Charles Danko

Resist, eggheads! Universities are not as weak as they have chosen to be. Opinion: It’s time for public resistance.

Absolutely outstanding op ed piece on the importance of US universities standing firm in this moment. Also covers the various tools at their disposal to do so.
arstechnica.com/culture/2025...

Genome-wide dynamic nascent transcript profiles reveal that most paused RNA polymerases terminate We present a simple model for analyzing and interpreting data from kinetic experiments that measure engaged RNA polymerase occupancy. The framework represents the densities of nascent transcripts with...

Our latest work indicates that termination of paused RNA polymerase is its most likely fate, while attempting to reconcile disparate estimates of relative rates and pause residency times from previous studies: www.biorxiv.org/content/10.1...

👇🎯 The public isn't going to understand this, unless the presidents of R1 universities around the country <loudly> & <collectively> get out into the public square & start explaining this & calling out the existential threat to the entire 🇺🇸 university system. The silence is deafening right now.

The admin plans to pick off universities 1-by-1. Instead, we have to come together. Universities need to stand together, fight in court, and take our case to the public by explaining the importance of what we do.

GDP forecast by Atlanta Fed.

Yikes. That Trump economy is really starting to shine.

Slava Ukraini! 🇺🇦

Accurate de novo transcription unit annotation from run-on and sequencing data Functional element annotations are critical tools used to provide insight into the molecular processes governing cell development, differentiation, and disease. Run-on and sequencing assays measure th...

Accurate de novo transcription unit annotation from run-on and sequencing data

@charlesdanko.bsky.social

www.biorxiv.org/content/10.1...

100%. All the more reason for us to start telling our story more widely. And to find professionals who know how to make it resonate with constituencies we don't know well.

This will be a long and expensive fight. There are lots of sympathetic people out there. But to win, we need to engage with folks who know how to tell our stories to a general audience. We need to work together to make the case for science clear to absolutely everyone in the US.

Universities need to band together, hire excellent public relations teams, advertising firms, lobbyists. We need to run advertisements that tell the audience how they benefit. Adds need to run everywhere, including and especially, Fox News.

Most importantly, we need to explain to the public why they benefit from what we do and how it impacts their lives. Make sure that absolutely everyone in the US knows about the economic impact, cures for children's diseases and all of the other benefits to society.

That just isn't true any more. And we need to catch up fast.

Frankly, Universities suck at the types of public outreach we need right now. We haven't built it because we haven't had to. The case for supporting science is just *so* strong from pretty much every perspective that it has enjoyed bipartisan support for decades.

My hot take: Universities and medical centers need to get *MUCH* better at outreach and explaining the benefits of funding independent research to the public.

Genomic Foundationless Models: Pretraining Does Not Promise Performance The success of Large Language Models has inspired the development of Genomic Foundation Models (GFMs) through similar pretraining techniques. However, the relationship between pretraining performance ...

www.biorxiv.org/content/10.1...

Another genomic FM benchmark 💀

I have noticed different fields can be a lot more cagey/ cutthroat about data. It's something I try to keep in mind when steering projects. I'd prefer to work in friendly, open communities.

Sorry to hear about this!

I will also add that since this positive experience, Adam He in my lab fairly routinely reaches out to members of Anshul's group. It really has sparked a larger collaboration that helps us a great deal.

I had a similar experience recently with @akispapantonis.bsky.social. We found each other's preprints on how Pol 2 impacts enhancer-promoter loop formation. We organized co-submission. Both papers were ultimately accepted and both have been well received by the community.

I agree 100% with all of this. It's how it *should* work in a friendly, collaborative community. People boost each other up, help out. The science that comes out is often better, and everyone gets credit in the end.

I wanted to write briefly about a very pleasant experience we recently had coordinating and collaborating closely on competing publications with 2 other teams. 1/

Q-rich activation domains: flexible ‘rulers’ for transcription start site selection? Recent findings broadened the function of RNA polymerase II (Pol II) proximal promoter motifs from quantitative regulators of transcription to important determinants of transcription start site (TSS) position. These motifs are recognized by transcription factors (TFs) that we propose to term ‘ruler’ TFs (rTFs), such as NRF1, NF-Y, YY1, ZNF143, BANP, and members of the SP, ETS, and CRE families, sharing as a common feature a glutamine-rich (Q-rich) effector domain also enriched in valine, isoleucine, and threonine (QVIT-rich). We propose that rTFs guide TSS location by constraining the position of the pre-initiation complex (PIC) during its promoter recognition phase through a specialized, and still enigmatic, class of activation domains.

We wrote an opinion article inspired by the recent exciting reports on the sequence determinants of TSS selection + old observations on TFs activation domains. More posts on this soon!

Q-rich activation domains: flexible ‘rulers’ for transcription start site selection?
www.cell.com/trends/genet...

Brief thread on our opinion article "Q-rich activation domains: flexible ‘rulers’ for transcription start site selection?". Transcription people are surely aware of the important reports on the DNA sequence determinants of start site (TSS) selection in the human genome that came out this year. 1/15

Training deep learning models on personalized genomic sequences improves variant effect prediction Sequence-to-function models have broad applications in interpreting the molecular impact of genetic variation, yet have been criticized for poor performance in this task. Here we show that training mo...

Latest from our lab: Training sequence-to-function models using matched genome sequence and functional data improves performance in variant interpretation tasks.

Congrats to Adam He and Nathan Palamuttam on getting this out.
www.biorxiv.org/content/10.1...

RNA polymerases reshape chromatin and coordinate transcription on individual fibers

www.biorxiv.org/content/10.1...

I just sent my congressman a strong letter supporting Ukraine aid. Please consider doing the same!

3D Enhancer–promoter networks provide predictive features for gene expression and coregulation in ... Here, the authors describe 3D hubs as regulatory subunits of gene expression in the three essential lineages of embryogenesis. They develop a computational model that can predict novel enhancers and t...

Beautiful work from Effie Apostolou' lab.
www.nature.com/articles/s41...

Important thread.

Let's say is clearly: $474K is what the modular budget cap would be if it kept pace with inflation over 25 years. 
 
If you're sticking to $250K these days, how much is that equivalent to in 1998 dollars?

About $132,000.