On the public citation graph
Comparative Analysis of Linear and Nonlinear Dimension Reduction Techniques on Mass Cytometry Data
0 signed · 65 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cyto.a.22625openalex-snapshot
FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data
inferredcites →https://doi.org/10.1007/3-540-44668-0_68openalex-snapshot
Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study
inferredcites →https://doi.org/10.1016/j.acha.2005.07.004openalex-snapshot
Diffusion maps, spectral clustering and reaction coordinates of dynamical systems
inferredcites →https://doi.org/10.1016/j.cell.2014.04.005openalex-snapshot
Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development
inferredcites →https://doi.org/10.1016/j.cell.2015.05.047openalex-snapshot
Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis
inferredcites →https://doi.org/10.1016/j.celrep.2014.09.045openalex-snapshot
CD161 Defines a Transcriptional and Functional Phenotype across Distinct Human T Cell Lineages
inferredcites →https://doi.org/10.1016/j.celrep.2015.05.022openalex-snapshot
Mapping the Diversity of Follicular Helper T Cells in Human Blood and Tonsils Using High-Dimensional Mass Cytometry Analysis
inferredcites →https://doi.org/10.1016/j.immuni.2012.01.002openalex-snapshot
Cytometry by Time-of-Flight Shows Combinatorial Cytokine Expression and Virus-Specific Cell Niches within a Continuum of CD8+ T Cell Phenotypes
inferredcites →https://doi.org/10.1016/j.immuni.2016.04.014openalex-snapshot
Mass Cytometry of the Human Mucosal Immune System Identifies Tissue- and Disease-Associated Immune Subsets
inferredcites →https://doi.org/10.1016/j.it.2012.02.010openalex-snapshot
A deep profiler's guide to cytometry
inferredcites →https://doi.org/10.1016/j.stem.2015.01.015openalex-snapshot
A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry
inferredcites →https://doi.org/10.1021/ac901049wopenalex-snapshot
Mass Cytometry: Technique for Real Time Single Cell Multitarget Immunoassay Based on Inductively Coupled Plasma Time-of-Flight Mass Spectrometry
inferredcites →https://doi.org/10.1021/ct400052yopenalex-snapshot
Evaluation of Dimensionality-Reduction Methods from Peptide Folding–Unfolding Simulations
inferredcites →https://doi.org/10.1038/nbt.1991openalex-snapshot
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
inferredcites →https://doi.org/10.1038/nbt.2593openalex-snapshot
Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization
inferredcites →https://doi.org/10.1038/nbt.2594openalex-snapshot
viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
inferredcites →https://doi.org/10.1038/nbt.3569openalex-snapshot
Wishbone identifies bifurcating developmental trajectories from single-cell data
inferredcites →https://doi.org/10.1038/nbt0308-303openalex-snapshot
What is principal component analysis?
inferredcites →https://doi.org/10.1038/ni.3006openalex-snapshot
High-dimensional analysis of the murine myeloid cell system
inferredcites →https://doi.org/10.1038/ni.3485openalex-snapshot
Mass cytometry: blessed with the curse of dimensionality
inferredcites →https://doi.org/10.1038/ni0706-681openalex-snapshot
Interpreting flow cytometry data: a guide for the perplexed
inferredcites →https://doi.org/10.1038/nmeth.3252openalex-snapshot
Orchestrating high-throughput genomic analysis with Bioconductor
inferredcites →https://doi.org/10.1038/nri.2016.56openalex-snapshot
Computational flow cytometry: helping to make sense of high-dimensional immunology data
inferredcites →https://doi.org/10.1093/bioinformatics/btv325openalex-snapshot
Diffusion maps for high-dimensional single-cell analysis of differentiation data
inferredcites →https://doi.org/10.1093/bioinformatics/btv715openalex-snapshot
destiny : diffusion maps for large-scale single-cell data in R
inferredcites →https://doi.org/10.1111/j.1751-5823.2002.tb00178.xopenalex-snapshot
On Choosing and Bounding Probability Metrics
inferredcites →https://doi.org/10.1126/science.1198704openalex-snapshot
Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum
inferredcites →https://doi.org/10.1126/science.290.5500.2319openalex-snapshot
A Global Geometric Framework for Nonlinear Dimensionality Reduction
inferredcites →https://doi.org/10.1155/2017/3930957openalex-snapshot
Robust L‐Isomap with a Novel Landmark Selection Method
inferredcites →https://doi.org/10.1186/1471-2105-6-195openalex-snapshot
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
inferredcites →https://doi.org/10.4049/jimmunol.1500633openalex-snapshot
Algorithmic Tools for Mining High-Dimensional Cytometry Data
inferredcites →https://doi.org/10.4049/jimmunol.1500703openalex-snapshot
