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The molpigs Podcast

Science Podcasts

Welcome to molpigs, the Molecular Programming Interest Group! molpigs is a group aimed at PhD students and early career researchers within the fields of Molecular Programming, DNA Computing, and other related specialties. We run most of our events in the form of podcasts, which you can find right here!


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Welcome to molpigs, the Molecular Programming Interest Group! molpigs is a group aimed at PhD students and early career researchers within the fields of Molecular Programming, DNA Computing, and other related specialties. We run most of our events in the form of podcasts, which you can find right here!




Zibo Chen: What's really cool is when it's functional and predictable

In this episode of the molpigs podcast, Hannah, Boya and Erik talk with Zibo Chen, a new professor at Westlake University about his scientific journey through the world of biological information system design. We discuss how he went from designing DNA, to proteins, to entire cellular systems. Designing with different materials requires different design and modeling methods. We also take a look to the future and how he plans to take protein-based neural networks from living cells to synthetic cells. Further Reading: "A cargo sorting DNA robot" - "Programmable design of orthogonal protein heterodimers" - "Confirmation of intersubunit connectivity and topology of designed protein complexes by native MS" - "A synthetic protein-level neural network in mammalian cells" - "De novo design of modular and tunable protein biosensors" - --- Zibo Chen is an assistant professor in the School of Life Sciences at Westlake University. He received his Ph.D. degree in biochemistry in the labs of David Baker and Frank DiMaio at the University of Washington and worked on mammalian synthetic biology with Michael Elowitz at Caltech as a Damon Runyon Fellow. His work focuses on programming biology using proteins as the coding language. He has received a number of awards, including the Robert Dirks Molecular Programming Prize, and was included in Forbes 30 Under 30. Outside of the lab, Zibo is an instrument rated pilot and enjoys flying around in a small Cessna. --- Find more information at the episode page here:


Ashwin Gopinath: Merging top-down and bottom-up synthesis

On this episode, the molpigs team talks with Ashwin Gopinath about bridging size scales in nanomaterial size scales. We explore his journey from optical physics to learning DNA nanotechnology in the Rothemund lab and his current projects and vision for highly multiplexed molecular measurements. Ashwin's career path has been quite the adventure, starting in academia, working for Google and then starting and later selling his own company. Finally, we turn to ways that AI is going to change research and the impending death of the current grant-funding structure. His excitement for scientific progress, perspective on different work environments and creativity in research is always inspiring for scientists young and old. The paper Ashwin mentions on developing new AI capabilities can be found here: --- Ashwin received his PhD in Electrical Engineering from Boston University, working on devices for detecting and characterizing single biomolecules. Challenges he encountered during this motivated him to switch focus from optical physics to DNA nanotechnology, leading to a postdoc under Paul Rothemund at Caltech. After working briefly for Google X, he is now an Assistant Professor at MIT. He has received the Robert Dirks Molecular Programming Prize for his work combining DNA nanotechnology with conventional micro-fabrication. --- Find more information at the episode page here:


Katherine Dunn

Join the molpigs team for a discussion with Prof. Katherine Dunn from the University of Edinburgh about her work on using DNA nanotechnology for medical applications and her exciting new ideas regarding "electrosynbionics," using biological engineering to tackle hard problems in energy production and storage. She also discusses her experiences transitioning from terahertz spectroscopy to biophysics and the challenges in teaching and mentoring students to prepare them for a variety of career paths in today's interdisciplinary world. Katherine completed her undergraduate degree in physics at the University of Oxford. She started a PhD there in Terahertz Spectroscopy before seeing the light and changing to DNA Origami. She has continued to study molecular programming within an engineering context, working on DNA nanomachines for bioelectronic computing at the University of York. She is now a Senior Lecturer at the University of Edinburgh, and has been named as one of the Top 50 Women in Engineering 2021 by the Women’s Engineering Society. --- Find more information at the episode page here:


