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Reposted

Volodymyr Minin 🇺🇦🇺🇸 @vmminin.bsky.social · 3d

In another display of incredible resilience, Ukrainian mathematicians in 2022(❗) opened a new International Centre for Mathematics in Ukraine (ICMU): icmu.ua/en

It was pleasure to give an online mini-course on Bayesian Statistics to Ukrainian students and scientists: icmu.ua/en/events/in...

International Centre for Mathematics in Ukraine - ICMU

ICMU supports top-level research in mathematics, with special emphasis on training younger generations of scientists and the development of mathematics in Ukraine.

icmu.ua

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Reposted

Yun S. Song @yun-s-song.bsky.social · 16d

We are excited to share GPN-Star, a cost-effective, biologically grounded genomic language modeling framework that achieves state-of-the-art performance across a wide range of variant effect prediction tasks relevant to human genetics.
www.biorxiv.org/content/10.1...
(1/n)

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Gytis Dudas @evogytis.bsky.social · 16d

My MSc student Indrė Blagnytė has a #preprint up on @biorxivpreprint.bsky.social on influenza D virus: www.biorxiv.org/content/10.1.... Flu D was discovered back in 2011, mostly circulating in cattle. Despite lots of research, a comprehensive analysis of its phylogeography had been missing. 1/6

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Reposted

William DeWitt @wsdewitt.github.io · Aug 26

A short blog post about a recent preprint (work hatched as a very fun all-postdoc collaboration at @sfiscience.bsky.social)

A dynamical perspective on triggering multiscale immune responses

Preprint: BH Schlomann, WS DeWitt, Y Zhang, K Shah. Ignition criteria for trigger waves in cell signaling. arXiv:2508.16810 [q-bio.CB]

dewitt-lab.github.io

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Reposted

Frederick "Erick" Matsen @matsen.bsky.social · Aug 19

Why does selection feel so weak relative to mutation in affinity maturation? A new blog post giving three perspectives, including our new transformer-based model of natural selection on antibodies: matsen.group/general/202...

The term 'affinity maturation' understates the influence of somatic hypermutation

Three recent papers quantify how nucleotide-level mutation processes drive antibody evolution.

matsen.group

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 19

And @vmminin.bsky.social! Somehow I couldn't find you before.

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

Ultimately, direct comparison between the approaches is hard since their three models are so different, but that's what makes them so complementary. With @matsen.bsky.social @yun-s-song.bsky.social @wsdewitt.github.io, and others I can't find on here, but may have missed!

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

they infer what we call an "effective" birth rate (left column) that is more biologically interpretable than the "intrinsic" rate inferred by deep learning (center column), but which also varies with time and across GCs.

effective vs intrinsic birth rates over time for several simulated GCs using final, fitted data parameter values

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

It also turns out there's some subtleties in comparing to the more analytic traveling wave and branching process approaches:

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

The results consist of a curve, or rather, two versions of (hopefully) the same curve: one infers the parameters of a sigmoid shape, the other infers independent bin values.

Data results: affinity fitness response curves

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

Finally, we applied the model to real data, inferring the affinity-fitness response curves for many potential parameter values, choosing the best combination based on summary statistic matching.

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

We then trained a deep learning model on simulation samples with a wide variety of parameter values.

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

Here I'll focus on the deep learning approach. We first built a birth-death-mutation simulator and carefully matched it to data to ensure we understood the processes underlying the experimental results.

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

whereas a branching process model arxiv.org/abs/2508.09519 and deep learning (this thread) zoom in to use detailed lineage trees to inform inference.

Bayesian inference of antibody evolutionary dynamics using multitype branching processes

When our immune system encounters foreign antigens (i.e., from pathogens), the B cells that produce our antibodies undergo a cyclic process of proliferation, mutation, and selection, improving their a...

arxiv.org

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

A traveling wave model takes a very high level view, essentially modeling histograms of affinity (Fig 6 in doi.org/10.1101/2025...)

