Searching, retrieving, and analyzing chemical information are among the main tasks faced by students and professionals in chemistry-related scientific disciplines. Currently, freely available modules developed in programming languages, such as Python, allow efficient data management and facilitate the obtaining of information and knowledge from the data. This article describes an electronic handbook generated on the GitBook platform to introduce the Python programming language and the analysis, computational representation, and visualization of chemical data. This manual explores the most common molecular representations of low molecular weight organic compounds and their applications in various contexts. It also illustrates the acquisition of chemical data from large public molecular databases such as ChEMBL and PubChem and the analysis and visualization of chemical information using concepts such as chemical space. The GitBook is freely available (https://difacquim.gitbook.io/quimioinformatica/) and is expected to foster open science and facilitate learning for chemistry students at the undergraduate and graduate levels, as well as professionals interested in chemical data analysis and visualization.
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Saldivar-González, F. I., Prado-Romero, D. L., Cedillo-González, R., Chávez-Hernández, A. L., Avellaneda-Tamayo, J. F., Gómez-García, A., … Medina-Franco, J. L. (2024). A Spanish Chemoinformatics GitBook for Chemical Data Retrieval and Analysis Using Python Programming. Journal of Chemical Education, 101(6), 2549–2554. https://doi.org/10.1021/acs.jchemed.4c00041
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