Erika DeBenedictis

This week’s podcast is with Erika DeBenedictis, a new principal investigator who is founding her lab at the Crick Institute in London. Her lab will focus around the broad field of bioautomation, but before talking about any of that, we delve into her past. Erika is just another one in a long string of podcast guests who has had an unconventional entry into the field of molecular programming! She started her scientific career interested in space science, telling us that her interest was kindled as a child because of the accessibility of this field to anyone. This led her to work at NASA’s Jet Propulsion Laboratory. Afterwards she talks about her time as a PhD student in Kevin Esvelt’s lab working on massively parallelised directed evolution, harnessing the power of robotics in order to develop her technique known as PRANCE. She talks about the use of these techniques in expanding the genetic code, and the main hurdles in doing so. We then move on to her post-doc at David Baker’s lab in Washington, where she worked on using machine learning for de novo protein engineering. At the same time we talk about the place of robots in modern laboratories, whether they will replace all hand pipettes (and wet lab scientists!), and the feasibility of cloud laboratories in making science more accessible. Finally we move on to the start of Erika’s new lab at the Crick Institute, her vision for what she wants to do, and ultimately the bioautomation challenge, which is a programme spearheaded by her to get bioautomation equipment into more laboratories to accelerate research. --- Erika began her science career as a computational physicist and astronomer and worked on space mission design at NASA’s Jet Propulsion Laboratory. She received a BS in Computer science from Caltech in 2014. She then worked at Dropbox as a software engineer and at D. E. Shaw Research on computational biophysics. She received a PhD in Biological Engineering from MIT in 2020, working with Kevin Esvelt. Erika’s research focused on developing techniques for robotics-accelerated evolution (PRANCE) and applying these techniques to quadruplet codon genetic code expansion and origin of life research in E. coli. Her postdoc in David Baker’s lab at the Institute for Protein Design at the University of Washington focused on using machine learning techniques to systematically engineer de novo proteins. In 2022, she launched the Bioautomation Challenge, a program designed to make experimental life science more reproducible, scalable and sharable by giving researchers access to programmable experiments. She now leads the Biodesign Laboratory at the Francis Crick Institute in London, UK. --- Find more information at the episode page here:


Grigory Tikhomirov

In this episode the molpigs team talks with Greg Tikhomirov about his experience starting a new molecular programming lab and his visions for “a new nanotechnology”. We learn about his journey from wanting to build large, beautiful molecules to his work at the interface between molecular design and material science. Greg Tikhomirov is an assistant professor in Electrical Engineering and Computer Sciences, with a background in chemistry, bioengineering, medicine, and nanotechnology. He has a longstanding dream to engineer life-like artificial systems, motivated by the realization that incomprehensible natural complexity arises from comprehensible fundamental laws. Ti Lab at Berkeley is pursuing the design and fabrication of devices with atomic precision by combining the strengths of rational top-down engineering and bottom-up biomolecular assembly. A key goal is to adopt the powerful but still proof-of-concept self-assembly approaches of DNA nanotechnology to engineer new, useful devices. --- Find more information at the episode page here:


Eva Bertosin: A DNA rotary mechanism with coordinated mobility control

Join the molpigs team for a conversation with Eva Bertosin about her work on building nanoscale rotors during her PhD with Hendrik Dietz. This is a "poster podcast," so we will occasionally be referencing figures in the associated poster which can be found at the link below. The DNA origami rotor was inspired by the rotational mechanism of ATP synthase, which Eva and her colleagues had to simplify and abstract to create a functional DNA structure which could demonstrate rotational diffusion. She explains how they used cryoEM to optimize design, and how new tools for analyzing cryo data made the ambitious data analysis involved in this process possible. And the promises of using molecular simulation to help inform design. We round out the conversation with discussion of how she got into DNA design, visions for the future, and advice to future students about tackling huge projects. Eva is a postdoc in the Cees Dekker's research group at the Technical University of Delft. Her work is focussed on building artificial systems that are inspired by natural components of the cell. In particular, she is working on biomimetic systems to study transport of molecules through the nuclear pore complex. She obtained her PhD in 2021 working in Hendrik Dietz' group at the Technical University of Munich. During this time, she built a novel rotating nanostructure made of DNA origami components with interlocked and coupled motion. This work was chosen as one of the finalists of the CeNS Nano Innovation Award 2021. She got her MSc degree at the Technical University of Munich and her BSc in physics studying at Padua University and at the Georg-August-University Göttingen. Poster: Video: --- Find more information at the episode page here:


