Below is a set of selected preprints and publications. Please see my Google Scholar page for a full list.
* denotes co-first authorship, and underlines denote corresponding authors.
Addressable and adaptable intercellular communication via DNA messaging
Marken JP, Murray RM. Nature Communications, 2023 Apr 24.
By encoding messages into mobile DNA elements, one can massively scale up the bandwidth of intercellular communication channels in engineered bacterial populations. Ortiz and Endy first implemented this insight in 2012, but in the proceeding ten years there was little adoption of DNA-based communication by the field. Here I developed a modular and scalable framework for DNA-based communication that leverages its unique property of dynamic message mutability to enable messages to be programmatically addressed to specific recipients in a population, and for those messages to be editable in situ by the cells themselves. [Link] [pdf]
A geometric and structural approach to the analysis and design of biological circuit dynamics: a theory tailored for synthetic biology
Marken JP * , Xiao F * , Murray RM. bioRxiv Preprint, 2020 Feb 19.
When we design and analyze genetic circuits, the mathematical tools and conceptual frameworks that we use typically come from other disciplines, like engineering and computer science. But what would it look like to have a mathematical theory that was specifically developed for biomolecular systems? Jointly with Fang Xiao, we propose just such a framework, focusing on the ubiquitous presence of saturation in biomolecular reactions. Our central insight is that a genetic circuit can be approximated by a set of simpler circuits depending on the system's saturation state, and by analyzing these simpler circuits, we find that dynamic properties like bistability and oscillations can actually be encoded at a more fundamental, structural level than could be seen with conventional analysis approaches. [Link] [pdf]
A Markovian entropy measure for the analysis of calcium activity time series
Marken JP * , Halleran AD * , Rahman A, Odorizzi L, LeFew MC, Golino CA, Kemper P, Saha MS. PLoS One, 2016 Dec 15.
Unlike mature neurons, Xenopus laevis neural progenitors do not display stereotyped spiking behavior in their calcium dynamics, precluding the use of conventional spike-counting algorithms to analyze time-series datasets. Jointly with Andy Halleran, I developed an algorithm that represents the calcium dynamics as a Markov process and calculates the entropy associated with the corresponding transition matrix. Our method was able to separate the calcium activity datasets from developmentally-distinct stages of progenitor cells more strongly than existing methods. [Link] [pdf]