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Xi Fu

@fuxialexander.bsky.social
122 followers 452 following 28 posts

Transcription regulation; deep learning; (bad) developer

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Reposted by Xi Fu
David A Knowles @davidaknowles.bsky.social · 03/07/2025
New work from the lab trying to wrap our heads around the massive complexity of the human transcriptome revealed by long-read RNA-seq! Fun collab with Gloria Sheynkman. www.biorxiv.org/content/10.1...
biorxiv.org
Perplexity as a Metric for Isoform Diversity in the Human Transcriptome
Long-read sequencing (LRS) has revealed a far greater diversity of RNA isoforms than earlier technologies, increasing the critical need to determine which, and how many, isoforms per gene are biologic...
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Reposted by Xi Fu
Chao Hou @chaohou.bsky.social · 17/04/2025
We have updated our protein lanuage model trained on structure dynamics. Our new models show significant better zero-shot performance on mutation effects of designed and viral proteins compared to ESM2. check the new preprint here: www.biorxiv.org/content/10.1...
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Sara Mostafavi @saramostafavi.bsky.social · 16/04/2025
Some encouraging news for cross-gene generalization of allele effects in S2F models. www.biorxiv.org/content/10.1...
biorxiv.org
Deep genomic models of allele-specific measurements
Allele-specific quantification of sequencing data, such as gene expression, allows for a causal investigation of how DNA sequence variations influence cis gene regulation. Current methods for analyzin...
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Reposted by Xi Fu
Nature Biotechnology @natbiotech.nature.com · 03/04/2025
An engineered Cas12a enables higher-order combinatorial functional genomic screens using CRISPR interference go.nature.com/3UTnSXM rdcu.be/ef95k
go.nature.com
Engineered CRISPR-Cas12a for higher-order combinatorial chromatin perturbations - Nature Biotechnology
An engineered Cas12a enables higher-order combinatorial functional genomic screens using CRISPR interference.
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zhoujt.bsky.social @zhoujt.bsky.social · 25/03/2025
1/10 Excited to share our latest - the first whole-body map of both DNA methylation and 3D genome at single-cell resolution.
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Xi Fu @fuxialexander.bsky.social · 21/03/2025
Biorxiv seems to be really slow nowadays. Is it just me? Curious whether it's due to some infra change or there are some AI Agents crawling the data...
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Reposted by Xi Fu
Columbia University's Zuckerman Institute @zuckermanbrain.bsky.social · 17/03/2025
For decades, government funding “has positioned the United States as a global leader” in science, says scientist Tom Maniatis of @zuckermanbrain.bsky.social and the New York Genome Center. He highlights how a new #NIH policy cutting money for research “jeopardizes” this, in Cell tinyurl.com/ubw6uphe
We must act swiftly and decisively to safeguard the future of science in the US - Tom Maniatis, PhD
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Tuuli Lappalainen @tuuliel.bsky.social · 06/03/2025
Can someone send this to the NIH Director nominee who said yesterday under oath that he doesn’t know where the indirects go.
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Reposted by Xi Fu
Carolyn Ibberson @cbibberson.bsky.social · 22/02/2025
We are crowd sourcing reductions in graduate admissions and hiring freezes across biomedical research and higher ed in response to pauses in NIH funding and EO’s. If you have information if you could add to this spreadsheet, it would be greatly appreciated!: docs.google.com/spreadsheets...
docs.google.com
Graduate Reductions Across Biomedical Sciences (2025)
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Tuuli Lappalainen @tuuliel.bsky.social · 12/02/2025
This is very cool work (where I was fortunate to play a small part), providing creative and crucial solutions for secure and federated eQTL mapping. Bigger functional genetic studies with less administrative and legal hassle! 💪
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Jacob Schreiber @jmschreiber91.bsky.social · 09/02/2025
Combinatorial mapping of E3 ubiquitin ligases to their target substrates www.cell.com/molecular-ce...
cell.com
Combinatorial mapping of E3 ubiquitin ligases to their target substrates
The substrate(s) of most E3 ubiquitin ligases remain unknown. Suiter et al. present COMET, a combinatorial framework for identifying proteolytic E3-substrate relationships at scale. Deep-learning-base...
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Reposted by Xi Fu
Romain Koszul @rkoszul.bsky.social · 07/02/2025
Deep learning models (@chromozz.bsky.social) trained only on yeast chromosomes predict nucleosome positioning, RNA Poll II and cohesin tracks along foreign DNA, based on the sequence alone. This implies that the behavior of any DNA in a host cell follows deterministic sequence-based rules.
CNN predict nucleosome positions, and RNA Pol II and cohesin deposition
