Titus H. Klinge

Requirements analysis for a product family of DNA nanodevices

DNA nanotechnology uses the information processing capabilities of nucleic acids to design self-assembling, programmable structures and devices at the nanoscale. Devices developed to date have been programmed to implement logic circuits and neural networks, capture or release specific molecules, and traverse molecular tracks and mazes. Here we investigate the use of requirements engineering methods to make DNA nanotechnology more productive, predictable, and safe. We use goal-oriented requirements modeling to identify, specify, and analyze a product family of DNA nanodevices, and we use PRISM model checking to verify both common properties across the family and properties that are specific to individual products. Challenges to doing requirements engineering in this domain include the error-prone nature of nanodevices carrying out their tasks in the probabilistic world of chemical kinetics, the fact that roughly a nanomole (a 1 followed by 14 0s) of devices are typically deployed at once, and the difficulty of specifying and achieving modularity in a realm where devices have many opportunities to interfere with each other. Nevertheless, our results show that requirements engineering is useful in DNA nanotechnology and that leveraging the similarities among nanodevices in the product family improves the modeling and analysis by supporting reuse.

Automated requirements analysis for a molecular watchdog timer

Dynamic systems in DNA nanotechnology are often programmed using a chemical reaction network (CRN) model as an intermediate level of abstraction. In this paper, we design and analyze a CRN model of a watchdog timer, a device commonly used to monitor the health of a safety critical system. Our process uses incremental design practices with goal-oriented requirements engineering, software verification tools, and custom software to help automate the software engineering process. The watchdog timer is comprised of three components: an absence detector, a threshold filter, and a signal amplifier. These components are separately designed and verified, and only then composed to create the molecular watchdog timer. During the requirements-design iterations, simulation, model checking, and analysis are used to verify the system. Using this methodology several incomplete requirements and design flaws were found, and the final verified model helped determine specific parameters for biological experiments.

Engineering and verifying requirements for programmable self-assembling nanomachines

We propose an extension of van Lamsweerdes goal-oriented requirements engineering to the domain of programmable DNA nanotechnology. This is a domain in which individual devices (agents) are at most a few dozen nanometers in diameter. These devices are programmed to assemble themselves from molecular components and perform their assigned tasks. The devices carry out their tasks in the probabilistic world of chemical kinetics, so they are individually error-prone. However, the number of devices deployed is roughly on the order of a nanomole (a 6 followed by fourteen 0s), and some goals are achieved when enough of these agents achieve their assigned subgoals. We show that it is useful in this setting to augment the AND/OR goal diagrams to allow goal refinements that are mediated by threshold functions, rather than ANDs or ORs. We illustrate this method by engineering requirements for a system of molecular detectors (DNA origami “pliers” that capture target molecules) invented by Kuzuya, Sakai, Yamazaki, Xu, and Komiyama (2011). We model this system in the Prism probabilistic symbolic model checker, and we use Prism to verify that requirements are satisfied, provided that the ratio of target molecules to detectors is neither too high nor too low. This gives prima facie evidence that software engineering methods can be used to make DNA nanotechnology more productive, predictable and safe.

Robust Signal Restoration in Chemical Reaction Networks

Molecular computing systems that are contained in well-mixed volumes are often modeled using chemical reaction networks. In these systems, concentrations of molecules are treated as signals and used for both communication and memory storage. A common design challenge for such a system is to avoid memory corruption caused by noise in the input signals. In this paper, we analyze two signal restoration algorithms for molecular systems modeled with chemical reaction networks. These algorithms are designed to prevent a memory signal from degrading over time, and we show that under modest conditions these algorithms will maintain the memory indefinitely. We also present an exact solution of the running time of the first algorithm which demonstrates that it converges in logarithmic time.

Real-time computability of real numbers by chemical reaction networks

We explore the class of real numbers that are computed in real time by deterministic chemical reaction networks that are integral in the sense that all their reaction rate constants are positive integers. We say that such a reaction network computes a real number

Robust Combinatorial Circuits in Chemical Reaction Networks

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A Functional Approach to Data Science in CS1

α in real time if it has a designated species X such that, when all species concentrations are set to zero at time