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...
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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.
New preprint from the lab and wonderful work by Seppe de Winter:
System-wide extraction of cis-regulatory rules from sequence-to-function models in human neural development
www.biorxiv.org/content/10.6...
Out now in Nature as part of the 'Brain Development' special issue, our perspective on the developing human and mammalian brain. www.nature.com/articles/s41...
A major KI initiative to recruit new assistant professors with outstanding proposals in all areas of medicine, biomedicine and public health. We offer an amazing research environment, great colleagues and generous startup packages. Check it out and get working on your applications! (repost please!)
You'd think they have stock in SAS
Heads-up for major new faculty search at KI — with great startup packages and a wide range of subject areas.
Breaking from @science.org: The Trump administration wants to kill off a host of active and healthy NASA climate and planetary spacecraft. It would be a "leaner, more focused" agency, they say -- and one far less capable of studying the Earth and exploring space.
Congratulations Karl!
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.
Data collected with the new sequencing platform HyDrop v2 is shown. First, a schematic overview of the bead batches of the microfluidic beads is followed by a tSNE and a barplot showing the costs in comparison to 10x Genomics. Then, a track of mouse data (cortex) is shown together with nucleotide contribution scores in the FIRE enhancer in microglia. Here, the HyDrop and 10x based models show the same contributions. On the right, the Drosophila embryo collection is explained; in the paper HyDrop v2 and 10x data are compared to sciATAC data. Then, a nucleotide contribution score is also shown, whereas HyDrop v2 and 10x models show the same contribution, just as in mouse.
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...
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...
NEWS This Brazilian frog might be the first pollinating amphibian known to science
It’s the first time a frog—or any amphibian—has been observed pollinating a plant, researchers reported in 2023.
Learn more on #WorldFrogDay: scim.ag/4kGdvCy
Congrats Camiel, awesome to have you in the lab!
