A molecular assessment of the practical potential of DNA-based computation - Polak, Rachel E; Keung, Albert J (Current opinion in biotechnology, 2023)
The immense information density of DNA and its potential for massively parallelized computations, paired with rapidly expanding data production and storage needs, have fueled a renewed interest in DNA-based computation. Since the construction of the first DNA computing systems in the 1990s, the field has grown to encompass a diverse array of configurations. Simple enzymatic and hybridization reactions to solve small combinatorial problems transitioned to synthetic circuits mimicking gene regulatory networks and DNA-only logic circuits based on strand displacement cascades. These have formed the foundations of neural networks and diagnostic tools that aim to bring molecular computation to practical scales and applications. Considering these great leaps in system complexity as well as in the tools and technologies enabling them, a reassessment of the potential of such DNA computing systems is warranted. •DNA holds potential for highly dense and extreme-scale parallelized computation.•Molecular components of DNA computers may not limit achieving functional net speeds.•Barriers to DNA computation are primarily macroscale and subject to system design.•Neural network configurations make promising steps toward computation at scale.