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Reposted by Marcel Schulz

Lior Pachter @lpachter.bsky.social · Sep 5

In a new work with Joseph Rich and Conrad Oakes we tackle the problem of how to best organize alluvial plots. We formalize two optimization problems and develop a solution for them based on the neighbornet algorithm, implemented in the program wompwomp: github.com/pachterlab/w...

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Reposted by Marcel Schulz

loosolab @loosolab.bsky.social · Aug 28

🚀 Two exciting days of Computational Biology at the Cardio-Pulmonary Institute in Bad Nauheim @cpi-exstra.bsky.social ! 🔬 Workshop on single-cell analysis + the CPI repository data ressource; 💡 Hackathon together with the Schulz Lab @themarcelschulz.bsky.social
Collaboration, coding & discovery

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Reposted by Marcel Schulz

Cardio-Pulmonary Institute | CPI @cpi-exstra.bsky.social · Aug 4

🎉 To mark the fourth extension of the CPI, we celebrated our success at the @mpi-hlr.bsky.social 🥳 We are delighted about the renewed funding and would like to thank everyone who made this step possible! Read more in the latest issue of "Synapse": www.unimedizin-ffm.de/fileadmin/re...

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Reposted by Marcel Schulz

Elena Rivas @rivaselenarivas.bsky.social · Aug 2

we asked a simple question:
What does it take to learn the rules of RNA base pairing?

using standard deep-learning technics, got a simple answer:
don't need structures, nor alignments or many parameters
only a few RNA sequences and 21 parameters;
doi.org/10.1101/2025...

doi.org

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Reposted by Marcel Schulz

Nature Biotechnology @natbiotech.nature.com · Jul 25

A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function go.nature.com/4mc1SmQ

A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function - Nature Biotechnology

RNA-binding motifs in eukaryotic proteins are presented in a comprehensive resource.

go.nature.com

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Reposted by Marcel Schulz

Eric Topol @erictopol.bsky.social · Jul 25

Multi-omics with A.I. analytics demonstrates critical role of the gut microbiome and immune response and enables accurate diagnosis of ME/CFS, may also be applicable to Long Covid.
www.nature.com/articles/s41...
www.ft.com/content/9cdf...

AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome - Nature Medicine

Analysis of a deeply phenotyped, longitudinal cohort of 249 participants elucidates the network of concurrent molecular and macroscopic patterns related to insurgence and course of ME/CFS.

www.nature.com

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Reposted by Marcel Schulz

DjuranovicLab at Brown University RNA Center @djuranoviclab.bsky.social · Jul 25

Our collaboration with Tony Mustoe's lab us out today. MPRA libraries and possible cryptic splicing in MPRA reporters, or reporters in general. The additional novelty here is that such events are controlled or influenced by AU-rich sequences.

www.nature.com/articles/s41...

U-rich elements drive pervasive cryptic splicing in 3’ UTR massively parallel reporter assays - Nature Communications

Massively parallel reporter assays (MPRAs) are powerful technologies for measuring the impact of non-coding sequences on gene expression. Here, the authors demonstrate that MPRA reporters often underg...

www.nature.com

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Reposted by Marcel Schulz

Vikram Agarwal @vagar.bsky.social · Jul 25

Very excited that our most significant work, a collaboration w/ Dr. Can Cenik at UT Austin on translational gene regulation, was finally published in Nature Biotechnology in a dual set of studies:

Paper 1 -- an AI model trained to predict translation rates from mRNA sequences: rdcu.be/exN1l

Predicting the translation efficiency of messenger RNA in mammalian cells

Nature Biotechnology - A deep convolutional neural network model predicts the influence of the full-length mRNA sequence on translation efficiency.

url.de.m.mimecastprotect.com

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Reposted by Marcel Schulz

Anthony Mathelier @amathelier.bsky.social · Jul 24

And BIG thanks to #RegSys track organizers @abardet.bsky.social A. Emad J. Welch R. Gordan @xiuweizhang.bsky.social R. Beekman @martamele.bsky.social @anniquec.bsky.social @shaunmahony.bsky.social @ferhatay.bsky.social and co-chairs @alemedinarivera.bsky.social and @themarcelschulz.bsky.social

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Reposted by Marcel Schulz

Anthony Mathelier @amathelier.bsky.social · Jul 24

What a fantastic #ISMBECCB2025 conference it has been, with an outstanding #RegSys @iscb-regsys.bsky.social COSI track!

Thanks, everyone, for submitting, attending, presenting, and organizing @iscb.bsky.social @eccb-europe.bsky.social

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Reposted by Marcel Schulz

Mallory Freeberg @malloryfreeberg.bsky.social · Jul 23

🧬 New @emblebi.bsky.social service beta launched:
Perturbation Catalogue

🔎 Browse genetic perturbation datasets
🧠 Train models
🧬 Interpret variant function
🧭 Explore gene dependencies

Search, test APIs, suggest datasets, send feedback!
🔗 www.ebi.ac.uk/perturbation...

Funded by @opentargets.org

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Last talk at #regsys today is a keynote by Mafalda Dias about modelling sequence variation in Evolution with insights into diseases #ismbeccb2025

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Reposted by Marcel Schulz

Alejandra Medina-Rivera @alemedinarivera.bsky.social · Jul 23

First talk of the last session of RegSys day 1 at #ismb2025 is from Jacob Schreiber on how we read the book of DNA

Spoiler: regulation is key

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Laura Gunsalus talks about design of small native regulatory elements using #ML #ismbeccb2015 #regsys

Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Last talk in this #regsys session is Jishnu Das who talks about regulatory programs that determine B-cell fates #ismbeccb2025

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Tatevik Jalatyan will talk about a new pipeline for estimating cell cycle phase from single cell data #ismbeccb2025 #regsys

Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Surag Nair talks about a general framework to combine different paradigms of DL genome models #ismbeccb2025 #regsys

Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Vitalii Kleshchenikow about a biophysical model for learning gene regulation from single cell data #ismbeccb2025 #regsys @oliverstegle.bsky.social

Marcel Schulz @themarcelschulz.bsky.social · Jul 23

#regsys session is overflowing at #ismbeccb2025 consider to go to rooms 6 and 7 for video broadcast if full

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Laura Rumpf talks about the MetaFR pipeline to learn gene regulation models from unpaired and paired scATAC and scRNA data #ismbeccb2025 #regsys #schulzlab @dzhk.de @sfb1531.bsky.social

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Refreshed after lunch we start with Oluwatosin Oluwadare to introduce a new approach for single cell HiC analysis #ismbeccb2025 #regsys

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Last speaker before lunch is Christophe Vroland to talk about confounders in Rna-Dna interaction data analysis #regsys #ismbeccb2025

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Laura Hinojosa talks about TFs that regulate replication timing
#RegSys #ismbeccb2025 @ferhatay.bsky.social

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Many BPNet models will be made available also correct id is @damlaob.bsky.social

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Marcel Schulz @themarcelschulz.bsky.social · Jul 23

Next is
@damlaob to talk about putting new Deep learning models of TFs into #Jaspardb #RegSys #ismbeccb2025 @amathelier.bsky.social

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