Really amazing work and a big effort by Olga, Alex, Julie, Koen and many others. Check it out for sure!

Alexandra P@alexanrna.bsky.social · 4mo ago

1/ 🧬 Happy to share our new preprint on modeling cis-regulatory variation in human brain enhancers across a large Parkinson’s disease cohort: www.biorxiv.org/content/10.6... Details in the thread below:

New preprint @cxqiu.bsky.social @jshendure.bsky.social ! Can we learn regulatory grammars of human cell types — by training on mouse development and transferring across 241 mammalian genomes? Introducing STEAM & a whole-organism scATAC-seq atlas from E10 to birth. www.biorxiv.org/content/10.6...

CREsted is finally out! You can find the article, together with a summarizing Research Briefing, in thread. 🦎

Nature Methods@natmethods.nature.com · 4mo ago

CREsted: an efficient and user-friendly toolbox for analysis, modeling and design of cell-type-specific enhancers. www.nature.com/articles/s41...

Last summer I spent 4 months working at the @alleninstitute.org as a Visiting Scientist. Recently we released some preprints about the work we collaborated on, where from new multiome atlases of CNS regions we tried to decipher underlying enhancer logic with CREsted (among many other things). (1/n)

Paper alert! 💻 How many cells do you need to train reliable deep learning models in regulatory genomics? We asked how data quality, sequencing depth, and dataset size affect training of sequence-to-function models from scATAC-seq. Out now www.nature.com/articles/s41... (details below)

We are thrilled to share our new pre-print: “System-wide extraction of cis-regulatory rules from sequence-to-function models in human neural development”. S2F-deeplearning models can accurately encode enhancers, yet decoding these models into human-interpretable rules remains a major challenge.

Relieved to finally post my whole developing brain evolutionary "theory of everything" preprint! www.biorxiv.org/content/10.1...

ANTIPODE Provides a Global View of Cell Type Homology and Transcriptomic Divergence in the Developing Mammalian Brain

Diverse neurons and glia are generated in conserved spatial and temporal sequences during mammalian brain development. Divergence in gene regulatory networks can alter brain composition, scaling, timi...

biorxiv.org

We have two open positions for a ML and a LLM engineer to launch a machine learning expertise unit in our center @vibai.bsky.social, see vib.ai/en/opportuni...

We will have our next community meeting on Tuesday, 2025-09-16 at 18:00 CEST! Niklas Kempynck will be presenting on CREsted, a package for training enhancer models on scATAC-seq data. (Zoom registration link and more information in thread!) 🧵

I wrote a quick application note on Tomtom-lite, a Python implementation of the Tomtom algorithm for comparing PWMs against each other. This implementation can be 10-1000x faster and, as a Python function, can be integrated into your workflows easier. www.biorxiv.org/content/10.1...

Tomtom-lite: Accelerating Tomtom enables large-scale and real-time motif similarity scoring

Summary Pairwise sequence similarity is a core operation in genomic analysis, yet most attention has been given to sequences made up of discrete characters. With the growing prevalence of machine lear...

biorxiv.org

One thousand candidate enhancers tested in vivo in the mouse brain! A massive resource and oh so useful as validation set for genome-wide enhancer prediction methods. Super fun to be involved in one of the papers: ‘the prediction challenge paper’ by Nelson&Niklas et al www.cell.com/cell-genomic...

Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex

Johansen et al. report the results of a community challenge to predict functional enhancers targeting specific brain cell types. By comparing multi-omics machine learning approaches using in vivo data...

cell.com

allen institute@alleninstitute.org · last yr.

In the battle against brain disease, researchers can now rely on a new arsenal of genetic tools – The Armamentarium. Together with scientists from across the NIH BRAIN Initiative, we’ve created and published over 1000 new enhancer AAV vectors. 🧠📈

Check out our work on evaluating methods for predicting in vivo cell enhancer activity in the mouse cortex! Combined, scATAC peak specificity and sequence-based CREsted predictions gave the best predictive performance, aiming to advance genetic tool design for cell targeting in the brain.

Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex

Johansen et al. report the results of a community challenge to predict functional enhancers targeting specific brain cell types. By comparing multi-omics machine learning approaches using in vivo data...

cell.com

Calling someone bird-brained is, in fact, a way of calling someone highly intelligent. @yaseminsaplakoglu.bsky.social reports: www.quantamagazine.org/intelligence...

Intelligence Evolved at Least Twice in Vertebrate Animals | Quanta Magazine

Complex neural circuits likely arose independently in birds and mammals, suggesting that vertebrates evolved intelligence multiple times.

quantamagazine.org

Very proud of two new preprints from the lab: 1) CREsted: to train sequence-to-function deep learning models on scATAC-seq atlases, and use them to decipher enhancer logic and design synthetic enhancers. This has been a wonderful lab-wide collaborative effort. www.biorxiv.org/content/10.1...

CREsted: modeling genomic and synthetic cell type-specific enhancers across tissues and species

Sequence-based deep learning models have become the state of the art for the analysis of the genomic regulatory code. Particularly for transcriptional enhancers, deep learning models excel at decipher...

biorxiv.org

Also check out Hannah’s thread on our latest preprint on HyDrop v2, an open-source platform for scATAC-sequencing, and a great, cost-efficient way of generating data for S2F models. 🙌

Hannah Dickmänken@hannahdckmnkn.bsky.social · last yr.

Our new preprint is out! We optimized our open-source platform, HyDrop (v2), for scATAC sequencing and generated new atlases for the mouse cortex and Drosophila embryo with 607k cells. Now, we can train sequence-to-function models on data generated with HyDrop v2! www.biorxiv.org/content/10.1...

We released our preprint on the CREsted package. CREsted allows for complete modeling of cell type-specific enhancer codes from scATAC-seq data. We demonstrate CREsted’s robust functionality in various species and tissues, and in vivo validate our findings: www.biorxiv.org/content/10.1...

Very excited to share our new preprint together with @daniedaaboul.bsky.social, where we studied the gene regulatory code that hippocampal granule cells (GCs) use during synapse formation (1/n)

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · last yr.

A dynamic gene regulatory code drives synaptic development of hippocampal granule cells https://www.biorxiv.org/content/10.1101/2025.03.27.645686v1

How does gene regulation shape brain evolution? Our new preprint dives into this question in the context of mammalian cerebellum development! rb.gy/dbcxjz Led by @ioansarr.bsky.social, @marisepp.bsky.social and @tyamadat.bsky.social, in collaboration with @steinaerts.bsky.social

The latest Discover ASAP episode dives into "Cell Type Directed Design of Synthetic Enhancers," a study published in Nature by CRN Team Voet. They discuss how machine learning enables precise enhancer design for targeted gene expression 🧬 Watch: www.youtube.com/watch?v=Qcms...

We wrote a review article on modelling and design of transcriptional enhancers using sequence-to-function models. From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design! @natrevbioeng.bsky.social www.nature.com/articles/s44...

Modelling and design of transcriptional enhancers - Nature Reviews Bioengineering

Enhancers are genomic elements critical for regulating gene expression. In this Review, the authors discuss how sequence-to-function models can be used to unravel the rules underlying enhancer activit...

nature.com

This has been a fantastic adventure - to capture the genomic regulatory code underlying brain cell types (using deep learning models trained on chromatin accessibility), and then use these models to compare cell types between the bird and mammalian brain

Niklas Kempynck@niklaskemp.bsky.social · last yr.

Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂

Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂

VIB.AI@vibai.bsky.social · last yr.

In a new study, Nikolai Hecker, Niklas Kempynck et al. in the team of @steinaerts.bsky.social explore 300 million years of brain evolution through the lens of enhancer codes. www.science.org/doi/10.1126/...