Orchestrate multi-step biomedical research workflows with code execution and integrated databases.
npx skills add https://github.com/rubensliv/k-dense-ai --skill biomni-rubensliv
Please help me install this Agent Skill. Skill: biomni Source: https://github.com/rubensliv/k-dense-ai/tree/main/scientific-skills/biomni Command: npx skills add https://github.com/rubensliv/k-dense-ai --skill biomni-rubensliv
Biomni enables autonomous execution of complex biomedical research tasks by decomposing multi-step queries into actionable sub-tasks, integrating code execution with rich biomedical knowledge sources, and producing reproducible results.
Run the biomni agent with your data lake and chosen LLM to begin autonomous biomedical research tasks.
High-intent search queries and answers about installing and using this skill.
Automate biomedical research workflows by deploying an autonomous AI agent that decomposes multi-step queries into actionable sub-tasks. It orchestrates code generation and execution against integrated biomedical databases to autonomously plan, execute, and report results.
Running multi-omics and scRNA-seq analysis without manual coding is achieved through an autonomous AI agent that generates analysis pipelines and executes code against a rich data lake. This integrates extensive biomedical knowledge sources for informed reasoning and reproducible results.
Yes, autonomous genomics and drug discovery tasks require configuring a data lake of approximately 11GB alongside an LLM provider. The environment setup also configures MCP servers, caches data, and saves reproducible conversation histories for robust execution.
Yes, you can use the AI agent for clinical data tasks and pharmacogenomics literature synthesis. It leverages integrated biomedical databases, literature, and ontologies to tackle diverse workflows, ensuring informed reasoning and reproducible result documentation.
Limitations for executing complex biomedical data tasks include the need for substantial environment setup, specifically an 11GB data lake and an LLM provider. The agent addresses execution constraints with robust error handling, security considerations, and result caching.
Yes, biomni supports reproducible conversation histories by caching data and saving execution logs during multi-step research workflows. This ensures end-to-end orchestration and task documentation remain robust and traceable across complex genomics or clinical data tasks.
pur3v4d3rExecute autonomous biomedical research tasks with code generation and database retrieval.
zerwizRoute genomics and omics tasks to relevant bioinformatics reference skills and pipelines.
Imad-OuteIntegrate biomedical data retrieval, analysis, and reasoning into automated research workflows.
jiaxiaojunQAQPlan and execute autonomous biomedical research tasks across multi-omics and clinical data.
