Work

Author response: Developing a multivariate prediction model of antibody features associated with protection of malaria-infected pregnant women from placental malaria

Year: 2021

Type: peer-review

Abstract: Machine learning identified six protective antibody features and showed for the first time that serological markers can predict protection from placental-malaria, which is important for evaluation and development of vaccines.

Source: eLife

DOI: 10.7554/elife.65776.sa2

Authors: Elizabeth H Aitken, Timon Damelang, Amaya Ortega-Pajares, Agersew Alemu, Wina Hasang, Saber Dini, Holger W Unger, Maria Ome-Kaius, Morten A Nielsen, Ali Salanti, Joe Smith, Stephen Kent, P Mark Hogarth, Bruce D Wines, Julie A Simpson, Amy W Chung, Stephen J Rogerson

Institutions: The University of Melbourne, Peter Doherty Institute, Menzies School of Health Research, Royal Darwin Hospital, Walter and Eliza Hall Institute of Medical Research, University of Copenhagen, Copenhagen University Hospital, University of Washington, Seattle Children's Research Institute, Burnet Institute, Monash University

Language: English

Topic: Malaria Research and Control

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,500

OpenAlex ID: W4242892317

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Related to: 10