About: flowEMMi: an automated model-based clustering tool for microbial cytometric data

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scientific article published on 09 December 2019

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) artículu científicu espublizáu n'avientu de 2019 (ast) наукова стаття, опублікована 9 грудня 2019 (uk) scientific article published on 09 December 2019 (en)
publication date	wds:Q91797553-1FE8E336-2016-47B2-A95B-42B4C98463F7
publication date	2019-12-09 00:00:00Z (xsd:dateTime)
cites work	wds:Q91797553-046AFF02-CF06-4A00-8F63-17FE14301130 wds:Q91797553-0B24BCB3-DD50-480E-8F71-31254283ED0B wds:Q91797553-0D0E4675-6238-4452-AE30-1FAB7E9F907D wds:Q91797553-13DC53B8-9875-44B6-A7DD-6AB381E66389 wds:Q91797553-18996F37-C787-412B-ADA3-CF7BFAD4F003 wds:Q91797553-2947C1DB-728D-4AE4-867B-DC2953190A68 wds:Q91797553-2B4E138A-A730-45A2-8636-C3C97F4CEF5F wds:Q91797553-3463E838-8EEC-405B-A38C-A1DAAEDE2359 wds:Q91797553-43A0A8E6-B631-481E-9F71-38B3D6DB0EC8 wds:Q91797553-4505E1ED-8960-4B91-82B2-97209D67BE33 wds:Q91797553-4558BB14-338B-4DA7-B43C-11D99DA707EE wds:Q91797553-507A4DC4-EE82-4C25-9291-273D0E7CC1B9 wds:Q91797553-5C4D0D6E-FF76-41FF-99AD-4997464A8C33 wds:Q91797553-711CE83D-C082-48A8-8048-861931A76B5D wds:Q91797553-72A20A5F-C9B7-4291-91A0-941E0CFC5A86 wds:Q91797553-801C0726-CAB9-4B9B-8FB7-21498D9B3545 wds:Q91797553-846C4F80-CB7B-41FF-90B2-A05894041E71 wds:Q91797553-8A90A567-9BB1-4E14-91FF-321CA7155331 wds:Q91797553-8C697351-9460-4DDC-88BA-1887E79F8A2C wds:Q91797553-8DE642D5-0135-4200-BF69-DF33382C408F wds:Q91797553-9323AFD5-5B99-4E8C-963C-20B5D6088C0D wds:Q91797553-A9D90B4A-B5E7-4544-A79B-6C4C307849E0 wds:Q91797553-C4E4444B-0A66-44CE-ABC5-00FF40948E36 wds:Q91797553-C54F7D5B-D9E6-4542-A268-0895916FA6BF wds:Q91797553-C6A845CA-4DB7-4031-9695-EB35E8B22196 wds:Q91797553-CEDE1A80-33BA-49EA-8B3B-166B1EB3AFCE wds:Q91797553-DDD31CDB-D9AD-4204-B7ED-C1D7A6DBB8C3 wds:Q91797553-ED23626F-55D0-4A69-9783-D3CB331B884D
cites work	Functional single-cell analyses: flow cytometry and cell sorting of microbial populations and communities flowClust: a Bioconductor package for automated gating of flow cytometry data Merging mixture components for cell population identification in flow cytometry Rapid cell population identification in flow cytometry data Critical assessment of automated flow cytometry data analysis techniques. Probability binning comparison: a metric for quantitating multivariate distribution differences. Data reduction for spectral clustering to analyze high throughput flow cytometry data Automated high-dimensional flow cytometric data analysis Outline of a Theory of Statistical Estimation Based on the Classical Theory of Probability High-content flow cytometry and temporal data analysis for defining a cellular signature of graft-versus-host disease CHIC-an automated approach for the detection of dynamic variations in complex microbial communities. Overnight stagnation of drinking water in household taps induces microbial growth and changes in community composition Flow-cytometric total bacterial cell counts as a descriptive microbiological parameter for drinking water treatment processes Monitoring Functions in Managed Microbial Systems by Cytometric Bar Coding Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function Abundance and composition of indigenous bacterial communities in a multi-step biofiltration-based drinking water treatment plant Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities A cytometric approach to follow variation and dynamics of the salivary microbiota Species-sorting and mass-transfer paradigms control managed natural metacommunities High-resolution microbiota flow cytometry reveals dynamic colitis-associated changes in fecal bacterial composition Facilitated gate setting by sequential dot plot scanning. flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification. Personalized microbiome dynamics - Cytometric fingerprints for routine diagnostics Deconvolution model to resolve cytometric microbial community patterns in flowing waters. Ecological Stability Properties of Microbial Communities Assessed by Flow Cytometry. Flow cytometric quantification, sorting and sequencing of methanogenic archaea based on F420 autofluorescence. Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization. Neutral mechanisms and niche differentiation in steady-state insular microbial communities revealed by single cell analysis
author name string	wds:Q91797553-0F65D741-6B3A-4647-99DD-E015689BB1E6 wds:Q91797553-4595BA22-8CF3-40CD-8EC9-F50C86C5268D wds:Q91797553-8EA8C84F-4E6D-4B2E-9D8D-8712F44F2AF4 wds:Q91797553-D4A5D5F8-7542-4202-AC3A-8DEA4673F451
author name string	Peter F Stadler Susann Müller Zishu Liu Joachim Ludwig
rdfs:label	flowEMMi: an automated model-based clustering tool for microbial cytometric data (en) flowEMMi: an automated model-based clustering tool for microbial cytometric data (nl)
skos:prefLabel	flowEMMi: an automated model-based clustering tool for microbial cytometric data (en) flowEMMi: an automated model-based clustering tool for microbial cytometric data (nl)
name	flowEMMi: an automated model-based clustering tool for microbial cytometric data (en) flowEMMi: an automated model-based clustering tool for microbial cytometric data (nl)
author	wds:Q91797553-CDB9BC59-27EC-46D5-B7BE-1B3BA3EB0CFD
author	Christian Höner zu Siederdissen
title	wds:Q91797553-56050895-9365-4E66-B6DD-312A5ECF4A8F
title	flowEMMi: an automated model-based clustering tool for microbial cytometric data (en)
page(s)	wds:Q91797553-7CC1F36B-1905-4CBA-A153-96FA26E5240D
page(s)	643
instance of	wds:Q91797553-410EAD2D-A093-4F4C-AA21-BAB820D7FA92
instance of	scholarly article
PubMed ID	wds:Q91797553-55198281-EA39-44E2-A334-2EC59B3AC3F7
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/31815609
PubMed ID	31815609
DBLP publication ID	wds:Q91797553-AEDA76E4-ADDA-436F-A81C-1B86754129D0
DBLP publication ID	https://dblp.org/rec/journals/bmcbi/LudwigSLSM19
DBLP publication ID	journals/bmcbi/LudwigSLSM19
published in	wds:Q91797553-BCE72EED-F613-4D5F-9B0F-2E8263DB381C
published in	BMC Bioinformatics
issue	wds:Q91797553-699ACFE4-0F3D-48DB-A50E-04C1604B1CD4
volume	wds:Q91797553-73996219-0C0A-423E-8CD1-FB9F81F28189
issue	1
volume	20
DOI	wds:Q91797553-9DD0351F-9280-46A7-BF1E-B801AF94C7C1
DOI	http://dx.doi.org/10.1186/S12859-019-3152-3
DOI	10.1186/S12859-019-3152-3

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