In the past decades, theoretical advances in the area of information processing and storage have lead to outstanding developments in the field of modern communication technology. The vast accumulated knowledge in mathematics and computer science pertaining to this subject matter is expected to play a major role in the future progress of other diverse scientific and engineering branches, including molecular biology and biomedical engineering. Biological systems are the most perfect known information processing and storage devices, but very little is known about the mathematical principles of their functions and operations. Without a deeper understanding of these characteristics, many emerging technologies aimed at replicating nature's communication pathways will not achieve their full potential. This issue is of special importance for DNA and RNA-based computers, proposed for applications involving solvers of computationally hard problems and for use in "smart drug" systems, capable of regulating and normalizing gene expressions levels in cancerous cells.
The investigators address various aspects of error-control and constrained coding for DNA based computers and DNA storage devices, which can aid in improving the performance and reliability of the systems under consideration. The research involves analyzing mathematical properties of RNA and single-stranded DNA folding and hybridization patterns from the perspective of information theory and statistical physics, and developing novel error-correction methods for constructing DNA tile sets used in algorithmic DNA self-assembly. The study is based on classical and some novel ideas from algebraic channel coding, combinatorial optimization and design theory. Furthermore, the investigators study the problem of modeling gene regulatory networks in terms of graphical structures closely related to coding-theoretic iterative systems.