Anne Condon

Join the molpigs team as they have a discussion with one of the theoretical giants of molecular programming: Anne Condon. Over the wide-ranging conversation, she shares her insights on NP-complete problems, solving RNA folding with good data, and how best to teach and mentor students in a manner that creates great researchers and facilitates diversity in the field. Anne Condon is a professor of Computer Science at the University of British Columbia, of which she was formerly head of department, and also a fellow of the Royal Society of Canada. She is known for her extensive work in computational complexity theory and design of algorithms, in the context of bioinformatics, hardware verification, combinatorial auctions, and of course, DNA computing. As well as numerous awards for her work in Computer Science from bodies including the ACM, she has also received many awards for her leadership in advancing women in computing, and has previously held the NSERC/General Motors Canada Chair for Women in Science. She completed her bachelor’s degree at University College Cork, and her doctorate at the University of Washington. For listeners who would like to skip to the less technical parts of the interview, and hear Anne’s insights on diversity, mentorship and creating a positive experience for students, that section begins 28:33 into the episode. --- Find more information at the episode page here:


Jurek Kozyra

On this episode Hannah, Boya, Erik and new co-host Dhaval sit down with Jurek Kozyra, founder of the molecular programming startup, Nanovery. Over the course of this wide-ranging interview, he tells us about how learning biology can help your dating life, his PhD work at the intersection of biotech and computer science and his early ventures in cherry picking and private investigation before diving into his story of building a successful startup with funders, employees, and lab space. Jurek Kozyra is the founder and CEO of Nanovery. He obtained his BSc in Computer Science with Artificial Intelligence from the University of Nottingham, where he studied bio-inspired and unconventional computing. Afterwards, Jurek earned his PhD in DNA nanotechnology and DNA computing from Newcastle University working at ICOS (one of the leading computational synthetic biology research groups in the UK). He was also an entrepreneurial lead for a university biotech spin-out based on the DNA barcoding technology he developed. In 2018 Jurek started Nanovery—a molecular diagnostic company developing DNA nanorobots for early detection of diseases from blood samples. The mission of the company is to enable accurate and simple testing closer to the patient bedside. Nanovery: --- Find more information at the episode page here:


Sam Schaffter

Join us for a chat with Sam Schaffter, a postdoc at NIST working on realizing complex transcription-based strand displacement in living systems. We start the conversation with the story of how he made the transition from the molecular biology of food to molecular programming. We then move on to the details of his research on transcriptional circuits including where the idea came from and the trials of taking molecular computing from the test tube to cell systems. He tells us about the differences and similarities between academic and government research and how everything is a “measurement” when you work for NIST. We round out the conversation with Sam’s dreams of the future of nucleic acid-based sensors for diagnostic and control purposes and the research he would like to see in the next 5, 10, 25 and 50 years to advance the field toward application. Sam conducted his PhD research in the field of DNA nanotechnology and DNA computing, working in Rebecca Schulman’s group at Johns Hopkins. He developed synthetic transcription-based networks with dynamics programmed via Franklin-Watson-Crick base pairing rules. These in vitro networks emulated key functionalities of cellular genetic regulatory networks and thus could serve as a programmable “synthetic genome” for controlling nucleic acid materials and devices, such as DNA nanostructures and DNA-responsive hydrogels. The goal of his research was to engineer synthetic materials capable of sophisticated behaviors seen in biology including hierarchical differentiation or self-healing. For this work, he won the 2021 Robert Dirks prize for molecular programming As a National Research Council (NRC) postdoctoral fellow at NIST, Sam is interested in moving DNA computing circuits from the test tube to living cells. Current DNA-based circuits are only single use and suffer from degradation in vivo, limiting their practical applications. To overcome these limitations, Sam’s current research focuses on transcriptionally encoding RNA-based circuits, equivalent to those developed in DNA computing, that can operate continuously inside living cells. These circuits could be programmed to recognize complex differential gene expression patterns in real-time in vivo, potentially enabling a new class of living measurement systems. Sam’s project at NIST: Co-transcriptional RNA strand displacement circuits: Call for applications to the NIST Cellular Engineering Group: For non-US citizens, the process for applying is essentially to contact someone at NIST you want to work with and to discuss potential projects. If NIST has available funding to hire students for a specific project, then the student can be hired through an external university. This process is actually done for both US an non-US citizens depending on need / the situation. There isn’t a funding mechanism like the NRC fellowship for non-US citizens so it depends more heavily on existing funding. But nonetheless, any interested international students are encouraged to reach out about available opportunities. --- Find more information at the episode page here:


