Hannah Dickmänken
@hannahdckmnkn.bsky.social
My favorite ice cream flavors are science & feminism. PhD candidate at VIB.AI in Stein Aerts lab 🪰 - she/her
Pinned
Evaluating single-cell ATAC-seq atlasing technologies using sequence-to-function modeling - Nature Communications
Generating high-quality training data for machine learning is costly. Here, authors include sequence-to-function modeling in benchmarking of custom and commercial droplet-based scATAC platforms, and r...
www.nature.com
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)
(details below)
Reposted by Hannah Dickmänken
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.
January 15, 2026 at 11:57 AM
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.
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)
(details below)
Evaluating single-cell ATAC-seq atlasing technologies using sequence-to-function modeling - Nature Communications
Generating high-quality training data for machine learning is costly. Here, authors include sequence-to-function modeling in benchmarking of custom and commercial droplet-based scATAC platforms, and r...
www.nature.com
January 29, 2026 at 2:08 PM
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)
(details below)
Reposted by Hannah Dickmänken
🚀 Proudly introducing the VIB-KU Leuven Center For Neuroscience, a merger of the two former VIB research centers VIB-KU Leuven Center for Brain & Disease Research and Neuro-Electronics Research Flanders (NERF)! Our new motto: Bold Science, Real Impact.
www.youtube.com/watch?v=uhaq...
www.youtube.com/watch?v=uhaq...
VIB-KU Leuven Center for Neuroscience
YouTube video by VIB-KU Leuven Center for Neuroscience
www.youtube.com
January 27, 2026 at 3:33 PM
🚀 Proudly introducing the VIB-KU Leuven Center For Neuroscience, a merger of the two former VIB research centers VIB-KU Leuven Center for Brain & Disease Research and Neuro-Electronics Research Flanders (NERF)! Our new motto: Bold Science, Real Impact.
www.youtube.com/watch?v=uhaq...
www.youtube.com/watch?v=uhaq...
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...
www.nature.com/articles/s41...
September 24, 2025 at 3:12 PM
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...
www.nature.com/articles/s41...
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
The FlyBase situation has made the national news www.nbcnews.com/science/scie...
Trump's Harvard cuts threaten a giant in biomedical research: A database about the tiny fruit fly
This spring, the Trump administration rescinded a grant that maintained FlyBase, a pillar of global basic research, as part of its broader $2.2 billion funding cuts at Harvard.
www.nbcnews.com
September 16, 2025 at 1:08 PM
The FlyBase situation has made the national news www.nbcnews.com/science/scie...
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
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...
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...
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
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...
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...
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!
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
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!
Congrats to @niklaskemp.bsky.social & @seppedewinter.bsky.social & all the others working on this super cool project!
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...
www.biorxiv.org/content/10.1...
April 4, 2025 at 8:52 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...
www.biorxiv.org/content/10.1...