Cluster stability in the analysis of mass cytometry data. - Wikidata - awgldk - TriplyDB

Cluster stability in the analysis of mass cytometry data.

Cluster stability in the analysis of mass cytometry data.

http://www.wikidata.org/entity/Q31137446

about

Distinct Cellular Mechanisms Underlie Anti-CTLA-4 and Anti-PD-1 Checkpoint Blockade.Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients.

P2860

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P2860

Cluster stability in the analysis of mass cytometry data.

http://www.wikidata.org/entity/Q31137446

description

2016 nî lūn-bûn

@nan

2016 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2016 թվականի հոտեմբերին հրատարակված գիտական հոդված

@hy

2016年の論文

@ja

2016年論文

@yue

2016年論文

@zh-hant

2016年論文

@zh-hk

2016年論文

@zh-mo

2016年論文

@zh-tw

2016年论文

@wuu

name

Cluster stability in the analysis of mass cytometry data.

@ast

Cluster stability in the analysis of mass cytometry data.

@en

type

label

Cluster stability in the analysis of mass cytometry data.

@ast

Cluster stability in the analysis of mass cytometry data.

@en

prefLabel

Cluster stability in the analysis of mass cytometry data.

@ast

Cluster stability in the analysis of mass cytometry data.

@en

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P356

P1433

Cytometry Part A

P1476

Cluster stability in the analysis of mass cytometry data.

@en

P2093

Alan K Todd

http://www.w3.org/2001/XMLSchema#string

Emanuele de Rinaldis

http://www.w3.org/2001/XMLSchema#string

Filipe Gracio

http://www.w3.org/2001/XMLSchema#string

Rossella Melchiotti

http://www.w3.org/2001/XMLSchema#string

P2860

Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum

Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data

Critical assessment of automated flow cytometry data analysis techniques.

viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.

Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data

Automated identification of stratifying signatures in cellular subpopulations

Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE

Clinical recovery from surgery correlates with single-cell immune signatures.

Phenotypic Complexity of the Human Regulatory T Cell Compartment Revealed by Mass Cytometry.

Deep phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment

P304

73-84

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P31

scholarly article

P356

10.1002/CYTO.A.23001

http://www.w3.org/2001/XMLSchema#string

P433

1

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P478

91

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P50

Shahram Kordasti

P577

2016-10-18T00:00:00Z

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P698

27754590

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