Single-cell and Spatial ONLINE Webinar 1: Marrying Single-cell and Spatial Biology for a More Complete Understanding of Disease

Join us for Single-cell and Spatial Online to find out how the experts are moving towards a more holistic single-cell and spatial methodology to achieve a tissue-centric understanding of disease.

Over the next three webinars you’ll learn how a spatially resolved approach to single-cell studies restores the context of cellular communication and interaction, currently missing from standard single-cell approaches.

You will also be introduced to the latest computational methods being developed to support cell-type clustering, cellular niche analysis and for integrating the structural, organisational, and functional descriptions of tissues.

Finally, our speakers will showcase examples of how multi-omics is being integrated into both single-cell and spatial investigations to understand the role of each omic layer in disease.

Webinar 1: Marrying Single-cell and Spatial Biology for a More Complete Understanding of Disease

Tuesday 6th February at 3pm GMT / 4pm CET / 10am EST

In this webinar, our speakers will showcase how they’re weaving single-cell and spatial methods together in their studies to paint a high-resolution picture of complex tissues.

Advance Single-cell Data Integration to Map Pathological Changes in Cancer – Frederik De Smet, Associate Professor, KU Leuven

Single-cell Spatial Omics Journey to Signalling and Metabolism of Immunity, Cancer, and Aging – Ahmet Coskun, Bernie Marcus Early-Career Professor, Georgia Institute of Technology & Emory University

Highly Multiplexed Imaging of Tissues with Subcellular Resolution by Imaging Mass Cytometry – Bernd Bodenmiller, Director, Department of Quantitative Biomedicine, University of Zurich

Upcoming webinars in this series:

Webinar 2: Advanced Computational Tools to Support Single-cell and Spatial Data Analysis

Sponsored by Parse Biosciences

Tuesday 13th February at 3pm GMT / 4pm CET / 10am EST

Data, data and more data. Single-cell sequencing, and spatial profiling produce vast quantities of complex data. To handle this, you will need a strong bioinformatic know-how and effective integration methodologies.

In this webinar, our speakers will demonstrate some of the latest computational tools that will help you gain meaningful biological insights from this huge amount of data.

Multi-scale Transcriptional Descriptions of Heart Failure for a Tissue-Centric Understanding of Disease- Ricardo Ramirez-Flores, Postdoc (Julio Saez-Rodriguez Lab), Heidelberg University

Broadening Horizons in Single Cell: A path to the 10M Cell Atlas - Mike Day, District Sales Manager, Parse Biosciences

Computational Reconstruction of Tissue Complexity from Spatial Transcriptomics - Francesca Finotello, Assistant Professor and Group Lead (Computational Biomedicine), University of Innsbruck

Benchmarking Cell-Type Clustering Methods for Spatially Resolved Transcriptomics Data - Wei Vivian Li, Assistant Professor, UC California Riverside

Webinar 3: Single-cell and Spatial Multi-omics for Intricate Disease Insights

Sponsored by 10x Genomics

Tuesday 20th February at 3pm GMT / 4pm CET / 10am EST

By interrogating each of the distinct omic layers at the single-cell level, we can begin to unwind the complex molecular hierarchy and develop a more comprehensive understanding of cell biology.

In this webinar, you will discover how the latest multi-omics approaches to single-cell and spatial are helping to unpick genotype-phenotype correlations and disease processes.

Using Single-cell Multi-omics to Show Divergent Immune Cell Selection and Immunosuppressive Mechanisms Between Patient Groups – Rachel Bashford-Rodgers, Associate Professor, University of Oxford

Disease Evolution in Multiple Sclerosis: Insights from Single-cell and Spatial Omics - Gonçalo Castelo-Branco, Professor, Karolinska Institutet

Resolving Form, Function, Time & Mechanism at the Tumor-Immune Interface - Garry Nolan, Rachford and Carlota A. Harris Professor, Department of Microbiology and Immunology, Stanford University School of Medicine