Jonathan Leo Schmid-Burgk

This paper combines evolutionary algorithms with AI to design potent Nectin-4-specific cancer biologics, achieving high-affinity minibinders and functional reagents.

This paper introduces Transposon-Display, a method to identify and optimize AI-designed protein binders for intracellular use, enabling controlled protein manipulation in human cells.

This paper develops AI-designed protein binders for cancer cell surface proteins, showing their effectiveness in detection and targeting through experimental validation and benchmarking of structure prediction models.

This paper introduces CRISPR-READ, a live cell RNA sensor that detects endogenous transcripts and identifies Type-I interferon signaling through RNA-seq of sorted cells.

The paper introduces NIS-Seq, a method for genome-scale optical perturbation screening in any nucleus-containing cell type, and demonstrates its application in identifying inflammation-related pathway components.

LAMP-Seq combines three-step isothermal RT-LAMP amplification with combinatorial barcoding to pool and sequence SARS-CoV-2 clinical samples en masse for scalable diagnostics.

The paper shows that genetic antigen loss in melanoma cells is selected for under T-cell therapy due to subclone fitness differences and stochastic events.

The paper introduces an optical method to link genetic perturbations with phenotypic outcomes in a pooled setting, identifying novel regulators of immune responses.