Axel Visel

@axelvisel.bsky.social

Genome Scientist. Studies how DNA makes humans, mice, plants, microbes. At Lawrence Berkeley National Lab and Joint Genome Institute. Views are my own.

Hi everyone, my name is Jack. I'm a SULI summer intern at Berkeley Lab. Over the next several weeks I’ll be creating posts sharing my experiences learning about cool research projects across the Biosciences Area. I hope you enjoy this series as I much as I enjoy making it!

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📢 Letters of Intent for our Large Scale call, part of our Community Science Program, are due April 9. Projects should leverage systems-based approaches to address biofuel and bioproducts production. 🖥️ 🧬 More info: https://jgi.doe.gov/work-with-us/proposals/community-science-program/large-scale

CSP Large Scale Call | Joint Genome Institute

The Community Science Program Large Scale Call is focused on genomic science projects that address sustainable biofuel and bioproducts production.

jgi.doe.gov

New research points to the oil-producing alga Auxenochlorella as a powerful platform for producing specialty oils, chemical feedstocks and industrial precursors—as well as to better enable the mining of critical minerals and materials. 🖥️🧬 @berkeleylab.lbl.gov @axelvisel.bsky.social @biosci.lbl.gov

Complete Genome of Oil-Rich Alga Reveals Ideal Platform for Bioengineering | Joint Genome Institute

Streamlined genome with precise gene targeting transforms oil-producing alga into a powerful platform for developing ​​bio-based industrial products.

jgi.doe.gov

Our FY25 Progress Report is now live! We broke our own record by sequencing more than 1Pb of data in a year—on top of serving 2,627 users w/active proposals, plus 17K researchers making use of our data. 🖥️ 🧬 🌱 🍄 🦠 🧪 Full report: https://jgi.doe.gov/user-science/science-stories/2025-progress-report

2025 Progress Report | Joint Genome Institute

Learn more about the JGI's 2025 accomplishments, including research and data output.

jgi.doe.gov

TF-MINDI is out! A new method to learn cis-regulatory codes through rich embeddings of TF binding sites. TF-MINDI decomposes motif neighbourhoods, and works downstream of any sequence-to-function deep learning model. We deeply study the enhancer code in human neural development, check out the thread

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Seppe De Winter@seppedewinter.bsky.social · 7mo ago

We are thrilled to share our new pre-print: “System-wide extraction of cis-regulatory rules from sequence-to-function models in human neural development”. S2F-deeplearning models can accurately encode enhancers, yet decoding these models into human-interpretable rules remains a major challenge.