Data Management

This skill provides comprehensive documentation for integrating with OMERO, an open-source platform for managing microscopy images. It covers connection management, data access, image processing, ROI creation, metadata annotations, OMERO tables, and server-side scripts for batch operations in scientific imaging workflows.

This skill provides comprehensive documentation for integrating with the LatchBio platform for bioinformatics workflows. It covers workflow creation using Python decorators, cloud data management with LatchFile/LatchDir, resource configuration for CPU/GPU tasks, and pre-built verified workflows like AlphaFold and DESeq2. No code is executed - it serves as a reference guide.

This skill provides programmatic access to LabArchives electronic lab notebook platform. It enables users to authenticate, list and backup notebooks, create entries, upload attachments, and integrate with third-party scientific tools like Protocols.io, Jupyter, and REDCap for research documentation workflows.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.