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Correction: Machine learning-based phenotypic imaging to characterise the targetable biology of Plasmodium falciparum male gametocytes for the development of transmission-blocking antimalarials

  • Oleksiy Tsebriy,
  • Andrii Khomiak,
  • Celia Miguel-Blanco,
  • Penny C. Sparkes,
  • Maurizio Gioli,
  • Marco Santelli,
  • Edgar Whitley,
  • Francisco-Javier Gamo,
  • Michael J. Delves

There are errors in the author affiliations. The correct affiliations are as follows:

Oleksiy Tsebriy1, Andrii Khomiak2, Celia Miguel-Blanco3, Penny C. Sparkes4, Maurizio Gioli5, Marco Santelli2, Edgar Whitley6, Francisco-Javier Gamo3, Michael J. Delves4

1 Ternopil Ivan Puluj National Technical University, Ternopil, Ukraine, 2 Independent researcher, Ternopil, Ukraine, 3 Global Health Medicines R&D., GlaxoSmithKline, Madrid, Spain, 4 Department of Infection Biology, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK, 5 SOAS University of London, London, UK, 6 Department of Management, London School of Economics and Political Science, London, UK.

Reference

  1. 1. Tsebriy O, Khomiak A, Miguel-Blanco C, Sparkes PC, Gioli M, Santelli M, et al. Machine learning-based phenotypic imaging to characterise the targetable biology of Plasmodium falciparum male gametocytes for the development of transmission-blocking antimalarials. PLoS Pathog. 2023;19(10):e1011711. pmid:37801466