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Quantitative proteomics of small numbers of closely-related..:

Kyra van der Pan ; Sara Kassem ; Indu Khatri...
https://www.frontiersin.org/articles/10.3389/fmed.2022.997305/full. , 2022

Link: https://doi.org/10.3389/fmed.2022.997305

RT Journal
T1 <Title>Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:10dcef007c494cce97c498dc3e5d7653&Exemplar=1&LAN=DE
				
A1 Kyra van der Pan
A1 Sara Kassem
A1 Indu Khatri
A1 Arnoud H. de Ru
A1 George M. C. Janssen
A1 Rayman T. N. Tjokrodirijo
A1 Fadi al Makindji
A1 Eftychia Stavrakaki
A1 Anniek L. de Jager
A1 Brigitta A. E. Naber
A1 Inge F. de Laat
A1 Alesha Louis
A1 Wouter B. L. van den Bossche
A1 Lisette B. Vogelezang
A1 Rutger K. Balvers
A1 Martine L. M. Lamfers
A1 Peter A. van Veelen
A1 Alberto Orfao
A1 Jacques J. M. van Dongen
A1 Cristina Teodosio
A1 Paula Díez
PB Frontiers Media S.A.
YR 2022
K1 proteome characterization
K1 low cell numbers
K1 closely-related cells
K1 monocyte
K1 macrophage
K1 paucicellular clinical samples
K1 Medicine (General)
K1 R5-920
JF https://www.frontiersin.org/articles/10.3389/fmed.2022.997305/full
LK http://dx.doi.org/https://doi.org/10.3389/fmed.2022.997305
DO https://doi.org/10.3389/fmed.2022.997305
SF ELIB - SuUB Bremen

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