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https://doi.org/10.1101/453449
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-46150-8_44openalex-snapshot
Correction to: Heavy-Tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations
inferredcites →https://doi.org/10.1016/j.cell.2015.05.002openalex-snapshot
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
inferredcites →https://doi.org/10.1016/j.cell.2016.07.054openalex-snapshot
Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics
inferredcites →https://doi.org/10.1016/j.cell.2018.06.021openalex-snapshot
Molecular Architecture of the Mouse Nervous System
inferredcites →https://doi.org/10.1016/j.cell.2018.07.028openalex-snapshot
Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
inferredcites →https://doi.org/10.1016/j.celrep.2017.12.017openalex-snapshot
Developmental Emergence of Adult Neural Stem Cells as Revealed by Single-Cell Transcriptional Profiling
inferredcites →https://doi.org/10.1016/j.cels.2018.05.017openalex-snapshot
Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks
inferredcites →https://doi.org/10.1016/j.jpdc.2019.04.008openalex-snapshot
GPU accelerated t-distributed stochastic neighbor embedding
inferredcites →https://doi.org/10.1016/j.neucom.2008.12.017openalex-snapshot
Quality assessment of dimensionality reduction: Rank-based criteria
inferredcites →https://doi.org/10.1016/j.neucom.2014.12.095openalex-snapshot
Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure
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.3445openalex-snapshot
Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq
inferredcites →https://doi.org/10.1038/nbt.4314openalex-snapshot
Dimensionality reduction for visualizing single-cell data using UMAP
inferredcites →https://doi.org/10.1038/ncomms14049openalex-snapshot
Massively parallel digital transcriptional profiling of single cells
inferredcites →https://doi.org/10.1038/nmeth.2764openalex-snapshot
Entering the era of single-cell transcriptomics in biology and medicine
inferredcites →https://doi.org/10.1038/nmeth.4644openalex-snapshot
scmap: projection of single-cell RNA-seq data across data sets
inferredcites →https://doi.org/10.1038/nn.4216openalex-snapshot
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics
inferredcites →https://doi.org/10.1038/nn.4366openalex-snapshot
Disentangling neural cell diversity using single-cell transcriptomics
inferredcites →https://doi.org/10.1038/s41467-017-01689-9openalex-snapshot
Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types
inferredcites →https://doi.org/10.1038/s41467-018-04368-5openalex-snapshot
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
inferredcites →https://doi.org/10.1038/s41467-019-13055-yopenalex-snapshot
Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets
inferredcites →https://doi.org/10.1038/s41586-018-0590-4openalex-snapshot
Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris
inferredcites →https://doi.org/10.1038/s41586-018-0654-5openalex-snapshot
Shared and distinct transcriptomic cell types across neocortical areas
inferredcites →https://doi.org/10.1038/s41586-019-0969-xopenalex-snapshot
The single-cell transcriptional landscape of mammalian organogenesis
inferredcites →https://doi.org/10.1038/s41592-018-0308-4openalex-snapshot
Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data
inferredcites →https://doi.org/10.1093/bioinformatics/bty1044openalex-snapshot
M3Drop: dropout-based feature selection for scRNASeq
inferredcites →https://doi.org/10.1098/rsif.2014.0672openalex-snapshot
Mapping the stereotyped behaviour of freely moving fruit flies
inferredcites →https://doi.org/10.1101/gr.230771.117openalex-snapshot
bigSCale: an analytical framework for big-scale single-cell data
inferredcites →https://doi.org/10.1109/tvcg.2016.2570755openalex-snapshot
Approximated and User Steerable tSNE for Progressive Visual Analytics
inferredcites →https://doi.org/10.1111/cgf.12878openalex-snapshot
Hierarchical Stochastic Neighbor Embedding
inferredcites →https://doi.org/10.1142/s0219720017500172openalex-snapshot
Application of t-SNE to human genetic data
inferredcites →https://doi.org/10.1145/2872427.2883041openalex-snapshot
Visualizing Large-scale and High-dimensional Data
inferredcites →https://doi.org/10.1146/annurev.cellbio.20.010403.095114openalex-snapshot
FUNDAMENTALS OF PLANARIAN REGENERATION
inferredcites →https://doi.org/10.1186/s12915-018-0580-xopenalex-snapshot
Identification of cell types in a mouse brain single-cell atlas using low sampling coverage
inferredcites →https://doi.org/10.1186/s13059-017-1382-0openalex-snapshot
SCANPY: large-scale single-cell gene expression data analysis
inferredcites →https://doi.org/10.1186/s13059-019-1663-xopenalex-snapshot
PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells
inferredcites →https://doi.org/10.1186/s13059-019-1861-6openalex-snapshot
Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
inferredcites →https://doi.org/10.1371/journal.pbio.2006387openalex-snapshot
Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics
inferredcites →https://doi.org/10.1523/jneurosci.2899-04.2005openalex-snapshot
Pax6, Tbr2, and Tbr1 Are Expressed Sequentially by Radial Glia, Intermediate Progenitor Cells, and Postmitotic Neurons in Developing Neocortex
inferredcites →https://doi.org/10.21105/joss.00861openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection
inferredcites →https://doi.org/10.22148/16.025openalex-snapshot
Stable Random Projection: Lightweight, General-Purpose Dimensionality Reduction for Digitized Libraries
inferredcites →https://doi.org/10.48550/arxiv.1712.09005openalex-snapshot
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
inferredcites →https://doi.org/10.48550/arxiv.1802.03426openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
