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Wylie Dissertation Fellowship University of Maryland Center for Health-related Informatics and Bioimaging"},{"DOI":"10.13039\/100000002","name":"U.S. Department of Health & Human Services | National Institutes of Health","doi-asserted-by":"publisher","award":["K01HL14028"],"award-info":[{"award-number":["K01HL14028"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"Department of Health | National Health and Medical Research Council","doi-asserted-by":"publisher","award":["GNT1161066"],"award-info":[{"award-number":["GNT1161066"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University of Maryland Center for Health-related Informatics and Bioimaging grant"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Syst Biol Appl"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Intensive malaria control and elimination efforts have led to substantial reductions in malaria incidence over the past two decades. However, the reduction in <jats:italic>Plasmodium falciparum<\/jats:italic> malaria cases has led to a species shift in some geographic areas, with <jats:italic>P. vivax<\/jats:italic> predominating in many areas outside of Africa. Despite its wide geographic distribution, <jats:italic>P. vivax<\/jats:italic> vaccine development has lagged far behind that for <jats:italic>P. falciparum<\/jats:italic>, in part due to the inability to cultivate <jats:italic>P. vivax<\/jats:italic> in vitro, hindering traditional approaches for antigen identification. In a prior study, we have used a positive-unlabeled random forest (PURF) machine learning approach to identify <jats:italic>P. falciparum<\/jats:italic> antigens based on features of known antigens for consideration in vaccine development efforts. Here we integrate systems data from <jats:italic>P. falciparum<\/jats:italic> (the better-studied species) to improve PURF models to predict potential <jats:italic>P. vivax<\/jats:italic> vaccine antigen candidates. We further show that inclusion of known antigens from the other species is critical for model performance, but the inclusion of only the unlabeled proteins from the other species can result in misdirection of the model toward predictors of species classification, rather than antigen identification. Beyond malaria, incorporating antigens from a closely related species may aid in vaccine development for emerging pathogens having few or no known antigens.<\/jats:p>","DOI":"10.1038\/s41540-024-00465-y","type":"journal-article","created":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T10:51:05Z","timestamp":1731495065000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Plasmodium vivax antigen candidate prediction improves with the addition of Plasmodium falciparum data"],"prefix":"10.1038","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8755-6938","authenticated-orcid":false,"given":"Renee Ti","family":"Chou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1964-7130","authenticated-orcid":false,"given":"Amed","family":"Ouattara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4674-8500","authenticated-orcid":false,"given":"Shannon","family":"Takala-Harrison","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1467-0334","authenticated-orcid":false,"given":"Michael P.","family":"Cummings","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,13]]},"reference":[{"key":"465_CR1","unstructured":"WHO. 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