Alzheimer’s disease is one of the most complex challenges in neurodegenerative disease research, not because we lack data, but because the biology is difficult to connect.

Researchers today generate large amounts of genetic and transcriptomic data, yet translating these signals into biological mechanisms and testable hypotheses remains a major bottleneck.

If this sounds familiar:

- You have GWAS hits but don’t know which genes are actually driving biology

- Known pathways don’t fully explain disease progression

- You need a better way to move from gene lists to actionable insights

This webinar is for you.

 

🎙️ Speakers

Join Camila Guerrero, PhD (Translational Bioinformatics, Mavatar) and
Tomas Deierborg, Professor Neuroinflammation, Lunds University for a practical session on how systems biology and transcriptomics can advance Alzheimer’s disease research.

 

🔬 What will I Learn in this Alzheimer's webinar?

You will learn how to connect GWAS signals to biological mechanisms using transcriptomic data and network-based analysis.

In this session, we will start from a real, published case:
research identifying galectin-3 (LGALS3) as a central regulator of microglial activation in Alzheimer’s disease.

Using this as a foundation, we will demonstrate how a network-based, transcriptomics-driven approach can:

- Move from GWAS signals to connected biological networks

- Map interactions between key genes such as LGALS3, TREM2, and APOE

- Characterize microglial activation and neuroinflammatory processes

- Generate new hypotheses and potential targets beyond current literature

This session explores how researchers can move from genetic signals to biological mechanisms in Alzheimer’s disease using data-driven approaches.


Who is this webinar for?


Researchers working in Alzheimer’s disease, neurodegeneration, translational research, and drug discovery.

 

🎁 Bonus for Participants

- Free trial access to Mavatar Discovery

- A guided workflow to explore your own genes and pathways

 

💡 What makes this approach different?


Unlike traditional pathway tools, this approach reveals data-driven biological relationships beyond known literature. 

Most tools show what is already known.

The real opportunity is to understand what the data reveals beyond that.

Featuring research perspectives from Lund University and real-world applications in Alzheimer’s disease biology.

 

Sign up here!