Melanie Weilert
@mlweilert.bsky.social
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📥 142
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bioinformatics, cats, deep learning, genomics, Zeitlinger Lab ((all views are mine alone))
reposted by
Melanie Weilert
Julia Zeitlinger
12 days ago
Very proud of our new paper! Great job @mweilert.bsky.social, our experimentalists and modeling collaborator Rosa Martinez-Corral. It was fun to see the story grow and get feedback from various experts. Thank you all!
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It’s been fun figuring out why some degenerate motifs matter while others don’t. Turns out there’s a whole syntax behind it, relying on cooperativity!
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12 days ago
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reposted by
Melanie Weilert
Julia Zeitlinger
7 months ago
Like regulatory genomics? Don’t miss this very fun meeting! May 7 is the deadline for early registration and abstract submission
www.asbmb.org/meetings-eve...
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Evolution and core processes in gene expression
June 26–29, 2025 | Kansas City, Mo.
https://www.asbmb.org/meetings-events/gene-expression-2025
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reposted by
Melanie Weilert
GenomeTDCC
7 months ago
🚨PRE-PRINT 🧪🧬🖥️👩🔬 Long-range massively parallel reporter assay reveals rules of distal enhancer-promoter interactions From Barak Cohen's lab at
@washu.bsky.social
Read the pre-print 👇
doi.org/10.1101/2025...
Learn more about the research from the Cohen lab:
bclab.wustl.edu
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reposted by
Melanie Weilert
Julia Zeitlinger
8 months ago
Our new preprint is out! Want to better visualize what your sequence-to-function profile learned? Here is PISA. It also comes in a new BPNet package, which can be used to train many genomics data sets, including MNase-seq data.
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reposted by
Melanie Weilert
Stein Aerts
8 months ago
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...
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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...
https://www.biorxiv.org/content/10.1101/2025.04.02.646812v1
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reposted by
Melanie Weilert
Stowers Institute
9 months ago
We're thrilled that Investigator
@juliazeitlinger.bsky.social
is co-chairing the 2025
@asbmb.bsky.social
meeting in
#KansasCity
, which will delve into the core processes of
#geneexpression
from
#developmental
and evolutionary perspectives. Read more:
bit.ly/41Czvqy
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reposted by
Melanie Weilert
Julia Zeitlinger
9 months ago
This a great interdisciplinary gene expression meeting, where everyone is welcome. Please consider attending and submitting your abstract:
www.asbmb.org/meetings-eve...
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reposted by
Melanie Weilert
Jacob Schreiber
10 months ago
Thermodynamic principles link in vitro transcription factor affinities to singlemolecule chromatin states in cells
www.biorxiv.org/content/10.1...
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Thermodynamic principles link in vitro transcription factor affinities to single-molecule chromatin states in cells
The molecular details governing transcription factor (TF) binding and the formation of accessible chromatin are not yet quantitatively understood - including how sequence context modulates affinity, h...
https://www.biorxiv.org/content/10.1101/2025.01.27.635162v2
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5 minutes on this platform and it's already clear leaving Twitter was a great call, glad to see everyone <3
10 months ago
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