Tomas Bruna
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tomasbruna.bsky.social
Tomas Bruna
@tomasbruna.bsky.social
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Genome Data Scientist @ DOE Joint Genome Institute
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Reposted by Tomas Bruna
katharinahoff.bsky.social
With help of international colleagues at @jgi.doe.gov, @oregonstate.edu, and @stockholm-uni.bsky.social, we are relasing new parameters for Tiberius. Thx to Lars Gabriel, @tomasbruna.bsky.social, Samuel Talbot, @chriswheat.bsky.social, @masta.bsky.social - and many others. github.com/Gaius-August...
Release v1.1.7 · Gaius-Augustus/Tiberius
⚠️ New Models available: Diatoms Eudicotyledons Lepidoptera Monocotyledonae Mucoromycota Saccharomycota Sordariomycota Several bugfixes.
github.com
October 24, 2025 at 6:37 PM
tomasbruna.bsky.social
Big thanks to @axelvisel.bsky.social for sharing! For full consideration, please apply by September 2.
axelvisel.bsky.social Axel Visel @axelvisel.bsky.social · Aug 21
Postdoc opportunity with @tomasbruna.bsky.social here at @jgi.doe.gov @berkeleylab.lbl.gov:

Develop, benchmark, and apply Plant Genomic Language Models (gLMs) 🌿🧬💻

jobs.lbl.gov/jobs/computa...

#AI #PlantGenomics #gLMs #Postdoc
Graphic announcing a Computational Postdoctoral Fellow position. Text: Computational Postdoctoral Fellow – Plant Genomic Language Models (gLMs). JGI is seeking a Computational Postdoctoral Fellow to join a funded project at Berkeley Lab’s Joint Genome Institute applying genomic language models (gLMs) to unlock new biological insights in plants. Join one of the world’s leading genomics facilities to pioneer AI applications in plant biology, with access to cutting-edge computational resources and diverse genomic datasets. This project will focus on developing and exploring applications of gLMs to plant genomes, from identifying novel regulatory elements to revealing evolutionary patterns across species, with particular interest in cross-species and data-limited scenarios. In this role, you will design tasks and datasets to test and extend gLM capabilities, apply models to generate new biological hypotheses, and share findings through high-impact publications and presentations.
August 21, 2025 at 12:13 AM
Reposted by Tomas Bruna
jotlovell.bsky.social
Determining presence-absence variation (PAV) across reference genomes is a major goal of pangenome analysis. It turns out that A LOT of gene PAV is due to methodological artifacts.

We explore the causes of this in soybean and cotton datasets in our recent preprint: www.biorxiv.org/content/10.1...
pangenome 'expansion' curves for cotton and soybean
August 18, 2025 at 4:51 PM