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PhenoGMM : Gaussian mixture modelling of microbial cytometry data enables efficient predictions of biodiversity

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/1097-0320(20000701)40:3<214::aid-cyto6>3.0.co;2-mopenalex-snapshot

Two and three-color fluorescence flow cytometric analysis of immunoidentified viable bacteria

inferredcites →https://doi.org/10.1002/cpcy.37openalex-snapshot

Overview of Flow Cytometry and Microbiology

inferredcites →https://doi.org/10.1002/cyto.a.20553openalex-snapshot

Mixture modeling approach to flow cytometry data

inferredcites →https://doi.org/10.1002/cyto.a.22048openalex-snapshot

Development and laboratory‐scale testing of a fully automated online flow cytometer for drinking water analysis

inferredcites →https://doi.org/10.1002/cyto.a.22286openalex-snapshot

CHIC—an automated approach for the detection of dynamic variations in complex microbial communities

inferredcites →https://doi.org/10.1002/cyto.a.23030openalex-snapshot

Comparison of clustering methods for high‐dimensional single‐cell flow and mass cytometry data

inferredcites →https://doi.org/10.1002/cyto.a.23284openalex-snapshot

Stripping flow cytometry: How many detectors do we need for bacterial identification?

inferredcites →https://doi.org/10.1002/cyto.a.23304openalex-snapshot

Deconvolution model to resolve cytometric microbial community patterns in flowing waters

inferredcites →https://doi.org/10.1002/cyto.a.23370openalex-snapshot

FAST: Rapid determinations of antibiotic susceptibility phenotypes using label‐free cytometry

inferredcites →https://doi.org/10.1002/eji.201646297openalex-snapshot

High‐resolution microbiota flow cytometry reveals dynamic colitis‐associated changes in fecal bacterial composition

inferredcites →https://doi.org/10.1007/s00253-016-7837-5openalex-snapshot

Reevaluating multicolor flow cytometry to assess microbial viability

inferredcites →https://doi.org/10.1007/s10295-005-0208-3openalex-snapshot

New method to characterize microbial diversity using flow cytometry

inferredcites →https://doi.org/10.1016/j.apsoil.2018.06.013openalex-snapshot

Rapid analysis of photoautotroph microbial communities in soils by flow cytometric barcoding and fingerprinting

inferredcites →https://doi.org/10.1016/j.mam.2017.06.005openalex-snapshot

Personalized microbiome dynamics – Cytometric fingerprints for routine diagnostics

inferredcites →https://doi.org/10.1016/j.mimet.2013.05.007openalex-snapshot

Routine bacterial analysis with automated flow cytometry

inferredcites →https://doi.org/10.1016/j.patcog.2016.04.004openalex-snapshot

Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures

inferredcites →https://doi.org/10.1016/j.tig.2014.07.001openalex-snapshot

Ten years of next-generation sequencing technology

inferredcites →https://doi.org/10.1016/j.watres.2011.11.076openalex-snapshot

Flow cytometry for fast microbial community fingerprinting

inferredcites →https://doi.org/10.1016/j.watres.2013.07.051openalex-snapshot

Monitoring microbiological changes in drinking water systems using a fast and reproducible flow cytometric method

inferredcites →https://doi.org/10.1016/j.watres.2016.10.041openalex-snapshot

Short-term microbial dynamics in a drinking water plant treating groundwater with occasional high microbial loads

inferredcites →https://doi.org/10.1016/s0167-7012(02)00219-1openalex-snapshot

Statistical analysis and biological interpretation of the flow cytometric heterogeneity observed in bacterial axenic cultures

inferredcites →https://doi.org/10.1017/cbo9781107415324.004openalex-snapshot

An Ichthyosaurus (Reptilia, Ichthyosauria) with gastric contents from Charmouth, England:first report of the genus from the Pliensbachian

inferredcites →https://doi.org/10.1021/es2010682openalex-snapshot

Correlation of Community Dynamics and Process Parameters As a Tool for the Prediction of the Stability of Wastewater Treatment

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1038/ismej.2014.251openalex-snapshot

