Histolab automates tissue detection and tile extraction from gigapixel whole slide images. It processes WSI files to extract informative tiles for deep learning pipelines and medical research.

Access comprehensive genome-wide association study data from the NHGRI-EBI GWAS Catalog. Search variants by rs ID, trait, or gene to retrieve p-values, effect sizes, and summary statistics for genetic research.

Process and analyze genomic interval data for bioinformatics research. Gtars provides high-performance tools for overlap detection, coverage analysis, and ML tokenization of genomic sequences.

gget provides unified access to 20+ genomic databases through a simple CLI or Python interface. Query gene information, retrieve sequences, perform BLAST searches, and run enrichment analysis without managing multiple API connections.

Scientific computing tasks need hardware information to select optimal computational strategies. This skill automatically detects CPU cores, GPU availability, memory, and disk space, then generates recommendations for parallel processing and GPU acceleration.

GeoPandas extends pandas for geospatial operations. It enables reading shapefiles, GeoJSON, and PostGIS data. Perform spatial joins, buffer analysis, coordinate transformations, and create choropleth maps with matplotlib integration.

Flow cytometry data requires specialized file handling. FlowIO parses FCS files, extracts event data as NumPy arrays, and enables conversion to CSV formats for downstream analysis pipelines.

Access comprehensive FDA regulatory data including drug adverse events, medical device recalls, and safety information through the official openFDA API. Build pharmacovigilance and regulatory research workflows with Python.

Scientific data files come in hundreds of formats. This skill automatically detects file type, extracts metadata, assesses data quality, and generates comprehensive markdown reports with format-specific analysis recommendations.

DrugBank is a comprehensive bioinformatics database containing detailed drug information. This skill enables programmatic access to drug properties, interactions, targets, pathways, and chemical structures for pharmacology research and drug discovery.

Process and visualize next-generation sequencing data. Convert BAM to bigWig, generate quality control plots, and create publication-ready heatmaps for ChIP-seq, RNA-seq, and ATAC-seq experiments.

Predict molecular properties like solubility, toxicity, and binding affinity using DeepChem. Train graph neural networks or use pretrained models like ChemBERTa for drug discovery and materials science applications.

Access global statistical data from Data Commons including demographics, economics, health, and environmental indicators. Query population figures, GDP, unemployment rates, and geographic relationships using Python client methods.

Process datasets larger than available RAM using parallel computing. Transform single-machine pandas and NumPy workflows to run across multiple cores or distributed clusters without rewriting your code.

Metabolic modeling requires specialized knowledge of constraint-based reconstruction and analysis methods. COBRApy provides a comprehensive Python interface for flux balance analysis, gene knockout studies, and production envelope calculations for systems biology research.

Finding relevant clinical trials requires searching a large registry database. This skill provides a Python interface to query ClinicalTrials.gov API v2 to search trials by condition, drug, location, or sponsor and retrieve detailed study information.

Clinical documentation requires precision and regulatory compliance. This skill provides templates and validation tools for case reports, diagnostic reports, clinical trial documentation, and patient notes following HIPAA, FDA, and ICH-GCP standards.

Access the ChEMBL database to search compounds by structure and properties. Retrieve bioactivity measurements, find inhibitors, and perform structure-activity relationship studies for drug discovery research.

Access comprehensive enzyme kinetic data from the worlds largest enzyme database. Find Km values, reaction equations, organism-specific parameters, and substrate specificity data for biochemical research and metabolic engineering.

Query 40+ biological databases including UniProt, KEGG, and ChEMBL with a consistent Python API. Simplifies cross-database analysis and identifier conversion for bioinformatics research.