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Topic: openclaw

3,425 skills in this topic.

bayesian-optimizer
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-population-genetics-scikit-allel-analysis
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-sra-data
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metagenomics-abundance Species abundance estimation using Bracken with Kraken2 output. Redistributes reads from higher taxonomic levels to species for more accurate estimates. Use when accurate species-level abundances are needed from Kraken2 classification output.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-systems-biology-flux-balance-analysis
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-workflows-crispr-screen-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bgpt-paper-search Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-metabolite-annotation Metabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities to detected features in untargeted metabolomics.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-lipidomics Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-vcf-manipulation Merge, concatenate, sort, intersect, and subset VCF files using bcftools. Use when combining variant files, comparing call sets, or restructuring VCF data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
binding-characterization Guidance for SPR and BLI binding characterization experiments. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-workflows-chipseq-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-workflows-biomarker-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-admet-prediction Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts. Use when filtering compounds for drug-likeness or prioritizing leads by predicted safety.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-normalization-qc Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-substructure-search Searches molecular libraries for substructure matches using SMARTS patterns with RDKit. Filters compounds by pharmacophore features, functional groups, or scaffold matches with atom mapping. Use when finding compounds containing specific chemical moieties or filtering libraries by structural features.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-alignment-msa-parsing Parse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis. Use when parsing or manipulating multiple sequence alignments.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-spatial-transcriptomics-spatial-proteomics Analyzes spatial proteomics data from CODEX, IMC, and MIBI platforms including cell segmentation and protein colocalization. Use when working with multiplexed imaging data, analyzing protein spatial patterns, or integrating spatial proteomics with transcriptomics.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-reporting-quarto-reports
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-spatial-transcriptomics-spatial-preprocessing Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes. Use when filtering and normalizing spatial transcriptomics data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-single-cell-preprocessing Quality control, filtering, and normalization for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for calculating QC metrics, filtering cells and genes, normalizing counts, identifying highly variable genes, and scaling data. Use when filtering, normalizing, and selecting features in single-cell data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-causal-genomics-fine-mapping Identify likely causal variants within GWAS loci using SuSiE for sum of single effects regression and FINEMAP for shotgun stochastic search. Computes posterior inclusion probabilities and credible sets to prioritize variants for functional follow-up. Use when narrowing GWAS association signals to candidate causal variants or building credible sets for functional validation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-causal-genomics-mendelian-randomization Estimate causal effects between exposures and outcomes using genetic variants as instrumental variables with TwoSampleMR. Implements IVW, MR-Egger, weighted median, and MR-PRESSO methods for robust causal inference from GWAS summary statistics. Use when testing whether an exposure causally affects an outcome using genetic instruments.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-causal-genomics-pleiotropy-detection Detect and correct for horizontal pleiotropy in Mendelian randomization analyses using MR-PRESSO for outlier removal, MR-Egger regression for directional pleiotropy, and Steiger filtering for variant directionality. Use when validating MR results, detecting pleiotropic instruments, or running sensitivity analyses for causal inference.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009