From widefield to confocal tracking and from single-spot to photon-array detectors, we chart the move beyond localization–linking toward integrative methods for crowded, superresolved tracking.
@labpresse.bsky.social

Learn more 👇
https://aippub.org/4qmTTFS

Specifically, MERFISH data where raw (or minimally processed / registered) images are available across rounds/bits, and where z-planes are sampled densely enough to justify explicit 3D modeling (ideally dz ≤ 0.5 µm; even ~0.75 µm would be workable depending on optics).

Help!!!

We're working on a Bayesian approach for decoding MERFISH images in 3D, and we’re trying to identify an accessible MERFISH dataset that’s “truly volumetric” in the imaging sense.

Even a pointer to the right paper, repository, or person to ask would be helpful.

Thanks so much!

When is it ok to invoke a small Reynolds number approximation in finite temperature fluids?

For spatially correlated fluids, curiously the answer is…never? 🧐

arxiv.org/html/2601.05...

#fluids #fluidphysics

It’s been 30 yrs since Zwanzig’s “non-eq stat mech”

As written, it has solidified the notion that theory develops models, and MD (perhaps) should be left to parametrize.

Maybe it’s time to re-pitch the work using functional integrals & tie this formulation to likelihoods :)

Recent discoveries on the acquisition of the highest levels of human performance Scientists have long debated the origins of exceptional human achievements. This literature review summarizes recent evidence from multiple domains on the acquisition of world-class performance. We re...

Really interesting research showing that while ultra-specialization in a single discipline might lead to better results early in one’s career, multi-discipline training and practice pays off big time in the long run. This applies to a range of professions from scientists to athletes and more

A bit of an emotional pic.

A Silbey lab reunion of sorts in Honolulu. L2R: ⁦‪@LabPresse‬⁩, Jaeyoung Sung, Yuen-Chung Cheng, YoonJoon Jung, Alex Tkachenko.

Haven’t seen some people in ~20 yrs 😢

Happy to be @acs.org #pacifichem with L2R Banu Ozkan, Jaeyoung Sung, Matthias Heyden, and @labpresse.bsky.social for our joint @arizonastateuni.bsky.social Center for Biological Physics - Chung Ang GCSC symposium.

Especially happy about Mai Tai’s 🍹

A cautious user’s guide in applying HMMs to physical systems Nature, as far as we know, evolves continuously through space and time. Yet, the ubiquitous hidden Markov model (HMM)—originally developed for discrete time and

Our latest JChemPhys selected as highlight.

Our title communicates it all :)

“A cautious user’s guide in applying HMMs to physical systems”

pubs.aip.org/aip/jcp/arti...

ASU Physics is searching for a new Chair.

If interested, please apply. Feel free to contact me with any questions.

We are seeking, first and foremost, a leader & world-class scientist with a strong research record

apply.interfolio.com/176489

#asu #ASUResearch

Lab Halloween fun before lab reception for Weiqing Xu’s departure to the lab of @jonasries.bsky.social

We will miss you Weiqing!

Perspective: An outlook on fluorescence tracking Tracking single fluorescent molecules has provided new insights into dynamic molecular processes at the single-molecule level. This Perspective traces the evolu

Here is the original:

pubs.aip.org/aip/jcp/arti...

Tracing fluorescence tracking’s past, present, and future Artificial intelligence and parallel computing could refine studies of the movement of single molecules inside cells.

Tracking has always been at the ❤️ of the scientific method, from planetary motion to single particles.

Weiqing’s thesis intro on tracking was so beautiful we turned it into a perspective in JCP who then selected it as a #Scilight.

Take a look! 😊

www.aip.org/scilights/tr...

News story our APS fellowship.

A testament to the great people we work with (and the unwavering rigor of Bayesian approaches, impervious to hype) 😊 🙏

news.asu.edu/b/20251021-a...

It’s an Honor to be named 2025 @apsphysics.bsky.social Fellow.

🙏 our lab members and collaborators.

