A central challenge in biology is to understand how DNA sequence and cellular context jointly shape gene expression, cell state, and response. Recent advances in AI are enabling predictive models of regulatory function from primary DNA sequence, alongside models of cellular programs and perturbation response. Connecting these efforts requires accounting for how cellular context shapes cis-regulatory activity and how regulatory sequences influence cellular programs. This connection is fundamental to understanding development and disease and predicting the effects of genetic variation and intervention.

The Keystone Symposia conference on AI and Gene Regulation Across Scales will examine which biological questions benefit from connecting regulatory scales, where doing so improves prediction and interpretation, and what measurements and perturbations are needed to test and improve these models. Discussions will consider applications in biotechnology and drug discovery, including interpreting disease-associated variation, prioritizing therapeutic targets, and predicting cellular responses to intervention. Attendees will gain a clearer understanding of current model capabilities and limitations, experimental approaches for evaluating predictions, and opportunities to connect models and experiments in their research.

By convening researchers across regulatory genomics, single-cell and spatial biology, perturbation biology, developmental and disease biology, and machine learning, the conference will define shared challenges, highlight emerging methods, and identify opportunities for new collaborations. The interactions between experimentalists generating molecular and cellular data and computational researchers developing predictive models will help identify the measurements and perturbations needed to improve models and use model predictions and limitations to guide new experiments.

Sequence-to-function and cell-state models are advancing rapidly within largely separate research communities. The conference brings these communities together to examine how their approaches can inform one another and link regulatory scales, advancing virtual cell models that account for the mechanisms underlying cellular behavior. In doing so, the conference will help shape a more unified view of gene regulation and clarify how AI and experimental biology can work together to reveal regulatory mechanisms across biological systems.

Unique Career Development Opportunities

This meeting will feature a Career Roundtable where trainees and early-career investigators will have the opportunity to interact with field leaders from across academic and industry sectors for essential career development advice and networking opportunities. Find out more about Career Roundtables here: https://www.keystonesymposia.org/diversity/career-development-initiatives