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Machine-learning analysis of flow or mass cytometry using self-organizing maps. Clusters require biological annotation and do not replace instrument or panel quality control.
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Machine-learning analysis of flow or mass cytometry using self-organizing maps. Clusters require biological annotation and do not replace instrument or panel quality control.
Información cotejada con una fuente oficial; no es un ensayo experimental directo. Fuente · Última revisión: 14/09/2026, 18:31:56 UTC
Use this citation format when referencing FlowSOM in scientific publications and benchmark papers.
@software{flowsom_2026,
title = {{FlowSOM}},
author = {{FlowSOM contributors}},
year = {2026},
url = {https://bioconductor.org/packages/FlowSOM/},
note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}Live scientific citations queried from Europe PMC and PubMed for FlowSOM.
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FlowSOM Scientific Architecture · Credit: FlowSOM contributors · Open original ↗
Research and editorial use Source & attribution ↗ License ↗
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