Dynamics in microbial communities: unraveling mechanisms to identify principles

inferredcites →https://doi.org/10.1038/ismej.2016.117openalex-snapshot

Absolute quantification of microbial taxon abundances

inferredcites →https://doi.org/10.1038/ismej.2016.118openalex-snapshot

Diversity is the question, not the answer

inferredcites →https://doi.org/10.1038/ismej.2016.204openalex-snapshot

Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula

inferredcites →https://doi.org/10.1038/nature24460openalex-snapshot

Quantitative microbiome profiling links gut community variation to microbial load

inferredcites →https://doi.org/10.1038/ncomms13942openalex-snapshot

Multiple Dirac cones at the surface of the topological metal LaBi

inferredcites →https://doi.org/10.1038/nmeth.2365openalex-snapshot

Critical assessment of automated flow cytometry data analysis techniques

inferredcites →https://doi.org/10.1038/nprot.2012.149openalex-snapshot

Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function

inferredcites →https://doi.org/10.1038/nrg3642openalex-snapshot

Sequencing depth and coverage: key considerations in genomic analyses

inferredcites →https://doi.org/10.1038/nrmicro3491openalex-snapshot

A functional perspective on phenotypic heterogeneity in microorganisms

inferredcites →https://doi.org/10.1038/s41467-017-00128-zopenalex-snapshot

Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles

inferredcites →https://doi.org/10.1093/bioinformatics/btv594openalex-snapshot

Scalable clustering algorithms for continuous environmental flow cytometry

inferredcites →https://doi.org/10.1093/bioinformatics/btw191openalex-snapshot

flowAI: automatic and interactive anomaly discerning tools for flow cytometry data

inferredcites →https://doi.org/10.1093/nar/gky066openalex-snapshot

Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics

inferredcites →https://doi.org/10.1101/392852openalex-snapshot

Randomized lasso associates freshwater lake-system specific bacterial taxa with heterotrophic production through flow cytometry

inferredcites →https://doi.org/10.1111/1462-2920.12984openalex-snapshot

Seasonality in molecular and cytometric diversity of marine bacterioplankton: the re‐shuffling of bacterial taxa by vertical mixing

inferredcites →https://doi.org/10.1111/1462-2920.13953openalex-snapshot

Flow cytometric monitoring of bacterioplankton phenotypic diversity predicts high population‐specific feeding rates by invasive dreissenid mussels

inferredcites →https://doi.org/10.1111/1462-2920.14269openalex-snapshot

Taking the technical microbiome into the next decade

inferredcites →https://doi.org/10.1111/1574-6941.12308openalex-snapshot

Community fingerprinting in a sequencing world

inferredcites →https://doi.org/10.1111/2041-210x.12607openalex-snapshot

Measuring the biodiversity of microbial communities by flow cytometry

inferredcites →https://doi.org/10.1111/ecog.02881openalex-snapshot

Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

inferredcites →https://doi.org/10.1111/j.1467-9868.2005.00503.xopenalex-snapshot

Regularization and Variable Selection Via the Elastic Net

inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02080.xopenalex-snapshot

Regression Shrinkage and Selection Via the Lasso

inferredcites →https://doi.org/10.1111/jbi.14281openalex-snapshot

The detection of disease clustering and a generalized regression approach.

inferredcites →https://doi.org/10.1117/1.2819119openalex-snapshot

Book Review: Pattern Recognition and Machine Learning

inferredcites →https://doi.org/10.1126/science.1153213openalex-snapshot

The Microbial Engines That Drive Earth's Biogeochemical Cycles

inferredcites →https://doi.org/10.1128/aem.00123-19openalex-snapshot

Influence of Plant Species, Tissue Type, and Temperature on the Capacity of Shiga-Toxigenic Escherichia coli To Colonize, Grow, and Be Internalized by Plants

inferredcites →https://doi.org/10.1128/aem.02814-18openalex-snapshot

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities

inferredcites →https://doi.org/10.1128/mbio.00714-16openalex-snapshot

Toward a Predictive Understanding of Earth’s Microbiomes to Address 21st Century Challenges

inferredcites →https://doi.org/10.1128/msystems.00003-19openalex-snapshot

16S rRNA/rRNA Gene Ratios and Cell Activity Staining Reveal Consistent Patterns of Microbial Activity in Plant-Associated Soil

