Elisa Franco

This paper demonstrates the co-assembly of DNA nanotubes and condensates in synthetic compartments, enabling programmable structures that mimic cellular organization.

This paper introduces programmable artificial RNA condensates in mammalian cells that can be controlled for subcellular localization and molecular recruitment.

The paper demonstrates temporal dose inversion in adaptive biomolecular circuits using synthetic gene circuits and identifies key parameters for this behavior.

This study analyzes sequestration-based networks to understand and control pulse dynamics through kinetic rates and feedback mechanisms.

The paper demonstrates enzymatic networks can function as molecular perceptrons for linear classification and multi-layer networks for nonlinear classification.

The paper designs and characterizes artificial nucleic acid condensates that recruit and concentrate proteins in vitro, demonstrating control over condensation and protein recruitment through UV irradiation and RNA transcription.

The paper designs an intracellular aptamer-based biosensor to monitor burden in E. coli by evaluating aptamer performance across promoters and strains.

This paper introduces a platform for engineering synthetic RNA condensates that can form programmable organelles with controlled properties.

This paper designs orthogonal RNA condensates using modular RNA motifs and demonstrates their ability to recruit proteins and form in living cells.

This paper demonstrates a method to control the self-assembly of DNA-based polymers using synthetic gene networks, achieving spatial and temporal control over polymer formation and dissolution.

This paper designs a portable regulatory RNA array for tunable gene regulation across diverse bacteria, enabling complex circuitry without requiring large regulatory libraries.

The paper demonstrates how subtraction can be achieved through molecular sequestration in a chemical reaction network and presents two feedback control architectures based on this principle.

The paper designs synthetic gene circuits that function as band-pass filters using molecular sequestration, showing improved performance with combined Incoherent Feed-Forward Loop and Negative Feedback motifs.

This study designs and models six recombinase-based oscillator circuits, showing they can produce periodic behavior under stochastic conditions using a Gillespie algorithm.

This paper introduces RNA compensation, a positive feedback strategy to mitigate RNA signal consumption in RNA-based circuits, improving composability and modularity.

The paper models phosphorylation/dephosphorylation cycles as molecular neurons and shows they can function as biomolecular neural networks capable of performing classification tasks.

The paper demonstrates how bistable switches and quorum sensing can enable ultrasensitive feedback control in microbial populations while avoiding cellular burden.

This paper designs molecular quasi-integral controllers using a reaction network called Brink motif to achieve robust homeostasis in biological systems.

The paper characterizes two RNA regulators with distinct timescales and demonstrates their use in creating a genetic pulse generator through computational modeling and experimental validation.

This paper uses real algebraic geometry to analyze bistable biological circuits, showing how topological properties affect parameter space and demonstrating the utility of Sturms theorem over traditional methods.

The paper classifies biological networks into candidate oscillators and multistationary systems based on feedback loop analysis without parameter knowledge.

This paper introduces a negative autoregulation system for synthetic genelets that matches production and demand, showing improved robustness and scalability compared to cross-activation.