Ben Good

@benjaminhgood.bsky.social

Assistant Professor of Applied Physics @Stanford. Theoretical biophysics, evolutionary dynamics & microbial evolution. https://bgoodlab.github.io/

Excited to share that I've been awarded a 5-year NIH MIRA (R35) from the National Institute of General Medical Sciences! The lab is growing! We're recruiting postdocs and research techs interested in microbial ecology, quantitative microscopy, microfluidics, and molecular biology. Please share!

check out our new work on the design principles underlying cytotoxic T-cell responses. how do trade-offs and cell economics shape immune decision making? led by Obinna Ukogu and in collaboration with Grégoire Altan-Bonnet. www.pnas.org/doi/10.1073/...

Design principles of the cytotoxic CD8+ T cell response | PNAS

Cytotoxic T lymphocytes eliminate infected or malignant cells, safeguarding surrounding tissues. Although experimental and systems-immunology studi...

pnas.org

Please share widely! We will imminently be posting a technician position in our lab group since @rheasood.bsky.social is off to grad school 🙌! If you know of anyone excited about molecular biology, evolution, and functional genomics please have them reach out (schumer at stanford). Start date ~June

We posted a new theory preprint. I am very interested to hear what the community thinks about it. We looked at the dynamics of evolution on several (simple) models of modular genotype-phenotype-fitness maps and found that populations approach a quasi-steady state we call "module-selection balance".

bioRxiv Evolutionary Biology@biorxiv-evobio.bsky.social · 4mo ago

Module-selection balance in the evolution of modular organisms https://www.biorxiv.org/content/10.64898/2026.04.01.715873v1

Happy to share the final version of @oliviamghosh.bsky.social's paper on inferring low dimensional phenotype-fitness maps from high-throughput fitness measurements across environments. Fun collaboration with @oliviamghosh.bsky.social, @grantkinsler.bsky.social, & @petrovadmitri.bsky.social

PLOS Biology@plosbiology.org · 4mo ago

Predicting the effect of a #mutation on #fitness is hard. @oliviamghosh.bsky.social @petrovadmitri.bsky.social &co use fitness effects of adaptive yeast mutants to show that underlying genotype-phenotype-fitness maps are low-dimensional but context-dependent @plosbiology.org 🧪 plos.io/4dLy2Ez

Two models for the nature of pleiotropy in adaptation. Left: Schematic of the environmental structure in this study. Environments can be mapped onto a multidimensional environment space characterized by chemical and physical compositions. The large green circle represents an environment where adaptive mutants evolved, and the large pink circle is a distant environment. Around each base, a set of identical environmental perturbations (arrows) is applied, generating clusters of similar environments around distinct base environments. Top right: Schematic of fitnotype map for adaptive mutants near their home base environment. By measuring fitness in each of the green environments, one can infer how many fitnotypes matter for this set of mutants in their home environment. Here, only four of the possible 8 fitnotypes matter. Bottom right: When the mutants are moved to the distant base environment, and their fitness is measured in all pink environments (base and perturbations), there are two possibilities. Either more fitnotypes become important and the space appears higher-dimensional (left, pleiotropic expansion), or the set of fitnotypes that matters remains low-dimensional, but shifts (right, pleiotropic shift).

I am seeking a postdoc to join my group at UCLA -- ideally the candidate would have some experience in either population genetics or microbes/microbiome (computational background needed). We have a range of projects and are happy to tailer to your interests. Please dm/email me if interested.