Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds

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• dc.contributor.author Bajorath, Jürgen
• dc.contributor.author Chávez-Hernández, Ana L.
• dc.contributor.author Duran-Frigola, Miquel, 1985-
• dc.contributor.author Fernández-de Gortari, Eli
• dc.contributor.author Gasteiger, Johann
• dc.contributor.author López-López, Edgar
• dc.contributor.author Maggiora, Gerald M.
• dc.contributor.author Medina-Franco, José L.
• dc.contributor.author Méndez-Lucio, Oscar
• dc.contributor.author Mestres i López, Jordi
• dc.contributor.author Miranda-Quintana, Ramón Alain
• dc.contributor.author Oprea, Tudor I.
• dc.contributor.author Plisson, Fabien
• dc.contributor.author Prieto-Martínez, Fernando D.
• dc.contributor.author Rodríguez-Pérez, Raquel
• dc.contributor.author Rondón-Villarreal, Paola
• dc.contributor.author Saldívar-Gonzalez, Fernanda I.
• dc.contributor.author Sánchez-Cruz, Norberto
• dc.contributor.author Valli, Marilia
• dc.date.accessioned 2023-04-14T06:21:17Z
• dc.date.available 2023-04-14T06:21:17Z
• dc.date.issued 2022
• dc.description.abstract We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries. During the meeting, applications, challenges, and opportunities in drug discovery, de novo drug design, ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) property predictions, organic chemistry, peptides, and antibiotic resistance were discussed. The program along with the recordings of all sessions are freely available at https://www.difacquim.com/english/events/2022-colloquium/ .
• dc.format.mimetype application/pdf
• dc.identifier.citation Bajorath J, Chávez-Hernández AL, Duran-Frigola M, Fernández-de Gortari E, Gasteiger J, López-López E, Maggiora GM, Medina-Franco JL, Méndez-Lucio O, Mestres J, Miranda-Quintana RA, Oprea TI, Plisson F, Prieto-Martínez FD, Rodríguez-Pérez R, Rondón-Villarreal P, Saldívar-Gonzalez FI, Sánchez-Cruz N, Valli M. Chemoinformatics and artificial intelligence colloquium: Progress and challenges in developing bioactive compounds. J Cheminform. 2022 Dec 2;14(1):82. DOI: 10.1186/s13321-022-00661-0
• dc.identifier.doi http://dx.doi.org/10.1186/s13321-022-00661-0
• dc.identifier.issn 1758-2946
• dc.identifier.uri http://hdl.handle.net/10230/56462
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof J Cheminform. 2022 Dec 2;14(1):82
• dc.rights © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword ADME profile
• dc.subject.keyword Antibiotic resistance
• dc.subject.keyword Artificial intelligence
• dc.subject.keyword Career development
• dc.subject.keyword Drug discovery
• dc.subject.keyword Ligand-based drug design
• dc.subject.keyword Machine learning
• dc.subject.keyword Natural products
• dc.subject.keyword Peptides
• dc.subject.keyword Structure-based drug design
• dc.subject.keyword Virtual screening
• dc.title Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion