Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method and, as such, does not require feedback, making it suitable in contexts …
Targeted high-throughput DNA sequencing is a primary approach for genomics and molecular diagnostics, and more recently as a readout for DNA information storage. Oligonucleotide probes used to enrich gene loci of interest have different hybridization …
Developing molecular communication platforms based on orthogonal communication channels is a crucial step towards engineering artificial multicellular systems. Here, we present a general and scalable platform entitled 'biomolecular …
Methods from stochastic dynamical systems theory have been instrumental in understanding the behaviours of chemical reaction networks (CRNs) arising in natural systems. However, considerably less attention has been given to the inverse problem of …
The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and …
Hybridization is a key molecular process in biology and biotechnology, but so far there is no predictive model for accurately determining hybridization rate constants based on sequence information. Here, we report a weighted neighbour voting (WNV) …
Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signalling networks. Synthetic silicon-based circuitry similarly relies on spatial constraints to process information. Here, we show that spatial …
We consider how to generate chemical reaction networks (CRNs) from functional specifications. We propose a two-stage approach that combines synthesis by satisfiability modulo theories and Markov chain Monte Carlo based optimisation. First, we …
Molecular devices made of nucleic acids can perform complex information processing tasks at the nanoscale, with potential applications in biofabrication and smart therapeutics. However, limitations in the speed and scalability of such devices in a …
DNA self-assembly is a powerful technology for controlling matter at the nanometre to micron scale, with potential applications in high-precision organisation and positioning of molecular components. However, the ability to program DNA-only …