Picture of myself in front of the Iso logo

Thrilled to join Isomorphic Labs—time to build better ML models of cells and create the drugs of the future!! 🧬🧫🧑‍💻🥳

Picture of myself in front of the Iso logo

Thrilled to join Isomorphic Labs—time to build better ML models of cells and create the drugs of the future!! 🧬🧫🧑‍💻🥳

We are super excited to welcome Dmitry Kobak @hippopedoid.bsky.social as a new VIB.AI group leader! The Kobak lab will officially kick off in April at the VIB.AI Ghent hub.

More:
vib.ai/en/news/dmit...

1/ Apply for an inter-disciplinary postdoc position in Heidelberg with the Health & Life Science Alliance
Deadline: **31 March**
Project proposals can be self-designed or adapt one of the outlines on the website ("List of project outlines for download")

www.health-life-sciences.de/opportunitie...

I have also seen, from people who know base really well, incredibly elegant code using tapply, merge, and clever indexing. But, in my experience, the typical code of a medium experienced person that uses the tidyverse is more robust than the one that uses base.

It's an example. As I said, the tidyverse has the advantage that it provides functions for typical data analysis tasks all in one place with great documentation and common semantics. Also, personally I'm not a fan that merge auto-sorts the output.
Another example would be pivot_longer :)

Teach the tidyverse! I have seen the code from people, who only learned base, that reinvents a join function and it's not pretty 😅
In the end, the tidyverse is a collection of useful functions for typicy data analysis tasks and beginners benefit from being told those exist :)

Biological Laboratory | LEGO® Ideas This is a two-floor realistic Biological Laboratory building. In this design, I try to tell stories about biologists, introduce biology concepts to general publ…

I just made an account and voted for this biology laboratory made of LEGO to "promote biological research and inspire more people into the world of biology". They need 10K votes. Reposting and/or voting below would be helpful. 🤗
beta.ideas.lego.com/product-idea...

How far back in time can you understand English? An experiment in language change

www.deadlanguagesociety.com/p/how-far-ba...

I cannot speak as to the accuracy of the piece yet I found it a fascinating exercise @adamroberts.bsky.social @drlauravarnam.bsky.social

screaming this from the rooftops

Screenshot of Job Ad

EMBL site in Heidelberg

Zurich, incl. a bit of UZH/USZ

Job offer: PhD-level biostatistician with ML&omics experience to work on prediction models for CAR T cell therapy, in an exciting clinical trial - spatial omics - data science consortium (LOOP/INTeRCePT3.0 centered in Zurich; this position in Heidelberg)

embl.wd103.myworkdayjobs.com/en-GB/EMBL/j...

It definitely helps, but I think it's also simply that most scientists have a LinkedIn account and occasionally check it, whereas still only a minority has a bluesky account.

Yeah, the amount of engagement on LinkedIn compared to bluesky is crazy. I recently posted about a new paper and it got 480 likes on LinkedIn vs 7 on bluesky (and I have more followers here than there...) :/

We wrote a review of representation learning methods of single-cell RNA-seq data, where we compare factor models, autoencoders, contrastive learning, and foundation models 🎉

rnajournal.cshlp.org/content/earl...

Postdoctoral Researcher or Senior Scientist (AI × Biology)

Boeva Lab is #hiring postdocs and senior scientists in AI/ML for Cancer Biology! Check the offer and apply at: jobs.ethz.ch/job/view/JOP...

View from the hotel room

Poster session 2024, with Valentina Boeva, Constantin Ahlmann-Eltze and others

Wednesday afternoon hike incl. swim in the mountain river

Another view from the hotel room

Apply for the Ascona workshop "Statistical and AI methods for multi-modal multi-scale modeling of biological systems", 28 Jun-3 Jul 2026 on Monte Verità, Lago Maggiore at the foot of the Swiss Alps.

ascona2026.sciencesconf.org

Save the date: April 9 from 4pm to 6pm CET. Our department is hosting an online seminar with @noeliaferruz.bsky.social @sdomcke.bsky.social @const-ae.bsky.social who will talk about models for protein design, large-scale perturbation screens, and benchmarking of perturbation prediction models.