inferredcites →https://doi.org/10.1128/msystems.00093-19openalex-snapshot

Randomized Lasso Links Microbial Taxa with Aquatic Functional Groups Inferred from Flow Cytometry

inferredcites →https://doi.org/10.1128/msystems.00230-18openalex-snapshot

Emergent Subpopulation Behavior Uncovered with a Community Dynamic Metabolic Model of Escherichia coli Diauxic Growth

inferredcites →https://doi.org/10.1136/bmj.j831openalex-snapshot

The role of the microbiome in human health and disease: an introduction for clinicians

inferredcites →https://doi.org/10.1155/2009/193947openalex-snapshot

FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data

inferredcites →https://doi.org/10.1186/s12859-019-3152-3openalex-snapshot

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

inferredcites →https://doi.org/10.1186/s13036-018-0109-4openalex-snapshot

Synthesis of control unit for future biocomputer

inferredcites →https://doi.org/10.1186/s13036-018-0112-9openalex-snapshot

Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes

inferredcites →https://doi.org/10.1186/s40168-018-0420-9openalex-snapshot

Correcting for 16S rRNA gene copy numbers in microbiome surveys remains an unsolved problem

inferredcites →https://doi.org/10.1371/journal.pbio.1002020openalex-snapshot

Life in a World without Microbes

inferredcites →https://doi.org/10.1371/journal.pcbi.1002687openalex-snapshot

Inferring Correlation Networks from Genomic Survey Data

inferredcites →https://doi.org/10.1371/journal.pcbi.1002837openalex-snapshot

3D Reconstruction and Standardization of the Rat Vibrissal Cortex for Precise Registration of Single Neuron Morphology

inferredcites →https://doi.org/10.1371/journal.pone.0121659openalex-snapshot

RNA Preservation Agents and Nucleic Acid Extraction Method Bias Perceived Bacterial Community Composition

inferredcites →https://doi.org/10.1371/journal.pone.0169754openalex-snapshot

Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities

inferredcites →https://doi.org/10.1371/journal.pone.0191962openalex-snapshot

Semaphorin3A induces nerve regeneration in the adult cornea-a switch from its repulsive role in development

inferredcites →https://doi.org/10.1371/journal.pone.0195112openalex-snapshot

Verrucomicrobia are prevalent in north-temperate freshwater lakes and display class-level preferences between lake habitats

inferredcites →https://doi.org/10.1890/10-2402.1openalex-snapshot

Measuring diversity: the importance of species similarity

inferredcites →https://doi.org/10.2307/1934352openalex-snapshot

Diversity and Evenness: A Unifying Notation and Its Consequences

inferredcites →https://doi.org/10.2307/1942268openalex-snapshot

An Ordination of the Upland Forest Communities of Southern Wisconsin

inferredcites →https://doi.org/10.32614/rj-2016-021openalex-snapshot

mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models

inferredcites →https://doi.org/10.3354/ame01691openalex-snapshot

Automated clustering of heterotrophic bacterioplankton in flow cytometry data

inferredcites →https://doi.org/10.3389/fmicb.2014.00273openalex-snapshot

Cytometric fingerprints: evaluation of new tools for analyzing microbial community dynamics

inferredcites →https://doi.org/10.3389/fmicb.2014.00459openalex-snapshot

Oxygenic photosynthesis as a protection mechanism for cyanobacteria against iron-encrustation in environments with high Fe2+ concentrations

inferredcites →https://doi.org/10.3390/math6070119openalex-snapshot

Ecological Diversity: Measuring the Unmeasurable

inferredcites →https://doi.org/10.3390/microorganisms6040103openalex-snapshot

Long-Term Biogas Production from Glycolate by Diverse and Highly Dynamic Communities

inferredcites →https://doi.org/10.4319/lo.1997.42.5.0874openalex-snapshot

Cytometric diversity in marine ultraphytoplankton

inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot

Scikit-learn: Machine Learning in Python

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1038/s41396-020-00762-4openalex-snapshot

Cytometric fingerprints of gut microbiota predict Crohn’s disease state

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