{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Palazzotti D"],"funding":["Fondazione Umberto Veronesi","Ministero dell'Universit? e della Ricerca"],"pagination":["6309-6315"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9795488"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["62(24)"],"pubmed_abstract":["The recent increase of bioactivity data freely available to the scientific community and stored as activity data points in chemogenomic repositories provides a huge amount of ready-to-use information to support the development of predictive models. However, the benefits provided by the availability of such a vast amount of accessible information are strongly counteracted by the lack of uniformity and consistency of data from multiple sources, requiring a process of integration and harmonization. While different automated pipelines for processing and assessing chemical data have emerged in the last years, the curation of bioactivity data points is a less investigated topic, with useful concepts provided but no tangible tools available. In this context, the present work represents a first step toward the filling of this gap, by providing a tool to meet the needs of end-user in building proprietary high-quality data sets for further studies. Specifically, we herein describe Q-raKtion, a systematic, semiautomated, flexible, and, above all, customizable KNIME workflow that effectively aggregates information on biological activities of compounds retrieved by two of the most comprehensive and widely used repositories, PubChem and ChEMBL."],"journal":["Journal of chemical information and modeling"],"pubmed_title":["Q-raKtion: A Semiautomated KNIME Workflow for Bioactivity Data Points Curation."],"pmcid":["PMC9795488"],"funding_grant_id":["23-G-15435-1"],"pubmed_authors":["Astolfi A","Barreca ML","Fiorelli M","Sabatini S","Massari S","Palazzotti D"],"additional_accession":[]},"is_claimable":false,"name":"Q-raKtion: A Semiautomated KNIME Workflow for Bioactivity Data Points Curation.","description":"The recent increase of bioactivity data freely available to the scientific community and stored as activity data points in chemogenomic repositories provides a huge amount of ready-to-use information to support the development of predictive models. However, the benefits provided by the availability of such a vast amount of accessible information are strongly counteracted by the lack of uniformity and consistency of data from multiple sources, requiring a process of integration and harmonization. While different automated pipelines for processing and assessing chemical data have emerged in the last years, the curation of bioactivity data points is a less investigated topic, with useful concepts provided but no tangible tools available. In this context, the present work represents a first step toward the filling of this gap, by providing a tool to meet the needs of end-user in building proprietary high-quality data sets for further studies. Specifically, we herein describe Q-raKtion, a systematic, semiautomated, flexible, and, above all, customizable KNIME workflow that effectively aggregates information on biological activities of compounds retrieved by two of the most comprehensive and widely used repositories, PubChem and ChEMBL.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Dec","modification":"2025-04-04T03:10:38.606Z","creation":"2025-04-04T03:10:38.606Z"},"accession":"S-EPMC9795488","cross_references":{"pubmed":["36442071"],"doi":["10.1021/acs.jcim.2c01199"]}}