nicholas.noll

quantitative.biology

I am a quantitative biologist with a background in Physics who is broadly interested in discovering the fundamental principles that govern living systems. Echoing Phil Anderson, More is Different: Biology has a beautiful wealth of complexity that operates at many different scales with interesting structures underneath. I currently sit with Richard Neher’s group within the Biozentrum at the University of Basel, staring at our new building.

current research

I am currently interested (some may say obsessed) in understanding how horizontal gene transfer and homologous recombination quantitatively affect evolution, with the ultimate goal in forming simple models able to predict rates of evolutionary outcomes. At the present, population genetic models exist at both extrema of recombination rate; we have some quantitative grip on the asexual and single locus evolution. We currently have no satisfactory models, and thus computational tools, in the intermediate regime, let alone that account for structural variation. Due to their smallish genome sizes, short (on the time-scale of a research project) generation times and epidemiological relevance, these questions are best addressed within the microbial world.

With the recent introduction of long-read, single molecule sequencing this is no longer a purely theoretical pursuit but can be empirically measured within ‘wild’ or ‘clinical’ ecosystems. My research tends to oscillate between empirics and theory driven modeling - I find one informs the other quite well. Evolution is a noisy process and thus requires large datasets to find signal. This requires scalable computational algorithms. As very few exist for multiple genome alignment, a lot of my thought is allocated here. Useful heurestics can teach us a lot about the underlying structure of the problem.

previous interests

I completed my PhD in UCSB where I studied under Boris Shraiman in the tangentially related field of Morphogenesis. Developmental Biology has been revolutionized by the fluorescent molecule which allows researchers the ability to watch development happen live. However, the mechanical state of the embryo which ultimately drives the developmental flow remains unknown. Boris and I worked out a model of the active mechanics of cells, and leveraged this to formulate a robust mechanical inference algorithm solely from measured cellular geometries obtained from live image movies, that was shown to be quite predictive during early Drosophila gastrulation. We also found a pretty neat duality.

Email
Github
Neher Lab