Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data

Fonseca, André; Spytek, Mikolaj; Biecek, Przemysław; Cordeiro, Clara; Sepúlveda, Nuno

http://hdl.handle.net/10400.1/20396

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Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The analysis of these data is typically divided into a feature selection phase followed by a predictive one where several models are constructed for predicting the outcome of interest. A key question in the analysis is to determine which antibodies should be included in the predictive stage and whether they should be included in the original or a transformed scale (i.e. binary/dichotomized).