Unlock new insights in immunotherapy and precision medicine by attending our webinar, “Advanced Bioinformatic Analysis of Single-Cell RNA Sequencing Data,” hosted by Immudex and Ardigen. This session will explore cutting-edge bioinformatics methodologies and the integration of Immudex’s dCODE® technology with scRNA-seq to enhance your research outcomes, featuring expert presentations and practical examples.
What you’ll learn:
Understanding of T and B cell specificity
- Learn how Immudex’s dCODE Dextamer® and dCODE Klickmer® technology can transform your understanding of T and B cell specificity.
- Discover how to leverage this technology to achieve precise immune profiling in your research.
Comprehensive bioinformatics knowledge
- Gain in-depth knowledge of bioinformatics analysis of single-cell RNA sequencing (scRNA-seq) data.
- Understand step-by-step bioinformatics workflows and see how they are applied in real-world scenarios.
Expert experimentation strategies
- Learn best practices for planning and executing experiments using multiple dCODE® products.
- Understand the importance of well-structured experimental design for maximizing data relevance and accuracy.
Interactive learning experience
- Participate in an interactive Q&A session with leading scientists and bioinformatics experts from Immudex and Ardigen.
- Get your specific questions answered and receive tailored advice for your research challenges.
Cutting-Edge Research Techniques
- Access advanced methodologies and practical examples that you can apply directly to your research.
- Gain insights into the latest advancements in bioinformatics and immunotherapy.
Meet our speakers:

Jaime James, PhD
Jaime holds a PhD in Immunology from the Karolinska Institute where she specialized in T cell signaling. She’s also worked as a scientist at a CRO focusing on inflammatory models before joining Immudex where she helps our customers with everything from enquiries to
troubleshooting.

Jakub Widawski
Jakub is specialising in single-cell RNA-Seq data. He develops cutting-edge bioinformatics pipelines for processing and analysis of clinical data, contributing to advancements in drug discovery. Jakub also builds user-friendly applications for data exploration and visualisation, increasing the accessibility of advanced bioinformatic methods to non-programmers. His recent work has centred on integrating and modelling the vast amount of transcriptomics data generated over the years, to better understand the changes that occur at a single-cell level across various conditions and to maximise the insights that can be extracted from this data modality.