inferredcites →https://doi.org/10.48550/arxiv.1803.01768openalex-snapshot
An Analysis of the t-SNE Algorithm for Data Visualization
inferredcites →https://doi.org/10.48550/arxiv.1807.11824openalex-snapshot
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data
inferredcites →https://doi.org/10.5555/2627435.2697068openalex-snapshot
Accelerating t-SNE using tree-based algorithms
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)
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Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments
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Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
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Recent Machine Learning Approaches for Single-Cell RNA-seq Data Analysis
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Data Compression and Visualization Using PCA and T-SNE
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A case study on the detailed reproducibility of a Human Cell Atlas project
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inferred← citeshttps://doi.org/10.1016/j.isci.2021.102225openalex-snapshot
Hyperbolic geometry of gene expression
inferred← citeshttps://doi.org/10.1016/j.kint.2019.03.035openalex-snapshot
Understanding the kidney one cell at a time
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A novel approach to remove the batch effect of single-cell data
inferred← citeshttps://doi.org/10.1038/s41467-019-12058-zopenalex-snapshot
Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas
inferred← citeshttps://doi.org/10.1093/bioinformatics/btaa189openalex-snapshot
Projected t-SNE for batch correction
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Transcriptomic homogeneity and an age-dependent onset of hemoglobin expression characterize morphological PV types
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The Na + /K + ATPase Regulates Glycolysis and Modifies Immune Metabolism in Tumors
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VAE-SNE: a deep generative model for simultaneous dimensionality reduction and clustering
inferred← citeshttps://doi.org/10.1101/2020.08.12.248963openalex-snapshot
MSImpute: Imputation of label-free mass spectrometry peptides by low-rank approximation
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Unsupervised Learning for Large Scale Data: The ATHLOS Project
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MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
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Cell types in the mouse amygdala and their transcriptional response to fear conditioning
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A Spectral Method for Assessing and Combining Multiple Data Visualizations
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Demultiplexing the heterogeneous conformational ensembles of intrinsically disordered proteins into structurally similar clusters
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RE2DC Resolves the Robustness–Efficiency Trade-Off in Single Particle Cryo-EM 2D Classification
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Approximate Nearest Neighbor Graph Provides Fast and Efficient Embedding with Applications in Large-scale Biological Data
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singleCellHaystack: Finding surprising genes in 2-dimensional representations of single cell transcriptome data
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Sequential compression of gene expression across dimensionalities and methods reveals no single best method or dimensionality
inferred← citeshttps://doi.org/10.1101/671404openalex-snapshot
Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification
inferred← citeshttps://doi.org/10.1101/731877openalex-snapshot
openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding
inferred← citeshttps://doi.org/10.1101/834549openalex-snapshot
Metric learning enables synthesis of heterogeneous single-cell modalities
inferred← citeshttps://doi.org/10.1109/cibcb.2019.8791482openalex-snapshot
Visualizing High-Dimensional Single-Cell RNA-seq Data via Random Projections and Geodesic Distances
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Exploring the complexity of African populations variability with Machine Learning
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Computational pathology reveals unique spatial patterns of immune response in H&E images from COVID-19 autopsies: preliminary findings
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Data from IgA-Dominated Humoral Immune Responses Govern Patients' Outcome in Endometrial Cancer
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Compressing gene expression data using multiple latent space dimensionalities learns complementary biological representations
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Stochastic quartet approach for fast multidimensional scaling
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Interactive dual projections for gene expression analysis
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Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration
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Resilience Evaluation of Automakers after 2008 Financial Crisis by UMAP
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Shape-aware Stochastic Neighbor Embedding for Robust Data Visualisations
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A Probabilistic Graph Coupling View of Dimension Reduction
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Single-cell transcriptomics reveals heterogeneous progression and EGFR activation in pancreatic adenosquamous carcinoma
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