AlphaGenome is Google DeepMind's AI model for decoding how DNA sequences control gene activity, and how a single mutation can disrupt that regulation. This beginner-friendly, hands-on session introduces AlphaGenome from the ground up: what it predicts, how it works at a high level, and why it matters for genomics and disease research.

We'll work through a real genomics question together, from hypothesis to result, so you leave not only understanding what AlphaGenome is, but also how to start using it in your own work.

Workshop Plan (2 hrs):

• Slides (~20–25 minutes): Introduce the core concepts, what AlphaGenome is, the problem it solves, and what its inputs and outputs represent, framed for both technical and non-technical attendees.

• Live, Guided Group Problem-Solving (~30–35 minutes): I'll present a carefully chosen real genomics problem, and we'll work through it together live. I'll drive the coding while you drive the reasoning and decision-making, building toward a genuine conclusion as a group.

• Kahoot Check-in: A short interactive quiz to ensure the key concepts are understood before moving on to the practical section.

• Wrap-up: A tour of the official AlphaGenome tutorials and resources, so you know exactly where to continue exploring with your own data.

This foundational session introduces participants to the intersection of AI and genomics through AlphaGenome. We will explore the fundamentals of genomic data, learn how to process DNA sequences using Python, and build a simple AI-powered genomic workflow from scratch.

Through hands-on examples based on the AlphaGenome tutorials, attendees will discover how machine learning can help analyse genetic information and gain the practical skills needed to start using AI for scientific research.

Recommend for:

• Early-Career Researchers & Academics

• PhD Students & Postdocs: Especially those in genetics, molecular biology, or biochemistry who want to incorporate AI into their research but don't know where to start.

• Bioinformaticians: Particularly traditional bioinformaticians who are highly skilled in genomics but want a gentle, structured introduction to Google DeepMind's specific AI workflows.

• Data Scientists & ML Engineers: Technical professionals who understand AI code but want to see a real-world application in genomics and understand what the inputs/outputs actually mean in a biological context.

• Computational Biology Students: Undergraduate or Master's students looking for practical skills and exposure to cutting-edge industry tools like AlphaGenome.

• Wet-Lab Biologists / Geneticists: Scientists and lab techs who want to understand the "dry-lab" (computational) side of predicting mutation impacts.

Requirements:

• Python and/or Genomics skills will be helpful but not essential, as we will build from the basics.

• Google account to access Google Colab.