Oct 23, 2023, 3:00 pm4:00 pm


Event Description

The cis-regulatory code that instructs gene regulation during development, also known as the genome’s second code, is a fundamentally unresolved problem. Recent progress has provided proof-of-principle evidence that this complex cis-regulatory code can be learned with neural networks. The new approach is fundamentally different from traditional methods in that the sequence rules are learned inside a black box directly from genomic sequences through their ability to better predict a specific genomics data set. This dramatically improves the predictive performance, but requires rigorous approaches for extracting, understanding and validating the learned sequence rules to make sure that they represent biology. I will describe how we use this approach using Drosophila or mouse development as model systems and uncover sequence rules for transcription factor binding, chromatin accessibility and enhancer activation that we can validate with experiments. 

Event Category
QCB Seminar Series