القائمة
Infer gene regulatory networks from single-cell data (pySCENIC for RNA-only, SCENIC+ for Multiome) and simulate TF perturbations with CellOracle.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Load BioMaster as one integrated skill-driven bioinformatics assistant.
BioMaster conversational bioinformatics assistant; starts workflows only after execution intent or empty activation.
Automated and marker-guided single-cell cell type annotation using CellTypist, marker review, reference transfer, and confidence-aware label curation.
Ligand-receptor communication inference in single-cell or spatial data with sender-receiver summaries and cautious interpretation.
Workflow for paired or integrated single-cell RNA and ATAC analysis with multimodal latent spaces and regulatory interpretation.
Workflow for spatial transcriptomics preprocessing, domain detection, deconvolution, neighborhood analysis, and publication-ready spatial maps.
| name | bioskills-grn-pipeline |
| description | Infer gene regulatory networks from single-cell data (pySCENIC for RNA-only, SCENIC+ for Multiome) and simulate TF perturbations with CellOracle. |
| domain | single-cell |
| primary_tool | pySCENIC |
| methods | ["pySCENIC","GRNBoost2","RcisTarget","AUCell","SCENIC+","cisTopic","pycistarget","CellOracle"] |
| macro_tags | ["gene-regulatory-network","regulon","perturbation-simulation","multiome","motif-enrichment"] |
| micro_tags | ["pySCENIC","GRNBoost2","RcisTarget","AUCell","SCENIC+","cisTopic","pycistarget","CellOracle","data-loading","path-selection","version-check","grnboost2","cistopic","grn-inference","rcistarget","motif-enrichment","regulon-pruning","aucell","scenicplus","egrn","qc","validation","celloracle","perturbation-simulation","knn-imputation"] |
| source | bioskills-grn-pipeline |
| status | active |
| enabled | true |
