Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Flow Cytometry Standard"'
Publikováno v:
Journal of Applied Hematology, Vol 12, Iss 2, Pp 83-89 (2021)
BACKGROUND: Automated hematology analyzers effectively reduce turnaround time and generates scattergrams which can be used to screen for different hematological conditions. AIMS: We wish to study the scattergrams generated by the Sysmex XN-series ana
Externí odkaz:
https://doaj.org/article/ed8fe2a5accc48698dac3d2ec27111cd
Autor:
Sebastian Attig, Matthew Adamow, Lisa K. McNeil, Elizabeth Reap, Pamela Norberg, Sylvia Janetzki, Leah Price, Peter E. Fecci
Publikováno v:
Cytometry Part A. 99:107-116
Results from the first gating proficiency panel of intracellular cytokine staining (ICS) highlighted the value of using a consensus gating approach to reduce the variability across laboratories in reported %CD8+ or %CD4+ cytokine-positive cells. Base
Publikováno v:
Cytometry
Cytometry Part A, 97(11), 1180-1186. Wiley-Liss Inc.
Cytometry Part A, 97(11), 1180-1186. Wiley-Liss Inc.
When it comes to data storage, the field of flow cytometry is fairly standardized, thanks to the flow cytometry standard (FCS) file format. The structure of FCS files is described in the FCS specification. Software that strictly complies with the FCS
Autor:
Shreyam Acharya, Kundan Kumar, Abhirup Sarkar, Arulselvi Subramanian, Anita Chopra, Aparna Ningombam
Publikováno v:
Indian J Hematol Blood Transfus
Malaria, an important parasitic disease worldwide, still has diagnostic challenges in the laboratory. Many studies have been conducted on the detection ability of haematology analysers for malaria. We evaluated the Sysmex XN-series analyser as a tool
Publikováno v:
Cytometry Part A. 93:848-853
The Flow Cytometry Standard (FCS) format is a widely accepted norm for storing Flow Cytometry (FCM) data. Its goal as a standard is to allow FCM data sharing and re-analysis. Over more than three decades of its existence FCS has evolved into a well-d
Akademický článek
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Automated analysis of acute myeloid leukemia minimal residual disease using a support vector machine
Autor:
Cuiping Zheng, Qing-qing Li, Yin Tong, Xiangmin Tong, Lei Wang, Wanmao Ni, Yong Han, Beili Hu
Publikováno v:
Oncotarget
// Wanmao Ni 1 , Beili Hu 2 , Cuiping Zheng 3 , Yin Tong 4 , Lei Wang 1 , Qing-qing Li 1 , Xiangmin Tong 1 , Yong Han 1 1 Key Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang Province, Zhejiang Provincial People’s Hos
Autor:
John T. Sexton, Evan J Olson, Oleg A. Igoshin, Jeffrey J. Tabor, Brian P. Landry, Sebastian M. Castillo-Hair
Publikováno v:
ACS Synthetic Biology. 5:774-780
Flow cytometry is widely used to measure gene expression and other molecular biological processes with single cell resolution via fluorescent probes. Flow cytometers output data in arbitrary units (a.u.) that vary with the probe, instrument, and sett
Autor:
Cesar Angeletti
Publikováno v:
Journal of Pathology Informatics
Journal of Pathology Informatics, Vol 9, Iss 1, Pp 16-16 (2018)
Journal of Pathology Informatics, Vol 9, Iss 1, Pp 16-16 (2018)
Background: Flow cytometry analysis is the method of choice for the differential diagnosis of hematologic disorders. It is typically performed by a trained hematopathologist through visual examination of bidimensional plots, making the analysis time-
Publikováno v:
Journal of investigative dermatology, 137(5), e43-e51. Nature Publishing Group
Mass cytometry by time-of-flight experiments allow analysis of over 40 functional and phenotypic cellular markers simultaneously at the single-cell level. The data dimensionality escalation accentuates limitations, inherent to manual analysis, as bei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd7563b98fcdd3a7aeaa25f2fd19090d
https://pure.amc.nl/en/publications/research-techniques-made-simple-mass-cytometry-analysis-tools-for-decrypting-the-complexity-of-biological-systems(0554c5a4-f1bd-4605-a9b3-f353b0b04569).html
https://pure.amc.nl/en/publications/research-techniques-made-simple-mass-cytometry-analysis-tools-for-decrypting-the-complexity-of-biological-systems(0554c5a4-f1bd-4605-a9b3-f353b0b04569).html