lamindb

Name: lamindb
Availability: InStock
Author: HolobiomicsLab

Track data provenance for biological workflows with lineage and ontology annotations.

4|1|Updated Jun 18, 2025

Search Tags:#ontology #bioinformatics #workflows #reproducibility #lineage #data-provenance #lamindb

Ready to run

npx skills add https://github.com/HolobiomicsLab/Toolomics --skill lamindb-holobiomicslab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: lamindb
Source: https://github.com/HolobiomicsLab/Toolomics/tree/main/mcp_host/skills/scientific-skills/scientific-skills/lamindb
Command: npx skills add https://github.com/HolobiomicsLab/Toolomics --skill lamindb-holobiomicslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

LaminDB provides end-to-end tracking and curation of biological data, ensuring reproducible workflows by capturing provenance.

Core Features & Use Cases

End-to-end data provenance tracking across Artifacts, Runs, and Transforms
Ontology-driven annotation and schema validation for standardized metadata
Seamless integrations with notebooks, pipelines, and storage backends (local and cloud)

Quick Start

Track a dataset, start a LaminDB session, load artifacts, validate schemas, and save curated outputs.

Frequently Asked Questions about lamindb

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I track data provenance for biological workflows?▼

Track data provenance for biological workflows by defining Artifacts, Runs, and Transforms to capture lineage. This approach uses guardrails like versioning and track/finish commands to ensure reproducible, auditable pipelines across local and cloud storage.

What is ontology-enabled annotation for reproducible bioinformatics?▼

Ontology-enabled annotation for reproducible bioinformatics applies standardized schemas and ontologies to biological metadata. This mechanism validates features against defined ontologies, ensuring consistent data curation and standardized lineage tracking across pipelines.

Can I integrate data provenance tracking across notebooks and cloud storage?▼

You can integrate data provenance tracking across notebooks, pipelines, and storage backends like cloud storage. This capability captures end-to-end lineage and tracks artifacts seamlessly across both local and cloud environments for reproducible science.

How do I start a session to validate schemas and save curated biological datasets?▼

To validate schemas and save curated biological datasets, start a session, load your artifacts, and apply ontology-driven schema validation. Finish by saving the curated outputs to maintain strict lineage tracking and data provenance.

Do I need to define transforms and runs to ensure auditable biological pipelines?▼

Yes, you need to define transforms and runs to ensure auditable biological pipelines. These definitions capture end-to-end data lineage, linking specific transformations to their input and output artifacts for full provenance tracking.