Sifang Chen

Join us for a relaxed chat with Sifang Chen, a science policy post-doc, for a slightly different discussion. We speak about Sifang’s past, how she got into DNA nanotech and molecular programming, her research on biosensors and DNA programmable materials, and how she switched to this field from quantum and graphene based devices. We then moved on to talking about science in a broader scope, starting off with the big question of how Synthetic Biology and related fields will help in the fight against climate change, and the problems we face, both from a policy and science perspective. Moving into policy is certainly unconventional, and Sifang explains the transition, and the skills required to do so, before diving into the specifics of what her job entails, how she communicates with lawmakers, and the difficulties she faces in this line of work. --- Find more information at the episode page here:


Damien Woods

Today we’re talking with Damien Woods, a professor and molecular programmer at the Hamilton Institute, Maynooth University, Ireland. We first began by talking about how his early interests in dynamics and optical computers (the subject of his PhD thesis) led him to the field of molecular programming. We then move on to talking about one of Damien’s well known papers, Diverse and robust molecular algorithms using reprogrammable DNA self-assembly. In this paper, Damien describes the implementation of 21 algorithms using a 6-bit boolean circuit built out of a DNA tile-set. Damien and his team built a set of DNA tiles which could implement any algorithm allowable by that 6-bit computer (the tiles are 6-bit universal). Damien describes how this allows anyone to wake up in the morning, design an algorithm, retrieve the appropriate tiles from the fridge, mix them and begin running the algorithm in a test tube on the very same day. This clearly has its advantages over other systems, which may require someone to wait for the DNA synthesis of their system before an implementation can be made. The readout of these circuits is by AFM to see a tape-recording of the computation, and so this paper generated a lot of pretty pictures! We then moved on to talk about potential implementations of more complex computers, how Damien et al.’s 6-bit boolean circuit might be scaled up, and how the number of required tiles scales with the computational complexity (it’s linear!). This led us on to an extended discussion about universal tile-sets, their existence, and their ability to be implemented in DNA. Finally we moved on to Damien’s experience in academia. He’s been to quite a few places, and has worked on many different things. He explains how his experience running a lab in two different countries differed, and how this shaped the way he runs his research group. Diverse and robust molecular algorithms using reprogrammable DNA self-assembly paper: --- Find more information at the episode page here:


Dave Doty

In our latest Meet The Molecular Programmer, our guest was David Doty. We dove right in to the way he splits his research time, which has been between software development, theory, and sometimes experiments! He talks about how his experience doing his first experiment made him realise the need for good software, as good software enables good experiments. We then moved on to discussing what “nice” theory is. Doty explains how typically people seek to publish the most elegant, and often complicated theory in conferences and journals, but that this rarely translates to experimentation which can be done in the lab. When asked for an example of a time that he saw elegant theory married to beautiful experiment, he gave our own host’s (Anastasia) most recent paper on crisscross assembly! Finally we moved on to more personal aspects of Doty’s academic life, talking about how he moved into the field, his experience switching topics twice during his PhD, and his rather unique marriage proposal! You’ll have to give the podcast a listen to find out how exactly he did it... Crisscross paper: Dave's wedding slides: --- Find more information at the episode page here:


