Merging mixture components for cell population identification in flow cytometry
about
Data reduction for spectral clustering to analyze high throughput flow cytometry dataAn Introduction to Automated Flow Cytometry Gating Tools and Their ImplementationInferring phenotypic properties from single-cell characteristicsGenePattern flow cytometry suiteCritical assessment of automated flow cytometry data analysis techniques.Application of user-guided automated cytometric data analysis to large-scale immunoprofiling of invariant natural killer T cellsHigh-throughput flow cytometry data normalization for clinical trials.OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysisIdentification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.The end of gating? An introduction to automated analysis of high dimensional cytometry data.Automated mapping of phenotype space with single-cell data.Single and multi-subject clustering of flow cytometry data for cell-type identification and anomaly detectionThe curvHDR method for gating flow cytometry samples.Optimizing transformations for automated, high throughput analysis of flow cytometry data.Automated identification of stratifying signatures in cellular subpopulationsSetting objective thresholds for rare event detection in flow cytometry.Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies.Parametric modeling of cellular state transitions as measured with flow cytometry.A computational framework to emulate the human perspective in flow cytometric data analysis.flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak findingRchyOptimyx: cellular hierarchy optimization for flow cytometry.Computational analysis of high-throughput flow cytometry dataA non-parametric Bayesian model for joint cell clustering and cluster matching: identification of anomalous sample phenotypes with random effects.Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.CCAST: a model-based gating strategy to isolate homogeneous subpopulations in a heterogeneous population of single cellsHigh-throughput secondary screening at the single-cell level.Scalable clustering algorithms for continuous environmental flow cytometry.BayesFlow: latent modeling of flow cytometry cell populationsDiscriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studiesCompetitive SWIFT cluster templates enhance detection of aging changesAutomated analysis of acute myeloid leukemia minimal residual disease using a support vector machine.SWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 1: algorithm designSWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 2: biological evaluation.Guidelines for the use of flow cytometry and cell sorting in immunological studies.High Throughput Automated Analysis of Big Flow Cytometry Data.DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.Towards automation of flow cytometric analysis for quality-assured follow-up assessment to guide curative therapy for acute lymphoblastic leukaemia in children
P2860
Q21284349-86731AAE-E961-4B30-BF87-9B1DAACDBCA2Q26797342-E0F1EB80-BF19-476B-A115-1B0FB8C4B84AQ28729182-1D216093-E048-4099-A556-0D2677FCD9F5Q30177554-5267AADE-F911-465B-80A2-DD73333F6BD0Q30587564-DD77AC66-7A2A-473D-AD44-A02C13699FB1Q30689010-82E9D6B7-0797-4FBF-86FC-47C6DD111BF4Q30725027-32BB5682-8153-4C49-BD31-E179D54CC7B9Q30845743-CDFCC2B6-117A-4529-8ED5-59EB1469AD7CQ30938836-43B70666-68FE-4AD9-93AA-BC78F2386901Q31019645-292E89F6-01C8-4963-9852-E0B8BE652381Q31096376-B5E613B3-AA17-4A4A-A68B-971D6AD2F9EDQ31120977-3125B685-C169-4ADF-8538-3AADC04F6EDCQ33526064-28D86D66-157B-47D1-ABD4-687D682BE1BDQ33738291-D1D996DA-902C-45C8-8FA5-268391E9D798Q33854094-7BA9020B-592F-45F2-ADC6-E24E284FB436Q34067006-3CDFC3E6-7AE4-4295-A78C-BA1D71C55E5CQ34139513-A8A132A4-D820-466D-98FA-163C0167FF26Q34248125-4307DA68-BDAA-4E8E-9613-1C9EF3EA4AF9Q34260007-A530FAD1-BBE3-4E3F-9240-D1F2741995E0Q34272797-99F70353-09C8-4D9D-B917-71982CB95B8DQ34304477-9F0239B8-FBB9-4F43-B00F-A6650685CEC4Q34307823-179D1321-E401-43E6-8A79-4E367C2F8FDCQ34671240-C9B3B49F-1C78-4FDC-8D73-FEABF70BBC7CQ34845052-8C7882C4-683F-4FB5-98D6-FDBBDF29B6D9Q35216098-237C6078-6FE4-4605-B018-31CA02AEDDA0Q35235361-950F138C-62BE-4D82-8A24-F3F7BEA3FCD2Q35811570-1268C58E-9010-4528-B258-046D33552D6FQ35891316-3B5AD60D-B91C-4EEB-818D-6C8B2EA90CD8Q36371564-F807EE79-A653-47A3-B1EC-1813B63CC90DQ36533352-775E6F82-2F32-4DBD-ADCC-0BE39A9F4EE1Q37687740-13CD4DC7-8525-413C-80C0-599F888B06F6Q38433447-88A5BF7D-E7E3-460C-89ED-EC911F8D5EF1Q41837281-875A48F5-135D-48B0-B2BC-5868942605D1Q41918189-41533860-BD83-43CB-B680-0C669166ECF8Q47233084-43B1C5D5-D6C0-475E-88B4-1A9C4DF258B1Q52582833-C1CF0589-9047-4F26-BE53-F7EC3D0C7C82Q57566668-4B8503D5-3584-4CA9-AA55-F3B5E2330927
P2860
Merging mixture components for cell population identification in flow cytometry
description
2009 nî lūn-bûn
@nan
2009 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Merging mixture components for cell population identification in flow cytometry
@ast
Merging mixture components for cell population identification in flow cytometry
@en
Merging mixture components for cell population identification in flow cytometry.
@nl
type
label
Merging mixture components for cell population identification in flow cytometry
@ast
Merging mixture components for cell population identification in flow cytometry
@en
Merging mixture components for cell population identification in flow cytometry.
@nl
prefLabel
Merging mixture components for cell population identification in flow cytometry
@ast
Merging mixture components for cell population identification in flow cytometry
@en
Merging mixture components for cell population identification in flow cytometry.
@nl
P2860
P356
P1476
Merging mixture components for cell population identification in flow cytometry
@en
P2093
Ali Bashashati
Raphaël Gottardo
P2860
P304
P356
10.1155/2009/247646
P577
2009-11-12T00:00:00Z