Join us for an exciting webinar showcasing ImmunoVerse, a comprehensive computational pipeline designed to analyze tumor RNA-Seq data and identify up to 11 classes of tumor-specific antigens. By applying ImmunoVerse to thousands of samples across 21 tumor types, we uncovered over 27,000 unique tumor-specific antigens—highlighting promising targets across multiple classes for next-generation cancer immunotherapies.
This webinar will cover:
The development and large-scale application of ImmunoVerse
Key findings from RNA-Seq and immunopeptidome integration
How the GUI-based workflow on the Cancer Genomics Cloud (CGC) simplifies complex bioinformatics analysis
A tour of the interactive web portal www.immuno-verse.com for clinical target prioritization
Don’t miss this opportunity to learn how ImmunoVerse is advancing precision oncology through scalable computational tools.
About the speaker
Dr. Guangyuan (Frank) Li
Dr. Li is a trained computational biologist and currently a postdoctoral fellow at the New York University Grossman School of Medicine. His research focuses on developing novel computational algorithms and pipelines that leverage deep learning, probabilistic modeling and statistical approaches to address complex biological problems. He has developed widely used computational tools in cancer immunotherapy and single-cell genomics, including DeepImmuno for predicting T-cell immunogenicity, SNAF for identifying tumor-specific splicing antigens, BayesTS for assessing the safety of tumor targets and scTriangulate to integrate multimodal single-cell data. His research has facilitated the discovery of actionable tumor antigens and has contributed to the establishment of comprehensive antigen databases.