Competitive SWIFT cluster templates enhance detection of aging changes

Clustering‐based algorithms for automated analysis of flow cytometry datasets have achieved more efficient and objective analysis than manual processing. Clustering organizes flow cytometry data into subpopulations with substantially homogenous characteristics but does not directly address the impor...

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Detalles Bibliográficos
Autores principales: Rebhahn, Jonathan A., Roumanes, David R., Qi, Yilin, Khan, Atif, Thakar, Juilee, Rosenberg, Alex, Lee, F. Eun‐Hyung, Quataert, Sally A., Sharma, Gaurav, Mosmann, Tim R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Computational Analysis of Flow Cytometry Data (PART II)
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4737406/
https://www.ncbi.nlm.nih.gov/pubmed/26441030
http://dx.doi.org/10.1002/cyto.a.22740

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4737406/
https://www.ncbi.nlm.nih.gov/pubmed/26441030
http://dx.doi.org/10.1002/cyto.a.22740

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