Citation: “For pioneering contributions to Bayesian method development in biological physics, particularly […] to imaging and single-molecule experiments. 

#APSFellow

The journey continues. UT Austin and Oden tomorrow and Friday. Here with Dima Makarov :)
(Discussing Bach, Richter, Gould, Yuja Wang, and maybe some single molecule 😊)

One of my favorites by Voltaire in describing Canada
“quelques arpents de neige, habités par des barbares, des ours et des castors” 🙃

Thanks to the CTBP for the wonderful invitation for a seminar at Rice! 🙏
Joining me are Tolya Kolomeisky and Oleg Igoshin.

Hello everyone,

Tomorrow I’ll be giving a chalk talk on our new eLife:
“REPOP: bacterial population quantification from plate counts”

elifesciences.org/reviewed-pre...

Looking forward to seeing you!!

#eLife #datascience #biophysics #bioinformatics #Bayesian #REPOP

Thanks for the link to your paper!

How Easy Is It to Learn Motion Models from Widefield Fluorescence Single Particle Tracks? Motion models (i.e., transition probability densities) are often deduced from fluorescence widefield tracking experiments by analyzing single-particle trajectories post-processed from data. This analy...

Can we learn motion models from post-processed tracks? 🧐
Not really 😢

Emission noise accounts for ~99% of the likelihood.

TLDR: What you think is anomalous diffusion… might just be noise. 🤷‍♂️🤷‍♂️🤷‍♂️🤷‍♂️

🔗 Read more in our latest preprint: arxiv.org/abs/2507.05599

#Biophysics

GitHub - PessoaP/REPOP Contribute to PessoaP/REPOP development by creating an account on GitHub.

6/6
If you plate, you need REPOP.

Software -- github.com/PessoaP/REPOP
Preprint -- elifesciences.org/reviewed-pre...

Special thanks to the Lab Members @pedropessoaphd.bsky.social, Carol Lu and Stanimir Tashev

As well as Rory Kruithoff and @dpshepherd.bsky.social
#Biophysics #QuantitativeBiology

GitHub - PessoaP/REPOP Contribute to PessoaP/REPOP development by creating an account on GitHub.

5/6
This is why we built REPOP, an #opensource tool to REconstruct POpulations from Plates.

Straightforward to use and with tutorials available on #GitHub

github.com/PessoaP/REPOP

With all the #Bayesian rigor and #PyTorch speed

4/6
As we show in the paper, this
- Overestimatese variability
- Can miss real structure in your population: Subpopulations and/or multimodality as biological differences across samples,

3/6
This assumes:
– No randomness in how many bacteria end up on the plate
– No randomness in the original swab

In reality, every step is noisy.

2/6
Plate counting is a simple:

You dilute a sample, plate a small volume, and count colonies.

Say you dilute by 200×, and count 50 colonies.
Easy just multiply 50 × 200 = 10k bacteria, right?

NOT QUITE...

Hello all,

If you do #PlateCounting, you may want to take a look at our new eLife @elife.bsky.social

If you don't, I still encourage you to join for an interesting discussion.

Follow the thread 🧵

elifesciences.org/reviewed-pre...

#Microbiology #DataScience #PyTorch #QuantitativeBiology #REPOP

3/3
In it, we simulate some general physical systems that violate the HMM's assumptions and demonstrate contradictory results that can arise. Surprisingly, the problems with HMM analysis only grow with better data acquisition (higher data acquisition rate and/or reduced noise).

2/3
HMM are classic in time series analysis, but they can yield confusing, seemingly contradictory results. In particular, when applying HMMs to physical systems where two key HMM assumptions, that state spaces are discrete, and that transitions are instantaneous, don't apply.

A cautious user's guide in applying HMMs to physical systems Nature, as far as we know, evolves continuously through space and time. Yet the ubiquitous hidden Markov model (HMM)--originally developed for discrete time and space analysis in natural language proc...

Have you ever applied a Hidden Markov Model (HMM)?
Does the results seems contradictory?

If so, you are going to love our new preprint:

arxiv.org/abs/2506.05707