This Genome Biology special issue is guest edited by Peter Koo of Cold Spring Harbor Laboratory, Sara Mostafavi of the University of Washington, and Asa Ben-Hur of Colorado State University.
Deep learning models have demonstrated a powerful ability to accurately model various genomics data. However, their impact on biology depends on the ability to interpret the models and discover new findings. We would like to invite submissions that focus on this aspect of deep learning: new methods for making interpretable predictions for genomics data or studies that demonstrate the ability of these architectures to make novel biological discoveries.
Genome Biology highlights timely advances in interpretable deep learning with applications in genomics.