William Poole

This week we spoke with William Poole, a graduate student at Caltech working on quite a few topics! His research spans synthetic/systems biology to molecular programming, software development to chemical reaction network (CRN) theory, machine learning to cell free systems. We certainly had a lot to talk about! We started off by discussing BioCRNPyler, a library which Will has been working on that allows for the rapid development and compilation of complex CRNs. He describes how BioCRNPyler can help you rapidly design CRNs in a variety of cellular contexts. The CRNs can then be simulated using any simulator/solver. We also discuss other software projects he is involved with such as Bioscrape and Vivarium. Next we move onto William’s research into chemical Boltzmann machines, what they are and how they are related to machine learning, while talking about how low molecular copy number systems might be able to perform more complex computation than high copy number systems. We also talk about how William got into molecular programming from his undergraduate degree, which focussed on physics and biology. He describes how his undergraduate research led him in various directions, and even into working in bioinformatics at the Institute of Systems Biology for a few years before pursuing graduate school. This ultimately spurred on a somewhat grand discussion on William’s “dream” for molecular programming. He is very concerned about climate change, and talks at length about how in the long term we might be able to program many of the materials around us to sequester carbon, and eventually “re-terraform” the earth. Finally, we asked why physicists and engineers are able to come together to build large scale projects such as the LHC and ISS, while no such projects exist for the biological sciences, and we speculate on what such a project could look like for our field... BioCRNPyler: Bioscrape: Vivarium: --- Find more information at the episode page here:


Anastasia, Boya, Georgeos, Hannah: Meet the Committee

Join us in this experimental episode as our conversation turns inwards! Instead of finding out about the life and interests of someone from the field, we share some of our own views and anecdotes. We discuss a little about who we are, graduate school, the definition of the field, and more. Hannah, the founder of molpigs, gives a bit of an insight into what the motivation for starting molpigs was and what they hope this project will achieve. Boya, our newsletter editor, explains how learning more about psychology is helping her to be a more effective researcher. Anastasia, who shares podcast editing duties with Hannah, gives some perspectives on how fundamental DNA is to the field of molecular programming. Georgeos, who manages our social media and money, tells us why he'd much rather be a scientist today than the 19th century. We also give an update on the status of our sister project, the Molecular Programming Society, which is currently writing the ‘Art of Molecular Programming’ textbook. The project is rapidly growing to include dozens and dozens of members of our field. If you want to keep up-to-date with their progress, follow them on Twitter @MolProgSoc and subscribe to their newsletter. Anastasia: Boya: Georgeos: Hannah: MPS Twitter: MPS Newsletter: --- Find more information at the episode page here:


Lee Organick

Today we are joined by Lee Organick, a PhD student in the Molecular Information Systems Lab (MISL) at the University of Washington. Lee is a biologist turned computer scientist and engineer, quite a unique transition! She explains how she was “forced” to take a computer science class in her undergrad, which opened up a completely new field of interests. After this, she started incorporating more programming into her research, and as such slowly moved into more computational fields. This is how she eventually found herself at MISL, and has been programming molecules ever since. She talks about how the transition from biology to computer science was a difficult one, and how she suspects that she invested more time than the average student moving in the opposite direction. We then move on to talk about her main research area, DNA storage. Because we focussed on the specifics of DNA storage in our previous episode with Yuan-Jyue Chen (another member of MISL), we spoke more about the future of DNA storage, specifically where it fits in to the current data storage ecosystem. Lee argues that DNA is currently best suited archival and long term data storage, with many advantages over the traditionally used tape. Lee also talks us through a new project she is working on which involves augmenting the previously discussed DNA based image similarity search with Cas9! Finally we move onto an extremely interesting topic; that of the security concerns surrounding DNA data storage. We learn about how current sequencing machines may be vulnerable to buffer overflow attacks through the submission of malicious sequences, how sequencing leak can result in a nefarious third party being able to “spy” on other people’s pooled sequences, and some of our committee members even suggest some new potential exploits! --- Find more information at the episode page here:


