Interpreting complex spatial biology data through unsupervised data analytics
Wednesday October 1, at 19:00 BST | 20:00 CEST | 14:00 EDT | 11:00 PDT
A single tissue section represents a cellular and molecular landscape of extraordinary complexity, waiting to be explored. However, past approaches have only tapped into a small fraction of the information hidden in their protein expression halting insights and clouding biotherapeutic discovery.
With advances in multiplexed imaging and cyclic staining technologies, researchers can now visualize dozens, and even hundreds of protein targets within a single tissue section. While this opens the door to unprecedented biological detail, it also introduces a significant challenge as we try to interpret and understand the vast amounts of data collected from the tissue.
In this webinar, Dr. Kevin Rychel-Penn, a spatial biology data scientist at Miltenyi Biotec, will demonstrate an advanced analysis workflow using 61-plex protein expression data from a colorectal carcinoma tumor microenvironment. Through cellular segmentation, dimensionality reduction (UMAP), clustering, spatial structure identification, and distance mapping, he will show how meaningful, high-impact insights can be extracted from complex tissue datasets.
Key learning objectives:
• Discover how to maximize the scientific value of your histology samples by using cyclical staining with the MACSima™ Platform on a large panel of antibodies.
• Understand how you can identify major expression patterns using unsupervised approaches to let the data guide your cell typing workflow.
• Learn how to use MACS® iQ View software to explore the spatial context of each of your cell types of interest with distance maps and structure identification.
Who should attend?
• Scientists and researchers in academia, biopharmaceuticals, biotechs and CROs who are utilizing spatial biology in their research workflows.
• Data scientists interested in unsupervised cell-typing approaches and spatial analysis methods.
• Immunologists, pathologists and cancer researchers interested in ways to explore the spatial context of tissue microenvironments.
Certificate of attendance
If you attend the live webinar, you will automatically receive a certificate of attendance, including a learning outcomes summary, for continuing education purposes.
If you view the on-demand webinar, you can request a certificate of attendance by emailing editor@selectscience.net.
Speakers
Dr. Kevin Rychel-Penn completed his PhD in Bioengineering at the University of California San Diego, where he worked on unsupervised machine learning approaches for interpreting RNA sequencing data. He is now a data scientist in spatial biology at Miltenyi Biotec. In this role, he performs analysis of multiplexed immunofluorescent imaging data for feasibility studies and academic collaborations, and builds automated workflows using Python™.
Moderator
