Two-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 Alexandro (Alex) Trevino, PhD, on how AI-powered algorithms within the Enable platform can facilitate comprehensive data storage, annotation, analysis, and search.
Webinar Part 1: Bridging Spatial Genomics and Spatial Proteomics with MaxFuse, a New AI-Powered Algorithm
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.
Interested in Part Two: Data Integration and Beyond: Creating and Leveraging Biological Atlases of Disease to Guide Drug Discovery – Watch Here>>
Related Posts
Accelerate Building Custom Spatial Proteomic Panels for New Biological Insights
Ultrasensitive Neuroimmune Biomarker Measurement for Translational Research and Therapeutic Development
Underdiagnosis of Alzheimer’s disease pathology in patients with cardiovascular disease
Decoding Neurodegeneration: High-plex Spatial Proteomics Reveal Distinct Cell Phenotypes and Pathological Signatures in Parkinson’s and Alzheimer’s Disease
In this webinar, Dr. Birgitt Schuele, Associate Professor (Research) of Pathology at Stanford University, showcases how ultrahigh-plex spatial proteomics is being used to uncover distinct cell phenotypes and pathological signatures…
Understanding the Brain: Advancing Neurodegeneration Research with Ultrahigh-Plex Spatial Proteomics
In this webinar, learn how ultrahigh-plex spatial phenotyping has been applied to neurodegenerative disease research.
p-Tau 205 and p-Tau 212: Emerging Biomarkers for Alzheimer’s Disease Research
Spatial Awareness: AI-powered Profiling of Trillions of Immune Cell Distribution Data Points Reveals Key Predictors of Cancer Recurrence Risk
This webinar highlights a groundbreaking study recently published as a Nature cover story (April 2025). Dr. Joe Yeong will describe how a pre-designed analytical framework—driven by well-defined clinical and scientific…
Multimodal Single-Cell Spatial Transcriptomics and Proteomics to Uncover the Biological Processes Driving Immunotherapy Response and Resistance in Renal Cancer
In this webinar, Dr. Anne-Laure Cattin from the Cancer Dynamics Laboratory at The Francis Crick Institute in London, will share her research on kidney cancer, focusing on the integration of…