Data analysis in flow cytometry: the future just started. - Wikidata - awgldk - TriplyDB

Data analysis in flow cytometry: the future just started.

Data analysis in flow cytometry: the future just started.

http://www.wikidata.org/entity/Q33618094

about

Flow cytometry bioinformatics Data reduction for spectral clustering to analyze high throughput flow cytometry data EuroFlow standardization of flow cytometer instrument settings and immunophenotyping protocols Algorithmic Tools for Mining High-Dimensional Cytometry Data Intraocular lymphoma: a clinical perspective Inherent low Erk and p38 activity reduce Fas Ligand expression and degranulation in T helper 17 cells leading to activation induced cell death resistance Quantitative characterization of cellular membrane-receptor heterogeneity through statistical and computational modeling Anti-TNF-α Drugs Differently Affect the TNFα-sTNFR System and Monocyte Subsets in Patients with Psoriasis GenePattern flow cytometry suite iNKT Cells in Secondary Progressive Multiple Sclerosis Patients Display Pro-inflammatory Profiles.Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.Graphical analysis of flow cytometer data for characterizing controlled fluorescent protein display on λ phage.Critical assessment of automated flow cytometry data analysis techniques.Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data.The end of gating? An introduction to automated analysis of high dimensional cytometry data.Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data.T-cell activation discriminates subclasses of symptomatic primary humoral immunodeficiency diseases in adults Understanding health and disease with multidimensional single-cell methods Rapid cell population identification in flow cytometry data High-dimensional CyTOF analysis of dengue virus-infected human DCs reveals distinct viral signatures An automated analysis of highly complex flow cytometry-based proteomic data.Multivariate analysis of flow cytometric data using decision trees Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry A computational framework to emulate the human perspective in flow cytometric data analysis.Preparing a Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) compliant manuscript using the International Society for Advancement of Cytometry (ISAC) FCS file repository (FlowRepository.org).SPICE: exploration and analysis of post-cytometric complex multivariate datasets Leukemia prediction using sparse logistic regression.The human condition: an immunological perspective.High Reproducibility of ELISPOT Counts from Nine Different Laboratories.Complexity and challenges in defining myeloid-derived suppressor cells Uncompensated Polychromatic Analysis of Mitochondrial Membrane Potential Using JC-1 and Multilaser Excitation.Multidimensional Clusters of CD4+ T Cell Dysfunction Are Primarily Associated with the CD4/CD8 Ratio in Chronic HIV Infection Adenosine A1 receptors contribute to immune regulation after neonatal hypoxic ischemic brain injury.PD-1 Blockade Expands Intratumoral Memory T Cells.Evaluation of the reactive T-cell infiltrate in uveitis and intraocular lymphoma with flow cytometry of vitreous fluid (an American Ophthalmological Society thesis).Cellular Microbiology of Mycoplasma canis.Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples.Asymmetric-detection time-stretch optical microscopy (ATOM) for ultrafast high-contrast cellular imaging in flow.Flow cytometric characterization of cerebrospinal fluid cells.

P2860

Q21045422-47AB0034-0F5D-4FC5-9419-F750C75EB084 Q21284349-28BF3AD6-C3E5-420A-A8A2-E3606EFC489D Q24604720-A0DF3E09-A06D-4F9A-88E1-BD3233C5E365 Q26799355-62B2C1F5-63A9-47E1-BEE7-DAECC6F33008 Q26827115-E747609C-4735-4B17-AD3D-54FF6AD86F1A Q28277617-A692596B-0B27-4D29-92D9-7FF0C7785880 Q28538791-EA3A8C0B-BA17-43F4-B398-E20DB13804A4 Q28554923-7F5D5C08-D623-47B7-A89C-8DB200BDF9D4 Q30177554-012DBBF9-F429-4BE9-9B78-FC493863B7C2 Q30368046-2F805F63-AE61-4C8F-A800-140049283F9B Q30512377-3DEA167B-B568-4CC6-8D9E-B4D2496F89B7 Q30571617-FA8A9D5C-F6E1-4382-AA1B-013AE63BD958 Q30587564-DF1CC43F-9543-4BCC-BBD8-DD54A17A02CC Q30834407-38396728-5C16-4DC2-8FA4-C4FBE47D395D Q30836153-EEB47ADF-64D2-424E-AFEA-3ED4936E4452 Q31019645-C4AC945F-7D59-4853-B1B0-2E291C722C27 Q31114708-1EE5AA3C-129E-4FFA-AF1A-BEFAE6C72137 Q33559219-165DEB3D-42BB-486F-A8D8-03AA89B703B2 Q33607854-79ED12B1-BE9E-46DC-9FF3-E3A92294AAB2 Q33779332-888FB62C-24A3-4F15-B36E-DAD2F369EA36 Q33877767-C332AD9E-FE49-45B3-8A2F-FD62B2FBA585 Q34116091-02F05B8A-8636-456B-9C01-757E1EC5AFB0 Q34224702-22180F50-A8E2-4D02-BC0A-DDB4F9FCA3B6 Q34247744-5C00FCF3-6A6E-4ED8-8F1C-A772B6BE817F Q34260007-0587A1B5-F41E-4D5D-B4B0-AAB2717041BD Q34285452-7814A6C5-93F2-44D3-B6C1-C79242F1DB0C Q34769778-022EDBFE-E00A-491E-92FC-C6DA90C73BD8 Q34983658-AF9AEC82-6645-4F83-8418-30083CECDBF2 Q35188878-1E39A8B1-C8AF-4BD8-BE01-D13DF073B36A Q35237383-EAF37BAC-0BDD-49C5-8CB7-C3764C95D171 Q35509317-7482FB7D-3093-4EED-90A0-F4BD1EC2DE7B Q35591242-E896F160-8136-4A55-9144-9716D01DFE41 Q35786633-C2526E9E-1A04-4EBD-BD29-8CD320A9AE8E Q36568447-12699E7B-F6A2-45A3-8A68-2E5ADE6DA625 Q36642804-C20A6400-D0E3-4113-A18F-7278FEBAF2AC Q36898918-B4D232BE-0A2B-4862-9D2B-36B92EF105E8 Q37002275-0C36D5EE-842D-40E4-B7D4-B8B6697D93EE Q37219725-8F6745EB-E13C-458D-BD05-929B23D0493C Q37466983-02344EE8-3361-4447-A0C9-CB09B17A31C2 Q37875022-14F06292-AEBB-426C-B480-851F84E4C4AA

