with our Code of Conduct; please see our Contributing Guidelines. Please report any issues you encounter while using selector library on GitHub Issues. For further information and inquiries please contact us at qcdevs@gmail.com.
Why QC-Selector?¶
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.
Key Features¶
Import Your Dataset: Simply import your molecule dataset in various file formats, including SDF, SMILES, and InChi, to get started.
Define Selection Criteria: Specify the desired level of diversity and other relevant parameters to tailor the subset selection to your unique requirements.
Run the Analysis: Let QC-Selector’s powerful algorithms process your dataset and efficiently select the most diverse molecules.
Export: Explore the diverse subset and export the results for further analysis and integration into your projects.