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Reposted by Xi Fu
Peter Koo @pkoo562.bsky.social · 05/02/2025
[SAVE THE DATE] MLCB 2025 is happening Sept 10-11 at the NY Genome Center in NYC! Attend the premier conference at the intersection of ML & Bio, share your research and make lasting connections! Submission deadline: June 1 More details: mlcb.github.io Help spread the word—please RT! #MLCB2025
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Leopold Parts @leopoldparts.bsky.social · 31/01/2025
Lars Steinmetz and @seczmarta.bsky.social put together a wonderful perspective on these two studies. www.science.org/doi/10.1126/...
science.org
Genome recombination on demand
Large genome rearrangements in mammalian cells can be generated at scale
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Reposted by Xi Fu
Eric Topol @erictopol.bsky.social · 29/01/2025
The "kitchen sink" of omics to solve the basis for an undiagnosed disease: long read genome , transcriptome, methytome, epigenome, all synchronized (a first) www.nature.com/articles/s41...
nature.com
Synchronized long-read genome, methylome, epigenome and transcriptome profiling resolve a Mendelian condition - Nature Genetics
Simultaneous profiling of the genome, methylome, epigenome and transcriptome using single-molecule chromatin fiber sequencing and multiplexed arrays isoform sequencing identifies the genetic and molec...
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Yan Hu @yanhu97.bsky.social · 23/01/2025
Super excited to share our new study from the @jbuenrostro.bsky.social Lab in @nature.com! We developed a computational method for tracking transcription factor and nucleosome binding using single-cell ATAC-seq and deep learning. Paper: www.nature.com/articles/s41...
nature.com
Multiscale footprints reveal the organization of cis-regulatory elements - Nature
We developed PRINT, a computational method that identifies footprints of DNA–protein interactions from bulk and single-cell chromatin accessibility data across multiple scales of protein size.
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Xi Fu @fuxialexander.bsky.social · 16/01/2025
The most senior cell typing expert should and always have been the evolution
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Anshul Kundaje @anshulkundaje.bsky.social · 13/01/2025
@anusri.bsky.social first author & developer of ChromBPNet is looking for opportunities in industry in ML for bio/genomics. She is an excellent rigorous scientist (as u can see from the paper). Very strongly recommend her. Plz reach out to her if u have openings. Plz forward.
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Reposted by Xi Fu
Centre de Regulació Genòmica (CRG) @crg.eu · 08/01/2025
The human genome encodes more than 20,000 proteins. Missense variants in nearly 5,000 of these proteins cause Mendelian diseases. Most variants compatible with life are likely present in someone currently alive. The study marks an important step in understanding the functional consequences.
nature.com
Site-saturation mutagenesis of 500 human protein domains - Nature
Large-scale experimental analysis of Human Domainome 1, a library containing more than 500,000 missense mutation variants across more than 500 human protein domains, reveals that 60% of pathogenic mis...
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Xi Fu @fuxialexander.bsky.social · 08/01/2025
GET is finally published! - Paper: t.ly/iQct_ (new validations, dry and wet) - Model: t.ly/4jnUI (new tutorial on PBMC 10x Multiome data, and yes you can even fine-tune it on a Macbook) - Analysis package: t.ly/OqLAL - Demo: t.ly/rbFQB - Docker: t.ly/86n_i
t.ly
A foundation model of transcription across human cell types - Nature
A foundation model learns transcriptional regulatory syntax from chromatin accessibility and sequence data across a range of cell types to predict gene expression and transcription factor interactions...
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Anshul Kundaje @anshulkundaje.bsky.social · 25/12/2024
Our ChromBPNet preprint out! www.biorxiv.org/content/10.1... Huge congrats to Anusri! This was quite a slog (for both of us) but we r very proud of this one! It is a long read but worth it IMHO. Methods r in the supp. materials. Bluetorial coming soon below 1/
biorxiv.org
ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants
Despite extensive mapping of cis-regulatory elements (cREs) across cellular contexts with chromatin accessibility assays, the sequence syntax and genetic variants that regulate transcription factor (T...
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Reposted by Xi Fu
Jeff Spence @jeffspence.github.io · 17/12/2024
What do GWAS and rare variant burden tests discover, and why? Do these studies find the most IMPORTANT genes? If not, how DO they rank genes? Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬) www.biorxiv.org/content/10.1...
biorxiv.org
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies
Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes. Although these methods are conceptually similar, we show by anal...
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