CultureBotAI
Official@culturebotai
Offers specialized data engineering for microbial media standardization, LinkML schema validation, and ontological mapping of ingredient hierarchies.
Agent Skills by CultureBotAI
Showing 11 vetted skills indexed across 2 GitHub repositories.
CultureBotAIschema-gap-analysis
Validate CultureMech LinkML YAML instances and cluster validation failures across schema, instance, and process axes.
CultureBotAImatch-kg-microbe
Align CHEBI-annotated ingredient sets to KG-Microbe medium nodes and populate kg_microbe_match.
CultureBotAImanage-ingredient-hierarchy
Import ingredient family hierarchies from MediaIngredientMech into CultureMech recipes.
CultureBotAIreview-recipes
Validate microbial media recipe records for LinkML schema and CultureMech ID compliance.
CultureBotAIcreate-recipe
Generate schema-compliant CultureMech YAML records from text, JSON, or documents.
CultureBotAIgenerate-ingredient-umap
Generate interactive UMAP visualizations of CultureMech CHEBI ingredient embeddings.
CultureBotAIdeep-research-medium
Run a two-phase Edison literature workflow to extract organism growth evidence and recipe details for CultureMech media.
CultureBotAIaudit-schema-gaps
Audit CultureMech LinkML schemas and YAML instances for validation gaps.
CultureBotAImap-media-ingredients
Map media ingredient names to CHEBI, FOODON, and ENVO ontology terms.
CultureBotAIMerge Ingredients Skill
Merge duplicate ingredient records by CHEBI ID and name in MediaIngredientMech.
CultureBotAImanage-identifiers
Generate sequential zero-padded identifiers in RepoName:NNNNNN format and validate for duplicates and gaps.
Frequently Asked Questions About CultureBotAI
FAQPage SchemaWhat specific tasks can be performed using CultureBotAI?▼
CultureBotAI enables the validation of LinkML instances, mapping of media ingredients to standardized ontologies like CHEBI and FOODON, and the generation of schema-compliant YAML records. It also supports the auditing of schema gaps and the creation of UMAP visualizations for ingredient embeddings.
Which technical personas benefit from these capabilities?▼
Bioinformatics engineers, data curators, and microbial researchers benefit from these capabilities. The system is designed for professionals managing complex biological media datasets who require strict schema adherence, identifier management, and ontological alignment to ensure data integrity across large-scale research repositories.
What are the prerequisites for implementing these data management functions?▼
Implementation requires existing CultureMech or MediaIngredientMech repository structures. Users must have their source data prepared in text, JSON, or document formats to initiate the generation of schema-compliant records and ensure compatibility with the established LinkML validation frameworks and identifier naming conventions.