Spatial Biomarkers in Immuno-Oncology: Recent Developments and Future Directions
Recent developments in the study of spatial biomarkers continue to demonstrate the predictive power of this new class of biomarker assays.
CODEX Is Now PhenoCycler
A Beginner’s Guide to CODEX
The interactions that a cell has within its microenvironment are key in determining both its function and fate. The ability to elucidate these cell-cell interactions within a tissue microenvironment is critical to the understanding of both tissue homeostasis and disease processes.
Home Resources Webinars Understanding Spatial Phenotyping: A Webinar Series by Akoya Academy Webinar Series | August 24 – September 7, 2021 Analyzing the cellular
In this webinar, we’ll share how phenoptrReports provides powerful, easy-to-use tools to analyze spatial relationships between cellular phenotypes and visualize their relationships overlaid on
Best practices and guidelines to move your manual assay to your favorite autostainer (Leica Bond RX, Roche Discovery Ultra). We will review Opal Manual
In this webinar Dr. Jonah Cool, Program Officer for Single-Cell Biology at the Chan Zuckerberg Initiative, provides an overview of single-cell efforts at CZI;
Immune checkpoint inhibitors are revolutionizing cancer therapy for many. But robust biomarkers are needed to predict which patients will likely benefit from these therapies.
Hear from Oliver Braubach, Ph.D., Senior Manager, Applications at Akoya Biosciences on the importance of single cell resolution in spatial biology , how to
In this presentation, from the 2021 Spatial Biology Europe Congress, Gavin Gordon, Ph.D., Vice President, Clinical Market Development from Akoya Biosciences describes evolving biomarker
Recent studies strongly suggest the importance of determining a patient’s Immunoscore as well as the need for a more comprehensive understanding, both spatially and
In this multi-part webinar series, our expert speakers review analytical frameworks and algorithms to integrate imaging-based single-cell spatial phenotyping data with complementary transcriptomic and