Kent Kemmish

Join us this week for an extremely interesting conversation with Kent Kemmish, the founder and chief exorcist (yes, exorcist) officer of Molecular Reality, and the creator of the new, and world’s first “molecular” games console, the demonpore 64. This is our first podcast with a member of the molecular programming community who works in industry, and in the startup sector. At its heart, Kent’s demonpore 64 is a device which utilises solid state nanopores in order to sense its environment at the molecular level. Kent and his team have reduced the cost to manufacture this traditionally lab based and expensive equipment by orders of magnitude. Kent’s hope is that by making this technology cheap, accessible and gamified, gamers can engage in science and data collection on behalf of scientists. This ought to enable scientists to perform very very large experiments, which would otherwise be impossible. We discuss what a molecular games console actually is, what sort of functionality the demonpore 64 has and how it can bring together academics, game developers, gamers, and citizen scientists in order to solve the world’s biggest challenges. Kent talks through future games which will be available for the demonpore 64, including Poop of the Gods, 2021: A SARS Odyssey, Genomic Ranger, and Molecules of Mars. These games allow people to explore the molecular mysteries of poop, viral detection, chromosome structure, and martian soil! We then move on to talk about Kent’s life, from student, to academic, to entrepreneur. Kent talks fondly of his early days working on Drosophila genetics, and later at Halcyon Molecular a startup which was focussed around sequencing DNA with electron microscopy. He talks about how these experiences shaped his worldview around having a much greater impact by working on and caring about scientific tools rather than the science itself, and bringing these tools to the scientists with research questions. To learn more about the demonpore 64, check out Kent’s WeFunder campaign, and also check out their website The nanopore cartridge shown at ~51:00 can be seen here: --- Find more information at the episode page here:


Namita Sarraf

What do ant colonies have to do with molecular programming? In this podcast, we spoke with Namita Sarraf, a graduate student at Caltech in Lulu Qian’s group. We discuss her research, which revolves around the production of multifunctional and modular DNA robots. Namita takes inspiration from ant colony dynamics to design robots, which alone may exhibit simple behaviour, but show emergent complexity when put together. By having these robots pattern the surface, ant pheromones can be emulated. One task which these “DNA ants” are being made to perform is maze-solving. Because traditional methods are not ideal for DNA robots, Namita is developing bespoke maze-solving algorithms. As she points out however, maze-solving by itself is not inherently useful, and for this reason these DNA robots are being built for modularity and composability. By combining maze-solving with cargo sorting Namita can generate more complex behaviours with real world applications. We then move on to talk about how Namita moved into molecular programming from her original field of tissue engineering. We discuss graduate student life, impostor syndrome, and the generation of negative results and their use in publishing. Namita is also one of the founders of the open collaborative textbook project “The Art of Molecular Programming”, a grassroots project aimed at collecting experts in the field to build a comprehensive textbook which will serve as a starting point for new and existing researchers. We discuss how the idea came about, inspired by the spirit of the Synthetic Biology community. The Art of Molecular Programming aims to be a project which collects all of the useful pieces of lore which exist scattered throughout the molecular programming literature and put them in one useful repository, taking away the pain that new graduate students endure in their first years while they struggle to build up a coherent picture of the field by reading countless ad-hoc papers. --- Find more information at the episode page here:


