Melanie Weilert
mlweilert.bsky.social
Melanie Weilert
@mlweilert.bsky.social
bioinformatics, cats, deep learning, genomics, Zeitlinger Lab ((all views are mine alone))
Reposted by Melanie Weilert
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!
November 19, 2025 at 11:38 PM
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!
November 19, 2025 at 9:03 PM
Reposted by Melanie Weilert
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...
Evolution and core processes in gene expression
June 26–29, 2025 | Kansas City, Mo.
www.asbmb.org
May 7, 2025 at 1:57 AM
Reposted by Melanie Weilert
🚨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
April 23, 2025 at 8:43 PM
Reposted by Melanie Weilert
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.
PISA: a versatile interpretation tool for visualizing cis-regulatory rules in genomic data https://www.biorxiv.org/content/10.1101/2025.04.07.647613v1
April 8, 2025 at 1:31 PM
Reposted by Melanie Weilert
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
Reposted by Melanie Weilert
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
March 3, 2025 at 9:31 PM
Reposted by Melanie Weilert
This a great interdisciplinary gene expression meeting, where everyone is welcome. Please consider attending and submitting your abstract: www.asbmb.org/meetings-eve...
March 4, 2025 at 2:10 PM
Reposted by Melanie Weilert
Thermodynamic principles link in vitro transcription factor affinities to singlemolecule chromatin states in cells

www.biorxiv.org/content/10.1...
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...
www.biorxiv.org
January 30, 2025 at 5:12 PM
5 minutes on this platform and it's already clear leaving Twitter was a great call, glad to see everyone <3
January 29, 2025 at 12:35 AM