Replaying germinal center evolution on a quantified affinity landscape

Darwinian evolution of immunoglobulin genes within germinal centers (GC) underlies the progressive increase in antibody affinity following antigen exposure. Whereas the mechanics of how competition be...

doi.org

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

Higher affinity antibodies, on average, have more offspring. But what exactly does this relationship look like? We used three complementary approaches to measure it:

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

In the weeks after we're exposed to a pathogen, our antibodies evolve toward higher affinity. The cellular mechanisms here are fairly well understood, but a recent experiment from @victora.bsky.social gave us the opportunity to also learn about the mathematical dynamics of this selection.

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psathyrella.bsky.social @psathyrella.bsky.social · Aug 16

In a new preprint we use deep learning on lineage trees to infer the functional form of the relationship between affinity and fitness that controls antibody evolution in germinal centers: arxiv.org/abs/2508.09871 🧵

Inference of germinal center evolutionary dynamics via simulation-based deep learning

B cells and the antibodies they produce are vital to health and survival, motivating research on the details of the mutational and evolutionary processes in the germinal centers (GC) from which mature...

arxiv.org

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Reposted

Yun S. Song @yun-s-song.bsky.social · Aug 15

Antibodies are highly diverse, but most possible sequences are unstable or polyreactive. In this work, just published in Cell Syst., we propose a new source of data for modeling constraints from these properties. Our models show clear improvements in predicting Ab dysfunction. (1/n)
t.co/qCZERPUMPF

https://authors.elsevier.com/a/1lbX08YyDfuZWX

t.co

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Reposted

Jiansi Gao @jsigao.bsky.social · Jun 17

Excited to share my new preprint developed with @matsen.bsky.social, in collaboration with Marius Brusselmans, Luiz Carvalho, @msuchard.bsky.social, and @guybaele.bsky.social, on the biological causes and impacts of tree space ruggedness in phylodynamic inference. 1/
www.biorxiv.org/content/10.1...

www.biorxiv.org

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Reposted

Gabriel Victora @victora.bsky.social · Jun 5

Wanted to highlight our latest preprint--a huge effort by multiple people and labs, but led primarily by @wsdewitt.github.io, Tatsuya Araki, and Ashni Vora, in a very close wet-dry collaboration with @matsen.bsky.social’s lab at the Hutch

www.biorxiv.org/content/10.1...

Replaying germinal center evolution on a quantified affinity landscape

Darwinian evolution of immunoglobulin genes within germinal centers (GC) underlies the progressive increase in antibody affinity following antigen exposure. Whereas the mechanics of how competition be...

www.biorxiv.org

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Reposted

Frederick "Erick" Matsen @matsen.bsky.social · May 20

New blog post: our recent work to understand the somatic hypermutation process that enables antibodies to incrementally improve.

A story of running into the limitations of deep learning, but still gaining biological insight along the way.

matsen.group/general/2025...

Two new approaches to learn about antibody somatic hypermutation

We try to learn about SHM mechanism and do so by directly using mechanistic models, and by exploring deep architectures.

matsen.group

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Reposted

Frederick "Erick" Matsen @matsen.bsky.social · May 18

matsen.group/general/2025...

Let's blog!

My return to blogging, and why I hope to read your blog too.

matsen.group

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Reposted

Kevin Zollman @kevinzollman.com · Feb 19

I have a new paper about these cute little guys (and some girls)!

White-necked Jacobins are interesting because all males and some but not all (!) females are brightly colored. The scientific question is why some but not all females?

(Img credit: Kate & Sam)

A picture of a white-necked Jacobin hummingbird with a blue head, long beak, blue-green shoulders, and a white belly. The hummingbird is sitting on a branch and staring into the camera.

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Reposted

Michael Eisen @mbeisen.bsky.social · Dec 19

Kudos to NIH for getting rid of the odious 12 month delay in public access (a capitulation to the demands of scientific societies). But, as the new policy assumes grantees will continue to publish their work in traditional scientific journals, it remains unacceptable.

grants.nih.gov/grants/guide...

NOT-OD-25-047: 2024 NIH Public Access Policy

NIH Funding Opportunities and Notices in the NIH Guide for Grants and Contracts: 2024 NIH Public Access Policy NOT-OD-25-047. OD

grants.nih.gov

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