Introduction and motivation. Life is full of amazingly sophisticated programs encoded in genomes, orchestrating molecules to sense, to compute, to respond, and to grow. Towards rationally designing and synthesizing molecular systems with programmable behaviors as sophisticated as life itself, this project will take an approach that is biologically inspired and computer science centered. On one hand, nature has been very successful in evolving and selecting the most efficient and powerful biological programs made of simple individual molecules. In order to use the full potential of molecules to create complex and programmable systems, one needs to borrow the information processing principles in biology. On the other hand, computer science has been very successful in mastering complexity, and devices with billions of electronic components have been manufactured. In order to build ever-more-complex molecular devices, one needs to borrow the concepts that enabled the success of computer engineering.
Intellectual merit. If successful, this project will transform the frontiers of understanding about what possible behaviors a network of interacting molecules can exhibit and how one can rationally design such behaviors. In particular, the project will seek answers for the following questions: (1) How can spatial organization improve the performance of molecular circuitry and machinery? Inspired by spatial organization in biology such as neural wiring and scaffold proteins, the project will develop molecular systems that are spatially organized on the surface of DNA nanostructures, to build faster and more reliable biochemical circuits, efficient molecular Turing machines, and DNA cellular automata with complex spatial and temporal behaviors. (2) How can the brain-like principle of learning from examples be embedded within a network of interacting molecules? Inspired by the learning and memory-forming rules in the brain, the project will explore simple and efficient learning algorithms to create synthetic DNA neural networks that learn from their biochemical environment and recall patterns of biochemical signals. (3) How can sophisticated collective behaviors arise from simple individual behaviors of molecular motors? Inspired by collective behaviors in animals, such as ant foraging and termite clustering, the project will build molecular robots that have simple functions as individuals but as groups perform complex tasks such as cargo sorting and maze solving.
Broader impact. This project will bring computer science into areas of molecular sciences in a way that is fundamentally different from the existing approaches in computational biology and bioinformatics: it is not just about using computer algorithms and programs to aid the design and analysis of molecular systems, but it is more about adapting the principles of computer science to create biochemical systems that can carry out instructions to perform tasks at the molecular level. If successful, this project will help extend computer science from the traditional electronic substrates to new molecular substrates that can execute new biologically-inspired algorithms, and create new frontiers in chemistry and biomedical sciences with potential solutions to smart autonomous chemical synthesis and complex disease diagnostics and therapeutics. The project will contribute to education and educator development by designing innovative courses, providing students and postdocs with teaching and mentoring experiences, supporting undergraduate research and student competitions, creating a highly interdisciplinary research environment, and involving more women in science. This project will also increase public engagement with science and technology by developing open-source software tools, producing research videos on YouTube, giving open lectures, and interviewing for science TV series.
