Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: cell-fate-determination

영문 디렉토리

A comprehensive collection of ready-to-use scientific and research skills for AI agents.

31K
Stars
78/100
신뢰
카테고리: utility감사

Single-cell analysis in Python. Scales to >100M cells.

2.5K
Stars
80/100
신뢰
카테고리: geo-science감사

A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.

1.0K
Stars
84/100
신뢰
카테고리: geo-science감사

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

34K
Stars
77/100
신뢰
카테고리: data-analysis감사

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

34K
Stars
77/100
신뢰
카테고리: data-analysis감사

Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.

34K
Stars
67/100
신뢰
카테고리: research감사

When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.

25K
Stars
77/100
신뢰
카테고리: design-creative감사

An Industrial Grade Federated Learning Framework

6.1K
Stars
73/100
신뢰
카테고리: ml-automation감사

An overview of algorithms for estimating pseudotime in single-cell RNA-seq data

444
Stars
70/100
신뢰
카테고리: geo-science감사

Cell type annotation for single-cell RNA-seq using multi-LLM consensus

646
Stars
71/100
신뢰
카테고리: geo-science감사

Spatial Single Cell Analysis in Python

578
Stars
71/100
신뢰
카테고리: data-analysis감사

A tool for semi-automatic cell type classification

490
Stars
67/100
신뢰
카테고리: ml-automation감사