{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Martinez-Mauricio KL"],"funding":["Consejo Nacional de Ciencia y Tecnología"],"pagination":["e4928"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10949403"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["33(4)"],"pubmed_abstract":["Molecular features play an important role in different bio-chem-informatics tasks, such as the Quantitative Structure-Activity Relationships (QSAR) modeling. Several pre-trained models have been recently created to be used in downstream tasks, either by fine-tuning a specific model or by extracting features to feed traditional classifiers. In this regard, a new family of Evolutionary Scale Modeling models (termed as ESM-2 models) was recently introduced, demonstrating outstanding results in protein structure prediction benchmarks. Herein, we studied the usefulness of the different-dimensional embeddings derived from the ESM-2 models to classify antimicrobial peptides (AMPs). To this end, we built a KNIME workflow to use the same modeling methodology across experiments in order to guarantee"],"journal":["Protein science : a publication of the Protein Society"],"pubmed_title":["Examining evolutionary scale modeling-derived different-dimensional embeddings in the antimicrobial peptide classification through a KNIME workflow."],"pmcid":["PMC10949403"],"funding_grant_id":["320658"],"pubmed_authors":["Martinez-Mauricio KL","Cordoves-Delgado G","Garcia-Jacas CR"],"additional_accession":[]},"is_claimable":false,"name":"Examining evolutionary scale modeling-derived different-dimensional embeddings in the antimicrobial peptide classification through a KNIME workflow.","description":"Molecular features play an important role in different bio-chem-informatics tasks, such as the Quantitative Structure-Activity Relationships (QSAR) modeling. Several pre-trained models have been recently created to be used in downstream tasks, either by fine-tuning a specific model or by extracting features to feed traditional classifiers. In this regard, a new family of Evolutionary Scale Modeling models (termed as ESM-2 models) was recently introduced, demonstrating outstanding results in protein structure prediction benchmarks. Herein, we studied the usefulness of the different-dimensional embeddings derived from the ESM-2 models to classify antimicrobial peptides (AMPs). To this end, we built a KNIME workflow to use the same modeling methodology across experiments in order to guarantee","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Apr","modification":"2025-04-04T09:07:21.406Z","creation":"2025-04-04T09:07:21.406Z"},"accession":"S-EPMC10949403","cross_references":{"pubmed":["38501511"],"doi":["10.1002/pro.4928"]}}