Machine Learning-based Phenotypic Imaging to Characterise the Targetable Biology of Plasmodium falciparum Male Gametocytes for Transmission-Blocking Antimalarials

Cellular/molecular imaging dataset — a durable, citable reference into the African DSI DataBank's federated catalog.

Last updated 9/2/2026, 3:41:35 AM

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African DSI DataBank. Machine Learning-based Phenotypic Imaging to Characterise the Targetable Biology of Plasmodium falciparum Male Gametocytes for Transmission-Blocking Antimalarials . AFDSI-CELL-1111. 2026. https://hub.africandsidatabank.africa/cite/AFDSI-CELL-1111 Mirrored from data source: BioImage Archive: https://www.ebi.ac.uk/biostudies/studies/S-BIAD633.Copy citation

@misc{AFDSICELL1111,
  title        = {Machine Learning-based Phenotypic Imaging to Characterise the Targetable Biology of Plasmodium falciparum Male Gametocytes for Transmission-Blocking Antimalarials },
  author       = {{African DSI DataBank}},
  year         = {2026},
  howpublished = {\url{https://hub.africandsidatabank.africa/cite/AFDSI-CELL-1111}},
  note         = {African DSI DataBank citable identifier AFDSI-CELL-1111; Mirrored from data source: BioImage Archive: https://www.ebi.ac.uk/biostudies/studies/S-BIAD633}
}

AFDSI-CELL-1111 is a stable, resolvable local identifier — not a registered DOI. See Terms of use's "Citation policy" for the full explanation.