Kate Adamala

Kate Adamala is a biochemist building synthetic cells at the University of Minnesota College of Biological Sciences. Her research aims at understanding chemical principles of biology, using artificial cells to create new tools for bioengineering, drug development, and basic research. The interests of her lab span questions from the origin and earliest evolution of life, using synthetic biology to colonize space, to the future of biotechnology and medicine. She received a MSc in chemistry from the University of Warsaw, Poland, studying synthetic organic chemistry. In grad school, she worked with professor Pier Luigi Luisi from University Roma Tre and Jack Szostak from Harvard University. She studied RNA biophysics, small peptide catalysis and liposome dynamics, in an effort to build a chemical system capable of Darwinian evolution. Kate’s postdoctoral work in Ed Boyden’s Synthetic Neurobiology group at MIT focused on developing novel methods for multiplex control and readout of mammalian cells. Her full first name spells Katarzyna; she goes by Kate for the benefit of friends speaking less consonant-enriched languages. First we discuss Kate’s synthetic cells and whether or not they are living. These are phospholipid liposomes which encapsulate a full central dogma (transcription, translation). Synthetic cells are more complex than biochemical experiments, but at the moment, Kate does not consider her synthetic cells living. These cells are not self replicating, currently requiring a graduate-assisted replication. We then have an extended discussion about the ribosome, why it’s the biggest hurdle to achieving true self replication, and why it kind of sucks as a catalyst! Next, we move on to how synthetic cells can be used to aid in the research of brain computer interfaces (BCI). Kate’s vision is that, because synthetic cells can be so robustly controlled, they represent a form of “programmable goo” which would interface much more robustly with our brains than traditional silicon. She envisions the role of synthetic cells as being used as a less injurious interface for BCIs, which currently cause significant scarring to the brain. Finally, we talk about one of the most interesting topics covered on the molpigs podcast: space exploration! Kate discusses how synthetic cells, being so programmable, might be ideal devices for Martian terraforming. By engineering poly-extremophiles (extremophiles which are robust to many extreme conditions, organisms which do not exist on Earth) specific to the environment of Mars, it may be possible to design a metabolism capable to transforming Martian soil into something fertile. Additionally, synthetic cells might be used as on-board biochemical printers on long space missions. Their programmable metabolism may enable us to produce any biomolecule, such as medicines on demand. --- Find more information at the episode page here:


Erik Poppleton

In the third episode of our ‘Lab Pigs’ series, which highlights the research and journeys of early career researchers in our field, we talked with Erik Poppleton, of the Biodesign Institute at Arizona State University. Erik researches the use of computational modeling in informing the design of molecular machines. As part of this, he also develops general-use analysis tools for oxDNA, and conversion tools to integrate the various design and simulation tools in the nucleic acid nanotechnology ecosystem. We talked about his research, his experience writing academic software, and the relationship between geology and molecular programming. Core Simulation Tools - Main oxDNA documentation: - Current stable release (being retired soon): - Bleeding edge release (has Python bindings!): - The model is also available as part of LAMMPS, documentation can be found here: Useful tutorials - A textbook chapter covering how to relax and simulate origamis: - A textbook chapter covering the details of molecular simulation: - Example input files: Useful tools - TacoxDNA, converters from design software to oxDNA: - oxView, a visualizer and editor for oxDNA: - oxView documentation: - oxdna_analysis_tools, a library of python scripts for basic simulation analysis: -, a public webserver for running simulations: - ox-serve, run interactive simulations in your web browser using a Google Colab GPU: Of course, if you find these tools useful, please remember to cite us! The citations for each tool can be found in its documentation ( paper coming soon!) --- Find more information at the episode page here:


Yuan-Jyue Chen: Random Access and Similarity Search in DNA Data Storage

In this episode we talked with Yuan-Jyue Chen, of Microsoft Research and the University of Washington, on some of his research into DNA Data Storage. Yuan focussed on two topics: random access of data, and the accompanying issues with stochasticity and errors, and an application of DNA storage for efficiently searching a large database of images by similarity. Please note: The views expressed by Yuan in this podcast do not necessarily represent the views of Microsoft. --- Find more information at the episode page here: