Loading homepage
CellOracle — Python toolkit for gene regulatory network (GRN) inference and in silico transcription factor (TF) perturbation simulation from single-cell data. Builds cluster-specific GRNs by integrati
Use with AI
Install the MCP server or CLI to instantly fetch CellOracle documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/celloracle
CellChat — R package for inference, analysis, and visualization of cell-cell communication networks from single-cell RNA-seq data. Uses a curated ligand-receptor database (CellChatDB) to quantify sign
2 shared topics • 1 shared operation
NEURON — biophysically detailed multi-compartment neural simulation environment for modeling neurons and neural networks. Builds and runs Hodgkin-Huxley style conductance-based neuron models, morpholo
2 shared topics • 1 shared operation
SCENIC (pySCENIC) — gene regulatory network inference and transcription factor regulon analysis for single-cell RNA-seq data. Infers TF-target gene networks using GRNBoost2/GENIE3, refines regulons vi
2 shared topics • 1 shared operation
scJoint integrates atlas-scale single-cell RNA-seq and scATAC-seq data using transfer learning. Transfers cell type labels from annotated RNA datasets to unannotated ATAC datasets via joint neural net
2 shared topics • 1 shared operation
Use this skill for SCpubr workflows producing publication-quality visualizations of single-cell RNA-seq data in R. Covers UMAP/dimensionality reduction plots, violin plots, feature plots, dot plots, h
2 shared topics • 1 shared operation