Join me in 5.5h, when we discuss our benchmark of perturbation prediction models and what the right metric is to assess if a gene expression prediction is good!

🚀 Excited to share our new preprint: msBayesImpute - A Versatile Framework for Addressing Missing Values in Biomedical Mass Spectrometry Proteomics Data
👉 Improves imputation accuracy, normalization, and differential expression detection
📝www.biorxiv.org/content/10.1101/2025.10....

Heads up: ignore samtools dot org, similarly minimap2 dot com and likely others. It's owned by a known phishing site and while the binaries they offer look valid currently (but note they may be serving us different binaries to others), that could change.

Ie: it's not us (Samtools team)! Be warned

We're excited to share that our preprint on anndataR, a new package bringing Python's AnnData to R, is now available on bioRxiv 🎉

🔗 Read the paper: www.biorxiv.org/content/10.1...
💻 Check the package in action: anndatar.data-intuitive.com

An arrow with a LaTeX equation

Trigonometric functions and a unit circle

A bivariate change model with structured residuals

A hierarchical model of cognitive abilities

Now on CRAN, ggdiagram is a #ggplot2 extension that draws diagrams programmatically in #Rstats. Allows for precise control in how objects, labels, and equations are placed in relation to each other.
wjschne.github.io/ggdiagram/ar...

Makes sense. I imagine this would simply be my primary use case, and I would prefer not having to refer to `x` twice. Something like:

replace_values <- function(x, ..., from=NULL, to=NULL, lookup=NULL){
if(! is.null(lookup)){
from <- names(lookup)
to <- lookup
}
...
}

This looks great! I think it would be neat if the functions also supported named look-up vectors in addition to the `to` and `from` arguments :)

Beeswarm plot of the prediction error across different methods of double perturbations showing that all methods (scGPT, scFoundation, UCE, scBERT, Geneformer, GEARS, and CPA) perform worse than the additive baseline.

Line plot of the true positive rate against the false discovery proportion showing that none of the methods is better at finding non additive interactions than simply predicting no change.

Our paper benchmarking foundation models for perturbation effect prediction is finally published 🎉🥳🎉

www.nature.com/articles/s41...

We show that none of the available* models outperform simple linear baselines. Since the original preprint, we added more methods, metrics, and prettier figures!

🧵

Pre-Cancer Immunology The Pre-Cancer Immunology Lab (James Reading Lab) is mapping pre-invasive T cell dynamics during carcinogenesis to detect and intercept cancer development.

🚨 PhD Position available in our lab 🚨 exploring the power of blood immune multi-omics to detect lung cancer years prior to clinical diagnosis in a unique cohort of >10,000 CT screened individuals.
✅ Wet & dry lab
✅ September 2025 enrolment
✅ UK tuition fees only

www.ucl.ac.uk/medical-scie...

I wrote about AI foundation models for biology last year: www.nytimes.com/2024/03/10/s... Benchmarking tests since then aren't finding that they're better than simpler models of how genes and cells work.

Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines - Nature Methods The analysis presented in this Brief Communication shows that, despite their complexity, current deep learning models do not outperform linear baselines in predicting gene perturbation effects, thus e...

An analysis shows that current deep learning models do not beat linear baselines in predicting gene perturbation effects, thus emphasizing the importance of further method development and evaluation. @const-ae.bsky.social @wkhuber.bsky.social @s-anders.bsky.social

www.nature.com/articles/s41...

Haha, would also be a succinct summary of most of my academic work 😅

Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines Nature Methods - The analysis presented in this Brief Communication shows that, despite their complexity, current deep learning models do not outperform linear baselines in predicting gene...

And lastly, a big shout-out to @wkhuber.bsky.social and @s-anders.bsky.social!

Link to pdf: rdcu.be/ey7x0