Cargando…
IceR improves proteome coverage and data completeness in global and single-cell proteomics
Label-free proteomics by data-dependent acquisition enables the unbiased quantification of thousands of proteins, however it notoriously suffers from high rates of missing values, thus prohibiting consistent protein quantification across large sample cohorts. To solve this, we here present IceR (Ion...
Autores principales: | Kalxdorf, Mathias, Müller, Torsten, Stegle, Oliver, Krijgsveld, Jeroen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352929/ https://www.ncbi.nlm.nih.gov/pubmed/34373457 http://dx.doi.org/10.1038/s41467-021-25077-6 |
Ejemplares similares
-
Automated sample preparation with SP3 for low‐input clinical proteomics
por: Müller, Torsten, et al.
Publicado: (2020) -
Protease‐resistant streptavidin for interaction proteomics
por: Rafiee, Mahmoud‐Reza, et al.
Publicado: (2020) -
ATRT-13. An integrative analysis of the ATRT proteome unravels novel drug targets and refines molecular subgrouping
por: Johann, Pascal, et al.
Publicado: (2022) -
Global changes of the RNA-bound proteome during the maternal-to-zygotic transition in Drosophila
por: Sysoev, Vasiliy O., et al.
Publicado: (2016) -
Should Drug Companies Engage with ICER? An Empirical Analysis of How Often Manufacturers Engage with ICER and Whether Engagement May Influence ICER’s Cost-Effectiveness Estimates
por: Breslau, Rachel Milstein, et al.
Publicado: (2022)