Phenotypic Complexity of the Human Regulatory T Cell Compartment Revealed by Mass Cytometry
inferredcites →https://doi.org/10.48550/arxiv.1404.1100openalex-snapshot
A Tutorial on Principal Component Analysis
inferredcites →https://doi.org/10.5555/2627435.2697068openalex-snapshot
Accelerating t-SNE using tree-based algorithms
inferredcites →https://doi.org/10.7555/jbr.29.20150035openalex-snapshot
Translating transitions - how to decipher peripheral human B cell development
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-43192-1_41openalex-snapshot
Review on Dimensionality Reduction Techniques
inferred← citeshttps://doi.org/10.1007/978-3-030-93119-3_20openalex-snapshot
Using Hybrid Scatterplots for Visualizing Multi-dimensional Data
inferred← citeshttps://doi.org/10.1007/978-981-16-8531-6_1openalex-snapshot
Parallel Nonlinear Dimensionality Reduction Using GPU Acceleration
inferred← citeshttps://doi.org/10.1007/978-981-19-8746-5_5openalex-snapshot
Enhancing Understandability of Omics Data with SHAP, Embedding Projections and Interactive Visualisations
inferred← citeshttps://doi.org/10.1007/s10518-024-02080-yopenalex-snapshot
Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling
inferred← citeshttps://doi.org/10.1016/j.chemolab.2019.103867openalex-snapshot
Supervised projection pursuit – A dimensionality reduction technique optimized for probabilistic classification
inferred← citeshttps://doi.org/10.1016/j.csbj.2020.03.024openalex-snapshot
Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry
inferred← citeshttps://doi.org/10.1016/j.inffus.2020.01.005openalex-snapshot
Overview and comparative study of dimensionality reduction techniques for high dimensional data
inferred← citeshttps://doi.org/10.1016/j.jcp.2022.111313openalex-snapshot
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems
inferred← citeshttps://doi.org/10.1017/9781009181884openalex-snapshot
Knowledge Discovery from Archaeological Materials
inferred← citeshttps://doi.org/10.1038/s41467-023-37478-wopenalex-snapshot
Comparative analysis of dimension reduction methods for cytometry by time-of-flight data
inferred← citeshttps://doi.org/10.1093/nargab/lqaa053openalex-snapshot
Untangling biological factors influencing trajectory inference from single cell data
inferred← citeshttps://doi.org/10.1093/nargab/lqaa102openalex-snapshot
Erratum: Untangling biological factors influencing trajectory inference from single cell data.
inferred← citeshttps://doi.org/10.1101/2023.11.23.568428openalex-snapshot
Interpretable models for scRNA-seq data embedding with multi-scale structure preservation
inferred← citeshttps://doi.org/10.1101/2025.04.28.651069openalex-snapshot
From Pairwise Distances to Neighborhood Preservation: Benchmarking Dimensionality Reduction Algorithms for CyTOF, scRNA-seq, and CITE-seq
inferred← citeshttps://doi.org/10.1101/337485openalex-snapshot
Continuous visualization of differences between biological conditions in single-cell data
inferred← citeshttps://doi.org/10.1101/496869openalex-snapshot
Rapid single-cell cytometry data visualization with EmbedSOM
inferred← citeshttps://doi.org/10.1109/access.2020.3016244openalex-snapshot
Projection-Based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials
inferred← citeshttps://doi.org/10.1109/ijcnn.2019.8851847openalex-snapshot
Visualizing Time Series Data with Temporal Matching Based t-SNE
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1008885openalex-snapshot
DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data
inferred← citeshttps://doi.org/10.1515/ijb-2025-0071openalex-snapshot
Performance evaluation of dimensionality reduction techniques on high-dimensional DNA methylation data
inferred← citeshttps://doi.org/10.22214/ijraset.2022.40572openalex-snapshot
Dimensional Reduction Techniques for Huge Volume of Data
inferred← citeshttps://doi.org/10.33448/rsd-v9i11.10023openalex-snapshot
Doença de Parkinson: os principais danos provocados no indivíduo
inferred← citeshttps://doi.org/10.3389/fimmu.2019.01194openalex-snapshot
Quantitative Comparison of Conventional and t-SNE-guided Gating Analyses
inferred← citeshttps://doi.org/10.3390/data10050070openalex-snapshot
Linear Dimensionality Reduction: What Is Better?
inferred← citeshttps://doi.org/10.51983/ajcst-2019.8.s3.2084openalex-snapshot
Performance Analysis of Dimensionality Reduction Techniques in the Context of Clustering
inferred← citeshttps://doi.org/10.6000/1929-6029.2025.14.01openalex-snapshot
Multiple Mean Comparison for Clusters of Gene Expression Data through the t-SNE Plot and PCA Dimension Reduction
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.