DBSCAN (Density-Based Spatial Clustering of Applications with Noise) — fast C++ implementation of density-based clustering algorithms in R. Includes DBSCAN, HDBSCAN, OPTICS/OPTICSXi, LOF outlier detec
Use with AI
Install the MCP server or CLI to instantly fetch DBSCAN documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/dbscan
CD-HIT — fast sequence clustering and redundancy reduction for protein and nucleotide sequences. Clusters FASTA sequences at a user-defined identity threshold to remove redundancy from databases. Prov
1 shared topic • 1 shared operation
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
1 shared topic • 1 shared operation
scGen — deep learning framework for predicting single-cell perturbation responses using variational autoencoders. Predicts how cells respond to unseen conditions (drug treatment, genetic knockout, dis
1 shared topic • 1 shared operation
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
1 shared topic • 1 shared operation
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
1 shared topic • 1 shared operation