菜单
Build a tissue/condition-specific metabolic model by constraining a generic genome-scale model with transcriptomics data using GIMME, iMAT, or GTEx-based tissue extraction, then validate against the original model.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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-context-specific-models |
| description | Build a tissue/condition-specific metabolic model by constraining a generic genome-scale model with transcriptomics data using GIMME, iMAT, or GTEx-based tissue extraction, then validate against the original model. |
| domain | single-cell |
| primary_tool | COBRApy |
| methods | ["cobra","GIMME","iMAT","numpy","pandas"] |
| macro_tags | ["context-specific-model","metabolic-modeling","transcriptomics-integration","GIMME","iMAT","tissue-specific"] |
| micro_tags | ["cobra","GIMME","iMAT","numpy","pandas","gpr-mapping","normalization","biomass-constraint","milp","gtex","fba","validation"] |
| source | bioskills-context-specific-models |
| status | active |
| enabled | true |
