Development of scalable molecular neural networks

Molecular neural networks are a promising technology with an immense potential for transformative applications in science and medicine. The current implementations of molecular neural networks use different system architectures and designs tailored toward specific objectives. This lack of standardisation and inherent complexity of these systems are the main challenges in their construction and implementation, further hindered by the lack of software tools to facilitate their realization.

In this talk, I will introduce the concept of molecular neural networks and discuss their potential. I will describe the essential computation-enabling components and propose a pathway towards implementing these networks experimentally using DNA. Finally, I will discuss the need for a standardized tools for the creation and implementation of molecular neural networks from abstract specification.