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2-Part Webinar Series 

Technologies for analyzing proteome, metabolome, transcriptome, and epigenome data at both spatial and single-cell levels have come a long way. Taken together, these methods provide a holistic view of biological processes and systems and reveal potential therapeutic targets. However, combining and integrating data from these diverse modalities and platforms presents a significant challenge. 

In this two-part GEN webinar series, our expert speakers Garry Nolan, PhD, (Part 1) will discuss MaxFuse, a new AI algorithm that provides reliable, fast, and cost-effective integration of spatial proteomic data with single-cell transcriptomic and epigenomic datasets. In part two, hear from Aaron Mayer, PhD, to learn all about the Enable CloudPlatform from Enable Medicine, and how MaxFuse leverages it to facilitate robust data generation to accelerate discovery and make progress towards clinical applications.

Webinar Part 1

Single-cell sequencing and spatial omics technologies can now profile diverse molecular readouts within cells and preserve their spatial context. However, integrating data across modalities (“cross-modal integration”) remains challenging, especially when the linked features between modalities are weak or uninformative. In this webinar, Garry Nolan introduces MaxFuse, a novel cross-modal data integration method that overcomes these limitations. MaxFuse enables the spatial consolidation of proteomic, transcriptomic, and epigenomic information at single-cell resolution opening exciting possibilities for dissecting complex biological processes.    

A live Q&A session followed the presentation, offering a chance to pose questions to our expert panelist.

Garry Nolan
Garry Nolan, PhD
Co-Founder, Akoya Biosciences  
Professor, Stanford University