What is open science, and why does it matter for today’s research ecosystem? Does making research outputs openly available contribute to greater transparency, reproducibility and scientific integrity? This lecture will provide an introduction to the principles, values and key components of open science. Participants will explore its historical development, its objectives, and the challenges it faces, particularly in relation to research assessment and academic incentives.

Genomic Al models have achieved strong performance in predicting functional genomics data, suggesting they capture key features underlying gene regulation. However, their black-box nature makes it challenging to determine whether they truly learn meaningful biological mechanisms. In this talk, I will present a suite of perturbation-based interpretation methods that leverage in silico mutations to identify the sequence features and combinatorial interactions that drive regulatory activity. These methods support interpretation across multiple scales--from individual nucleotides to entire cis-regulatory elements- revealing complex dependencies and generalizable cis-regulatory principles. In the second part of the talk, I will introduce DNA Discrete Diffusion (D3), a generative Al framework based on discrete diffusion for designing regulatory DNA sequences with tunable activity levels. D3 enables cell type-specific sequence generation, captures diverse regulatory patterns, and enhances the performance of predictive models when used to augment training data in low-data regimes. Together, these approaches demonstrate how predictive and generative Al can advance bioloqical discovery by deepening our understanding o gene regulation and enabling the machine-guided design of regulatory sequences.
For more see the abstract_file: Abstract-File

Aim:
You will learn to visually communicate your complex research ideas and results so your messages are effortlessly understood by any specific audience (scientists or non-scientists). We will not focus on aesthetics but on how understanding human visual perception can inform your design decision for better comprehension of your scientific images, posters, and slides. You will also design a graphical abstract of your research, discuss it with peer scientists in a group exercise, and get actionable advice and feedback on your own materials. It is an immersive workshop, comprehensive, structured, memorable, easy to follow, useful and fun. More at https://www.seyens.com

Contents & Method:
The training is offered as blended learning that combines a self-study module and a live online workshop. All participants get 12 month access to all materials.

1. Self-study via an online platform (6-8 hours of engaging video content & a useful assignment):
1.1. Communicating with scientific vs non-scientific audiences
1.2. Visual perception and what humans find intuitive
1.3. Layout: simplifying comprehension through structured layout
1.4. Eye-flow: effortlessly guide the audience through the design
1.5. Colors: how to amplify, not ‘fancify’
1.6. Typography for legibility, structure and aesthetics
1.7. Digital images in science: the optimal use of vector and raster images
1.8. Slides that amplify messages and don't distract when presenting
1.9. Posters: strategy and process for creating posters that attract and explain
1.10. Homework: participants submit images and slides to the trainer to receive feedback
2. Live Online Workshop (April 10, 2025, 9 am – 1 pm via Zoom, interactive and hands-on)
2.1. Recap of fundamentals and Q&A: trainer facilitates an effective recap of lessons learned in self-study module and answers all further questions.
2.2. Exercises & group work: participants draw a graphical abstract of their research and share their posters and we form groups so everyone gives and receives informed feedback.

Discussion on pre-submitted materials: participants receive actionable suggestions on how to improve their own images and slides from the trainer and on posters from fellow researchers.