About Workshop
Spatial biology and digital histopathology are transforming biomedical research by enabling high-resolution analysis of gene expression, cellular organization, and disease microenvironments within intact tissues. When integrated with Artificial Intelligence, these approaches allow precise mapping of tissue architecture, tumor heterogeneity, and disease progression, advancing both research and clinical diagnostics.
This 3-day international virtual workshop provides a structured introduction to AI-driven spatial biology, covering digital histopathology, spatial transcriptomics, and computational pathology. Participants will learn how AI supports tissue image interpretation and spatial omics analysis through conceptual explanations and guided, no-code hands-on demonstrations using publicly available tools and datasets. Designed for a global audience of students, researchers, clinicians, pathologists, biomedical engineers, and AI professionals, the program highlights real-world applications in cancer research, neuroscience, immunology, and precision medicine.
Aim
This workshop aims to provide a no-code, practical introduction to AI in Spatial Biology and Digital Histopathology, covering tissue architecture, spatial omics, Tumor Microenvironment, AI-based image analysis, and multimodal data interpretation. Participants will learn how these technologies support biomarker discovery, computational pathology, precision medicine, and clinical research through guided demonstrations using real-world public datasets.
What Participants Will Learn
- Introduce fundamentals of spatial biology and tissue microenvironments
- Explain principles of digital histopathology and computational pathology
- Demonstrate integration of AI in tissue image analysis
- Train participants in spatial gene expression and mapping concepts
- Explore applications in cancer heterogeneity and disease progression
- Develop understanding of AI-driven tissue-level diagnostics
Structure
📅 Day 1: Foundations – Spatial Biology, Tissue Architecture & Digital Histopathology
- Core concepts of spatial biology: tissue architecture, cellular organization, and why location matters in health and disease
- Fundamentals of digital histopathology and how whole-slide images capture morphology
- Introduction to spatial omics and the Tumor Microenvironment (TME): heterogeneity, cellular neighborhoods, and key biological patterns
- How AI assists interpretation of tissue-level data (conceptual overview only – no algorithms)
🛠️ Hands-on
- Guided exploration of the Human Protein Atlas: locate and compare protein-expression patterns across normal and disease tissues
- Interpret spatial organization and note 2–3 biologically meaningful differences under mentor guidance
📅 Day 2: AI-Enabled Analysis – Tissue Image Interpretation & Spatial Omics
- Practical role of AI and computer vision in digital pathology: cell segmentation, pattern recognition, and image embeddings (high-level)
- Reading spatial gene-expression data: cellular heterogeneity and neighborhood analysis
- Linking imaging features with molecular (spatial omics) information for biomarker clues
- Live mentor walkthrough of interpretation logic using public datasets
🛠️ Hands-on
- Explore cell populations and spatial gene-expression patterns in CellxGene (public spatial datasets)
- Interpret a NanoString GeoMx spatial dataset: identify one clear biological pattern or neighborhood and record key observations
📅 Day 3: Application & Integration – From Spatial Insights to Precision Pathology Workflows
- AI-supported computational pathology in cancer and complex diseases: digital biomarkers and patient stratification
- Combining histopathology + spatial omics + AI insights for translational questions
- Designing a simple, realistic Spatial AI → Biomarker → Precision Medicine workflow
- Clinical relevance, current limitations, and emerging trends (foundation models at a conceptual level)
🛠️ Hands-on
- Work through a provided case-based AI spatial pathology workflow (tissue architecture → key findings → biomarker hypothesis)
- Complete a one-page conceptual workflow template for a research or clinical question of interest and receive brief mentor feedback
Important Dates
Registration Ends
4:30 PM IST
Workshop Dates
2026-09-02
05:30PM
05:30PM
What You Will Gain
- Live interactive training sessions
- Spatial biology workflow guides
- Digital histopathology interpretation templates
- AI-based tissue analysis case studies
- Spatial omics conceptual frameworks
- Computational pathology learning materials
- Certificate of Participation
Outcomes
- Understand spatial organization of biological tissues
- Interpret histopathology using AI concepts
- Apply spatial biology principles in disease research
- Analyze tissue microenvironment and heterogeneity
- Understand integration of imaging and omics data
- Design conceptual AI-driven spatial pathology workflows
Who Should Attend
This program is designed for Undergraduate and Postgraduate students in Life Sciences, Biotechnology, Biomedical Sciences, and Medical fields, as well as Ph.D. Scholars and Research Fellows. It is also suitable for Faculty Members, Academicians, Pathologists, and Clinical Researchers working in healthcare and diagnostics. Additionally, Biomedical Engineers, AI Researchers, Bioinformatics and Computational Biology professionals, Biotechnology and Healthcare industry professionals, and Data Scientists working in medical imaging and spatial omics will benefit from this workshop.
Deliverables
- Live interactive training sessions
- Spatial biology workflow guides
- Digital histopathology interpretation templates
- AI-based tissue analysis case studies
- Spatial omics conceptual frameworks
- Computational pathology learning materials
- Certificate of Participation