Model-based cluster analysis applied to flow cytometry data of phytoplankton

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: WIAS: Technical Reports ; 5

Classification: Mathematik

Event: Veröffentlichung

(where): Berlin

(who): Weierstraß-Institut für Angewandte Analysis und Stochastik im Forschungsverbund Berlin e.V.

(when): 2002

Creator: Mucha, Hans-Joachim
Simon, Ute
Brüggemann, Rainer

Contributor: Weierstraß-Institut für Angewandte Analysis und Stochastik

URN: urn:nbn:de:101:1-201104183706

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:23 AM CEST

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Associated

Mucha, Hans-Joachim
Simon, Ute
Brüggemann, Rainer
Weierstraß-Institut für Angewandte Analysis und Stochastik
Weierstraß-Institut für Angewandte Analysis und Stochastik im Forschungsverbund Berlin e.V.

Time of origin

2002

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Model-based clustering for flow and mass cytometry data with clinical information

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Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton

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Model-based cluster analysis applied to flow cytometry data of phytoplankton

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Other Objects (12)

Model-based clustering for flow and mass cytometry data with clinical information

Model-based cell clustering and population tracking for time-series flow cytometry data

Tracking the frequency of phytoplankton clonal lineages using multispectral image flow cytometry and neural networks

INFLECT: an R-package for cytometry cluster evaluation using marker modality

Assessment of global phytoplankton growth inferred from satellite and physiological model-based analyses

Complete Model-Based Testing Applied to the Railway Domain

Model-based cluster analysis of microarray gene-expression data

Design-based and model-based estimation in adaptive cluster sampling

How cluster-robust inference is changing applied econometrics

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Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton

Model-based clustering for flow and mass cytometry data with clinical information

Model-based cell clustering and population tracking for time-series flow cytometry data

Tracking the frequency of phytoplankton clonal lineages using multispectral image flow cytometry and neural networks

INFLECT: an R-package for cytometry cluster evaluation using marker modality

Assessment of global phytoplankton growth inferred from satellite and physiological model-based analyses

Complete Model-Based Testing Applied to the Railway Domain

Model-based cluster analysis of microarray gene-expression data

Design-based and model-based estimation in adaptive cluster sampling

How cluster-robust inference is changing applied econometrics

Magnetic Flow Cytometry

Phytoplankton in the Elbe estuary: New insights into community composition and mixotrophy, from metabarcoding, flow cytometry, and laboratory experiments

Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton

Model-based clustering for flow and mass cytometry data with clinical information

Model-based cell clustering and population tracking for time-series flow cytometry data

Tracking the frequency of phytoplankton clonal lineages using multispectral image flow cytometry and neural networks

INFLECT: an R-package for cytometry cluster evaluation using marker modality

Assessment of global phytoplankton growth inferred from satellite and physiological model-based analyses

Complete Model-Based Testing Applied to the Railway Domain

Model-based cluster analysis of microarray gene-expression data

Design-based and model-based estimation in adaptive cluster sampling

How cluster-robust inference is changing applied econometrics

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Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton

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