t-SNE via Rtsne — Barnes-Hut t-distributed Stochastic Neighbor Embedding for nonlinear dimensionality reduction and visualization. Wraps Van der Maaten's C++ Barnes-Hut implementation for O(n log n) c
Use with AI
Install the MCP server or CLI to instantly fetch t-SNE (Rtsne) documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/rtsne
openTSNE — modular Python library for t-distributed Stochastic Neighbor Embedding. Implements Barnes-Hut and FIt-SNE (interpolation-based) acceleration for scalable O(n log n) / near-linear t-SNE on l
2 shared topics • 2 shared operations
t-SNE (t-distributed Stochastic Neighbor Embedding) for nonlinear dimensionality reduction and visualization of high-dimensional data. Covers Barnes-Hut and exact modes, FIt-SNE/openTSNE interpolation
2 shared topics • 2 shared operations
Use when working with Borzoi — a sequence-to-function DNA foundation model — for predicting genome-wide regulatory activity from DNA sequences. Borzoi predicts RNA-seq, ATAC-seq, ChIP-seq, and histone
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EBSeq is an R/Bioconductor package implementing an empirical Bayes hierarchical model for identifying differentially expressed (DE) genes and isoforms in RNA-seq experiments. It supports both two-cond
2 shared topics
sciPENN — neural network model for single-cell protein expression imputation and multi-omics integration. Transfers protein predictions from CITE-seq (paired RNA+protein) training data to unpaired RNA
2 shared topics