The activity of cis-regulatory elements (CREs), key drivers of gene expression, is governed by complex interactions between DNA sequence and regulatory proteins. We address the challenge of modeling this complexity by developing deep learning approaches trained with transcriptomic and DNA-protein interaction (OMICS) data. These models learn intricate sequence-function relationships, allowing for accurate prediction of CRE activity, identification of critical regulatory features, and ultimately, a better understanding of how CRE variation influences gene expression.
1st July Düsseldorf: Bio Data Science Evening – let’s meet!
Register | on-site: https://forms.gle/yvEvB3HfFLDxKiYP9
Speaker?
Omics Data Research Group, Institute of Bio- and Geosciences, IBG-4: Bioinformatik, Forschungszentrum Jülich
What is the topic?
Decoding plant gene regulation with deep learning from omics data
Use the chance to meet Simon and other sequencing & bioinformatics experts on-site. Build valuable connections.
Organized by the West German Genome Center. Supported by the Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen