Hannah Dickmänken
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hannahdckmnkn.bsky.social
Hannah Dickmänken
@hannahdckmnkn.bsky.social
My favorite ice cream flavors are science & feminism. PhD candidate at VIB.AI in Stein Aerts lab 🪰 - she/her
Reposted by Hannah Dickmänken
Happy to share the Biodiversity Cell Atlas white paper, out today in @nature.com. We look at the possibilities, challenges, and potential impacts of molecularly mapping cells across the tree of life.
www.nature.com/articles/s41...
September 24, 2025 at 3:12 PM
Ending my two weeks conference marathon: last week Single Cell Spatial Omics #SCSO 600 year #KULeuven edition & now #SCG2025 - learned so much & am now already searching for the next one! Any recommendations for biodiversity, non-model organisms & genetics in 2026? 🪰🦋🐛🐌
September 18, 2025 at 4:44 PM
Reposted by Hannah Dickmänken
1/ First preprint from @jdemeul.bsky.social lab 🥳! We present our new multi-modal single-cell long-read method SPLONGGET (Single-cell Profiling of LONG-read Genome, Epigenome, and Transcriptome)! www.biorxiv.org/content/10.1...
September 10, 2025 at 3:48 PM
Reposted by Hannah Dickmänken
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...
www.biorxiv.org
April 4, 2025 at 9:04 AM
Make sure to also check out the preprint on the new CREsted package: many more sequence-to-function models across different species! … and it works with HyDrop v2 data as well.
Congrats to @niklaskemp.bsky.social & @seppedewinter.bsky.social & all the others working on this super cool project!
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...
April 4, 2025 at 10:04 AM
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...
April 4, 2025 at 8:52 AM