Topic: clawhub
924 skills in this topic.
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boltz
Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources.
For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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foldseek
Structure similarity search with Foldseek. Use this skill when: (1) Finding similar structures in PDB/AFDB databases, (2) Structural homology search, (3) Database queries by 3D structure, (4) Finding remote homologs not detected by sequence, (5) Clustering structures by similarity.
For sequence similarity, use uniprot BLAST. For structure prediction, use chai or boltz.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-genome-assembly-long-read-assembly
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-ribo-seq-ribosome-periodicity
Validate Ribo-seq data quality by checking 3-nucleotide periodicity and calculating P-site offsets. Use when assessing library quality or determining read offsets for downstream analysis.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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pydicom
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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rfdiffusion
Generate protein backbones using RFdiffusion, a diffusion-based generative model for de novo protein structure generation. Use this skill when: (1) Designing binder scaffolds for a target protein, (2) Generating novel protein backbones from scratch, (3) Scaffolding functional motifs into new proteins, (4) Specifying hotspot residues for interface design, (5) Creating symmetric oligomers.
For sequence design after backbone generation, use proteinmpnn. For structure validation, use alphafold or chai. For QC thresholds, use protein-qc.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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STAgent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-read-qc-umi-processing
Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate molecule counting is needed, such as in single-cell RNA-seq, low-input RNA-seq, or targeted sequencing to distinguish PCR from biological duplicates.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-geo-data
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-read-qc-quality-reports
Generate and interpret quality reports from FASTQ files using FastQC and MultiQC. Assess per-base quality, adapter content, GC bias, duplication levels, and overrepresented sequences. Use when performing initial QC on raw sequencing data or validating preprocessing results.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-read-alignment-star-alignment
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-immunoinformatics-neoantigen-prediction
Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell responses. Use when identifying vaccine targets or checkpoint inhibitor response biomarkers from tumor sequencing data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-long-read-sequencing-clair3-variants
Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-single-cell-multimodal-integration
Analyze multi-modal single-cell data (CITE-seq, Multiome, spatial). Use when working with data that measures multiple modalities per cell like RNA + protein or RNA + ATAC. Use when analyzing CITE-seq, Multiome, or other multi-modal single-cell data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-longitudinal-monitoring
Tracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or detecting molecular relapse before clinical progression.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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drug-labels-search
Search FDA drug labels with natural language queries. Official drug information, indications, and safety data via Valyu.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bioservices
Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-machine-learning-atlas-mapping
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-research-tools-biomarker-signature-studio
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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mage-antibody-generator
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-spatial-transcriptomics-spatial-neighbors
Build spatial neighbor graphs for spatial transcriptomics data using Squidpy. Compute k-nearest neighbors, Delaunay triangulation, and radius-based connectivity for downstream spatial analyses. Use when building spatial neighborhood graphs.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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tcell-exhaustion-analysis-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-metagenomics-functional-profiling
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009