{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/classifying-antimicrobial-and-multifunctional","title":"Classifying Antimicrobial and Multifunctional Peptides with Bayesian Network Models","arxiv_id":"1804.06327","date":"2018-04-17","proceeding":null,"authors":["Rainier Barrett","Shaoyi Jiang","Andrew D. White"],"abstract":"Bayesian network models are finding success in characterizing\nenzyme-catalyzed reactions, slow conformational changes, predicting enzyme\ninhibition, and genomics. In this work, we apply them to statistical modeling\nof peptides by simultaneously identifying amino acid sequence motifs and using\na motif-based model to clarify the role motifs may play in antimicrobial\nactivity. We construct models of increasing sophistication, demonstrating how\nchemical knowledge of a peptide system may be embedded without requiring new\nderivation of model fitting equations after changing model structure. These\nmodels are used to construct classifiers with good performance (94% accuracy,\nMatthews correlation coefficient of 0.87) at predicting antimicrobial activity\nin peptides, while at the same time being built of interpretable parameters. We\ndemonstrate use of these models to identify peptides that are potentially both\nantimicrobial and antifouling, and show that the background distribution of\namino acids could play a greater role in activity than sequence motifs do. This\nprovides an advancement in the type of peptide activity modeling that can be\ndone and the ease in which models can be constructed.","url_abs":"http://arxiv.org/abs/1804.06327v1","url_pdf":"http://arxiv.org/pdf/1804.06327v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"classifying-antimicrobial-and-multifunctional","repo_url":"https://github.com/RainierBarrett/pymc3_qspr","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}