Christoph S Börlin

The paper screens peptides to optimise alginate hydrogels for cultivated meat, identifying RGD-containing peptides as most effective for cell attachment and myogenic fusion.

This paper introduces ExpressionGAN, a deep learning model that generates functional regulatory DNA with specified expression levels, outperforming random mutagenesis approaches.

The paper uses deep learning to show that gene expression levels are encoded in both coding and non-coding regions of the gene regulatory structure across multiple organisms.

The paper shows that the transcription start site landscape in Saccharomyces cerevisiae remains stable across different environmental conditions and identifies a negative correlation between TSS shape index and expression levels.