P2860

Data analysis in flow cytometry: the future just started.

http://www.wikidata.org/entity/Q33618094

description

2010 nî lūn-bûn

@nan

2010 թուականի Յուլիսին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի հուլիսին հրատարակված գիտական հոդված

@hy

2010年の論文

@ja

2010年論文

@yue

2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

@zh-mo

2010年論文

@zh-tw

2010年论文

@wuu

name

Data analysis in flow cytometry: the future just started.

@ast

Data analysis in flow cytometry: the future just started.

@en

type

label

Data analysis in flow cytometry: the future just started.

@ast

Data analysis in flow cytometry: the future just started.

@en

prefLabel

Data analysis in flow cytometry: the future just started.

@ast

Data analysis in flow cytometry: the future just started.

@en

P1433

Q33618094-C1E682EE-1F5A-4970-A2BB-AAC54258DEF8

P1476

Q33618094-D7F2FD0C-5D76-4C06-A75D-3253CFDAD159

P2093

Q33618094-3ECDE154-BD28-46B2-91E0-111D173334E4

Q33618094-F81945B1-F893-4A1A-8ED2-F886899E1584

P2860

Q33618094-08C201A9-73C3-4559-AE0D-0F8133FAD2A7

Q33618094-0A3E3A6C-1D5F-4BE2-8727-27667A0F7487

Q33618094-22FAAB96-7FA4-496C-9273-3273A605FAB7

Q33618094-26A81C5D-7AC9-4183-AC7F-E393E2D50D95

Q33618094-2BBF26F0-E1A6-4364-AA6F-9FE5E772398D

Q33618094-302AEE20-BBA9-42AD-8105-F3A13C2C9D7A

Q33618094-397F152C-1020-4D6D-8030-A3D3E5BBE595

Q33618094-3E8E20EF-61DC-44A4-B85B-43310976BD4B

Q33618094-454D1FF0-4BC0-4A41-94CD-6061F50C29F4

Q33618094-49AA71F7-AA38-4D5D-9C7E-D6D05D5B4868

P304

Q33618094-0EB74BC5-849E-4145-BF70-E28BBC6C6639

P31

Q33618094-1A892DEF-FABF-411B-B4F3-76D0E213A09B

P356

Q33618094-2122E83D-A6B9-4A31-9FE3-5D8882CDD917

P433

Q33618094-DD2390BB-DFC9-4616-8B0A-D853F72A2069

P478

Q33618094-6F779C36-0F41-47DF-8C03-C2DE87829A5E

P50

Q33618094-5746A0B6-EAFB-4217-A46A-2EE4DFFCAF3F

P577

Q33618094-53050D4A-164C-44E5-8487-F5E03DD1618A

P5875

Q33618094-9709E03D-8697-440F-A309-98A5A7D58F29

P698

Q33618094-D53E398E-02BC-4317-A4E5-9028EBE73193

P921

Q33618094-6FB48210-D184-474F-8B72-998804300E5B

P932

Q33618094-B1DA42D9-405D-423D-8961-381F98E9B0AE

P356

P1433

Cytometry Part A

P1476

Data analysis in flow cytometry: the future just started.

@en

P2093

Enrico Lugli

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

Mario Roederer

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

P2860

Cluster analysis and display of genome-wide expression patterns

11-color, 13-parameter flow cytometry: identification of human naive T cells by phenotype, function, and T-cell receptor diversity

Phenotypic analysis of antigen-specific T lymphocytes

HIV nonprogressors preferentially maintain highly functional HIV-specific CD8+ T cells

Causal protein-signaling networks derived from multiparameter single-cell data

Comparison of five clustering algorithms to classify phytoplankton from flow cytometry data.

Identification of organ-specific T cell populations by analysis of multiparameter flow cytometry data using DNA-chip analysis software.

Interpreting flow cytometry data: a guide for the perplexed.

Polychromatic flow cytometry: a rapid method for the reduction and analysis of complex multiparameter data.

Subject classification obtained by cluster analysis and principal component analysis applied to flow cytometric data.

P304

705-713

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

P31

scholarly article

P356

10.1002/CYTO.A.20901

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

P433

7

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

P478

77

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

P50

Andrea Cossarizza

P577

2010-07-01T00:00:00Z

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

P5875

44804981

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

P698

20583274

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

P921

P932

2909632

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