Visualizing structure and transitions in high-dimensional biological data

Untitled work

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Feature importance‐based interpretation of UMAP‐visualized polymer space

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CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets

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Dimensionality reduction for visualizing high-dimensional biological data

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Mapping the tumor immune landscape: single-cell RNA sequencing in cancer immunotherapy

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Sampling-enabled scalable manifold learning unveils the discriminative cluster structure of high-dimensional data

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Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators

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Structural bioinformatics enhances mechanistic interpretation of genomic variation, demonstrated through the analyses of 935 distinct RAS family mutations

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