Dr. Marcin P. Joachimiak — Principal Investigator

Dr. Marcin P. Joachimiak leads CultureBotAI and the development of KG-Microbe, the first comprehensive and ontology-grounded knowledge graph for microbiology research. As a staff researcher at Lawrence Berkeley National Laboratory (LBNL) and member of the Berkeley Bioinformatics Open-source Projects (BBOP), Dr. Joachimiak bridges artificial intelligence and microbial cultivation to advance microbiological discoveries.

Research Focus

Dr. Joachimiak’s research centers on developing AI-powered solutions for microbial research, with particular emphasis on:

  • Knowledge Graph Development: Leading the creation of KG-Microbe, a modular and scalable knowledge graph for microbiome and microbial sciences
  • AI for Cultivation: Applying machine learning and artificial intelligence methods for growth preference prediction and culture optimization
  • Data Integration: Developing frameworks for integrating diverse microbial data sources into unified, queryable knowledge systems
  • Ontology Development: Creating standardized vocabularies like METPO (Microbial Ecophysiological Trait and Phenotype Ontology) for microbiology research

Professional Affiliations

Lawrence Berkeley National Laboratory (LBNL)

  • Division: Environmental Genomics and Systems Biology Division
  • Role: Staff Scientist and Principal Investigator
  • Focus: Computational biology and bioinformatics for microbial systems

Berkeley Bioinformatics Open-source Projects (BBOP)

  • Role: Core team member
  • Contribution: Development of open-source bioinformatics tools and resources
  • Mission: Advancing biological research through collaborative, open-source software development

Key Projects

CultureBotAI

Principal investigator and founder of CultureBotAI, developing AI-powered solutions for microbial research, cultivation, and analysis that enhance laboratory workflows and accelerate microbiological discoveries.

KG-Microbe Knowledge Graph

Lead developer of KG-Microbe, a comprehensive knowledge graph that integrates diverse microbial data sources to enable AI-driven insights for growth preference prediction and culture optimization.

METPO Ontology

Creator of the Microbial Ecophysiological Trait and Phenotype Ontology, providing standardized vocabulary for growth preferences and experimental conditions in microbiology research.

Selected Publications

Recent Publication

Santangelo, B. E., Hegde, H., Caufield, J. H., Reese, J., Kliegr, T., Hunter, L. E., Lozupone, C. A., Mungall, C. J., & Joachimiak, M. P. (2026). KG-Microbe - Building Modular and Scalable Knowledge Graphs for Microbiome and Microbial Sciences. GigaScience, giag077. 10.1093/gigascience/giag077

This peer-reviewed article describes the development, architecture, and applications of KG-Microbe, demonstrating its potential for advancing microbiology research through AI-driven knowledge discovery.

Contact Information

  • Email: mjoachimiak@lbl.gov
  • Institution: Lawrence Berkeley National Laboratory
  • Division: Environmental Genomics and Systems Biology
  • GitHub: CultureBotAI Organization

Bibliography

  1. Santangelo BE, Hegde H, Caufield JH, Reese J, Kliegr T, Hunter LE, Lozupone CA, Mungall CJ, Joachimiak MP. KG-Microbe — Building Modular and Scalable Knowledge Graphs for Microbiome and Microbial Sciences. GigaScience. 2026;giag077. doi:10.1093/gigascience/giag077
  2. Máša P, Kliegr T, Joachimiak MP. Explainable rule-based prediction of cultivation media for microbes. Computational and Structural Biotechnology Journal. 2025;27:5194–5206. doi:10.1016/j.csbj.2025.10.014 · free full text
  3. Naseem S, Miller MA, Martinez-Gomez NC, Sun N, Joachimiak MP. MicroGrowAgents: An Agentic AI System for Microbial Cultivation Engineering. bioRxiv. 2026. doi:10.64898/2026.06.04.729985
  4. Joachimiak MP. Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1 [software]. DOE CODE; 2025. doi:10.11578/dc.20260210.3 · DOE CODE 175162
  5. Joachimiak MP, Miller MA, Caufield JH, Ly R, Harris NL, et al. The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies. Applied Ontology. 2024;19:408–418. doi:10.1177/15705838241304103
  6. Caufield JH, Hegde H, Emonet V, Harris NL, Joachimiak MP, et al. Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning. Bioinformatics. 2024;40(3):btae104. doi:10.1093/bioinformatics/btae104 · free full text
  7. Caufield JH, Putman T, Schaper K, Unni DR, Hegde H, et al. (incl. Joachimiak MP). KG-Hub — building and exchanging biological knowledge graphs. Bioinformatics. 2023;39(7):btad418. doi:10.1093/bioinformatics/btad418 · free full text
  8. Clark T, Caufield H, Parker JA, Al Manir S, Amorim E, et al. (31 authors, incl. Joachimiak M). AI-readiness criteria for biomedical data. bioRxiv. 2026 (v6; first posted 2024). doi:10.1101/2024.10.23.619844
  9. Joachimiak MP. “RuleML/GOBLIN COST Action Lecture on Data Science: Teaching AI to Teach Humans About Microbiology” [talk]. RuleML / COST GOBLIN Action Seminar; 2026. Recording

Full publication list →

Advancing microbiology through the convergence of artificial intelligence, knowledge graphs, and open science.