Recent advances in artificial intelligence, including machine learning, deep learning, large language models (LLMs), and foundation models, together with high-throughput biotechnologies, are transforming biological and biomedical research. Integrating diverse data types—including genomics, transcriptomics, proteomics, metabolomics, microbiome, imaging, and clinical data—has become essential for understanding complex biological systems and accelerating translational discoveries.

M³AI-Bio 2026 provides an international forum for researchers working at the intersection of artificial intelligence, systems biology, and translational bioinformatics. The workshop focuses on multimodal and multi-omics data integration, interpretable AI, foundation models, and computational approaches for biological knowledge discovery. We welcome original research that advances AI-driven methodologies for understanding biological processes, disease mechanisms, biomarker discovery, and precision medicine.

September 27, 2026: Full workshop paper submission deadline 

October 18, 2026: Notification of paper acceptance to authors 

November 8, 2026: Camera-ready papers due 

December 1–4, 2026: Workshop (held in conjunction with the conference) 

M³AI-Bio 2026 invites original and unpublished research papers on artificial intelligence, multimodal learning, and multi-omics data integration for systems biology and translational bioinformatics.

The workshop provides an international forum for researchers from academia and industry to present innovative methodologies, computational tools, and real-world applications for analysing complex biological and biomedical systems.

Topics of interest include, but are not limited to:

•  Multi-omics data integration and analysis  

• Multimodal data integration in biological and biomedical systems  

• Integration of omics data with imaging, phenotypic, environmental and biomedical applications 

• Cross-domain and cross-species data integration  

• Machine learning, deep learning, foundation models, and AI-driven methods for biological data integration 

• Large language models, foundation models, and generative AI for biological data  

• Interpretable, robust, and scalable AI methods  

• Knowledge-driven and hybrid computational modelling approaches  

•  Reconstruction and analysis of biological networks and pathways  

•  Modelling and simulation of regulatory, signalling, and metabolic networks  

• Genomics, transcriptomics, and epigenomics data analysis  

• Single-cell and spatial multi-omics data analysis and visualisation 

• Microbiome and metagenomics data analysis and integration  

• Time-series and dynamic biological data analysis  

• Biomarker discovery using integrative approaches  

• Drug discovery and repurposing using multi-omics data  

• Translational bioinformatics and precision medicine  

• Complex network analysis in systems biology 

Accepted papers will be included in the IEEE BIBM 2026 Conference Proceedings.

🌍 Hybrid Participation🌍
The workshop is planned to support both onsite and online participation, enabling researchers from around the world to present and engage with the scientific community.

📄 IEEE Conference Proceedings📄
All accepted workshop papers will be published in the IEEE BIBM 2026 Conference Proceedings by the IEEE Computer Society Press.

🤝 Integrated with IEEE BIBM 2026🤝
Workshop participants will have access to the broader IEEE BIBM 2026 conference, including keynote lectures, technical sessions, and networking opportunities.