Topic: openclaw
3,425 skills in this topic.
-
bio-experimental-design-batch-design
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
cytokine-storm-analysis-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-population-genetics-linkage-disequilibrium
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-spatial-transcriptomics-spatial-statistics
Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment. Use when computing spatial autocorrelation or co-occurrence statistics.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
pan-cancer-multiomics-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
microbiome-cancer-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-expression-matrix-gene-id-mapping
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
goal-analyzer
分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
spatial-deconvolution
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-ribo-seq-orf-detection
Detect and quantify translated ORFs from Ribo-seq data including uORFs and novel ORFs using RiboCode and ORFquant. Use when identifying translated regions beyond annotated coding sequences or quantifying ORF-level translation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-single-cell-doublet-detection
Detect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R). Essential QC step before clustering to avoid artificial cell populations. Use when identifying and removing doublets from scRNA-seq data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
STAgent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-clinical-databases-hla-typing
Call HLA alleles from NGS data using OptiType, HLA-HD, or arcasHLA for immunogenomics applications. Use when determining HLA genotype for transplant matching, neoantigen prediction, or pharmacogenomic screening.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
struct-predictor
Local protein structure prediction with AlphaFold, Boltz, or Chai. Compare predicted structures, compute RMSD, visualise 3D models.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-genome-engineering-base-editing-design
Design guides for cytosine and adenine base editing using editing window optimization and BE-Hive outcome prediction. Select optimal positions for C-to-T or A-to-G conversions without double-strand breaks. Use when designing base editor experiments for precise nucleotide changes.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-variant-calling-joint-calling
Joint genotype calling across multiple samples using GATK CombineGVCFs and GenotypeGVCFs. Essential for cohort studies, population genetics, and leveraging VQSR. Use when performing joint genotyping across multiple samples.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-multi-omics-similarity-network
Similarity Network Fusion (SNF) for patient stratification using multi-omics data. Integrates multiple data types into a unified patient similarity network. Use when performing patient stratification or integrating multi-omics data into unified similarity networks.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-epidemiological-genomics-amr-surveillance
Detect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-genome-assembly-assembly-polishing
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
bio-atac-seq-atac-qc
Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
SpatialAgent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
-
differentiation-schemes
Select and apply numerical differentiation schemes for PDE/ODE discretization. Use when choosing finite difference/volume/spectral schemes, building stencils, handling boundaries, estimating truncation error, or analyzing dispersion and dissipation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009