Heinz Koeppl

This study demonstrates that osmotic stress from internal gene expression can promote macromolecular release from synthetic cells without requiring membrane pores.

The paper introduces the Yeast Logic Toolkit (YLT), which provides pre-assembled backbones and parts for constructing genetic circuits in yeast with reduced context-dependent effects.

The paper introduces iFLinkC-EZ, a method for assembling complex DNA constructs using genetic purification, demonstrating its use in creating fusion proteins and multi-gene constructs.

The paper introduces the Coli Toolkit (CTK), a modular cloning system for E. coli, expanding on the Yeast Toolkit to enable efficient genetic circuit assembly.

This study investigates how different DNA damage stimuli regulate p53 target gene promoter activity through stochastic gene expression, revealing stimulus-specific activation and deactivation rates.

The paper introduces DLRN, a deep learning framework that models time-resolved data to extract kinetic reaction networks, time constants, and amplitudes with performance comparable to or better than classical methods.

This paper improves inverting genetic logic gates by introducing antisense RNA feedback, enhancing their steepness, reducing leakage, and enabling tunable dose-response curves.

This study designs hybrid riboswitches in yeast to emulate Boolean NAND logic using machine learning-based Bayesian optimization.

This paper introduces Energy Aware Technology Mapping to design genetic logic circuits with energy efficiency and functionality, showing energy efficiency improves by 37.2% over functionally optimized variants.

The paper models chemical reaction networks in a random environment using Hawkes processes to approximate marginal descriptions of the system.

This paper develops a framework for analyzing information transmission in biochemical reaction networks under energy constraints and derives bounds for reliable communication.

The paper uses Bayesian methods to analyze kinetic transcription parameters in yeast under stress, revealing fast bursting dynamics within slower cycles.

This work improves genetic design automation by incorporating context effects through thermodynamic models and branch-and-bound techniques, enhancing circuit prediction accuracy.

The paper quantifies the mean expression levels in linear CRNs under a random environment, showing how heterogeneity affects the stationary mean.

The paper introduces a high-throughput assay called the Functional Nanopore screen to study and engineer protein nanopores in E. coli by measuring Ca2+ influx.

The paper introduces a method to design robust genetic circuits by adapting electronic design automation techniques to account for structural variants and parameter uncertainty in biological systems.

This paper demonstrates the integration of CRISPR-associated proteins into cell-free systems to enhance RNA-based circuit prototyping, showing improved dynamic range and reduced leakage in logic gates.

This study designs AND-logic gates using RNA components and tests them in vitro and in vivo, showing comparable performance to protein circuits.