Mohammad Paktiawal died in ICE custody. He fought with our troops in Afghanistan. He was not here illegally or a criminal. He worked & had a family. There was no reason for his detention. This ongoing inhumanity is a national shame. Powerful @BillKristol:
https://t.co/vsjELCxUNk
[Reminder] MLCB 2026 submissions are open!
Deadline: July 1 AOE
Keynote speakers: @DrAnneCarpenter (Purdue), Christina Leslie (MSKCC), @ZhongingAlong (Princeton), and @BrennerMichael (Harvard/Google)
Meeting: Nov 16–17 at NY Genome Center in NYC
https://t.co/aBGJ9Q5WQo
1/ We built the Genomics × AI blog so the genomics + ML community can share work fast and actually discuss it — incremental results, negative results, tutorials — without waiting on a publisher. Posts are live, more landing over the coming weeks: https://t.co/a4YY6avrda
Plenty of excitement about DIY genome sequencing, genetics & AI for Bio. But its going to take decades to decipher the genetic & molecular basis of diseases. Requires increasing, not gutting NIH funding of academic research (expts, computational, clinical) to get to the answers.
@chiragjp Congratulations! Inspiring to see you guys continuing to chart new waters in the study of the Exposome! Always inspired in how you have developed usable tools beyond just publication.
We built open tools so you can explore it yourself: 📦 R package nhanespewas → https://t.co/MKUGxJ06Wn… 🗂️ Browsable Phenome-Exposome Atlas (all 120k+ associations): https://t.co/B2FB0LIyOV 📓 Quickstart + ExWAS tutorial notebooks 📚 And a course/tutorial walking through the methods end to end:
https://t.co/4s7nrlU3g2
Paper: https://t.co/AHtQA4jZjF
Thank you to the @NIH_NIEHS @NIDDKgov and @NIHAging for funding support!
The next frontier: advancing #exposomics to understanding biology of disease. Causal attribution: where the heck do the exposures came from and how do they change from birth to death? But, not least, understanding how they matter to the health of the individual with the tools of AI and continuous monitoring. 🚀
Our manuscript for parameter-efficient fine-tuning of Borzoi is now out in Genome Biology:
https://t.co/yGoTQnj0ui
We’ve also included transfer tutorials for
- hg38: https://t.co/igfGPKSMcb
- mm10: https://t.co/kBgDFTkELU
Happy to hear your feedback!
Quanta always has very interesting and in-depth articles about the latest breakthroughs in science. I especially enjoyed this one on how neural networks are being used in fluid dynamics research.
Yongji Wang, a researcher at Google Deepmind, helped develop physics-informed neural networks that can spot potential “unstable” singularities in fluid equations, a long-sought goal in mathematical physics. https://t.co/xL0SxAN9Bz