Data acquisition (sometimes), standards, and expert curation (often) remain major bottlenecks. Applying AI earlier in the pipeline could help, but trust in the reliability of current models is still limited.
The non-profit sector is showing increasingly sophisticated AI applications, though imho it’s still not fully leveraging its accumulated data and expertise.
But the real flavor comes from the cooks - their domain expertise and data/coding/stats/ML-AI wizardry.
Startups and established biopharma are doubling down on proprietary or federated client data as their “secret sauce.”
Major players like AWS, Microsoft, and NVIDIA are building increasingly comprehensive ecosystems for model access, agent orchestration, and beyond.
Industry had a strong presence, highlighting how AI is reshaping bioinformatics, drug design, and even broader research and software development.
#ABACBS2025 is in full swing! Before I share broader updates, here’s a quick look at one of the satellite events: the Symposium on Bioinformatics and Engineered Intelligence 👇
Holy 🐮, TIL that Nixtla has R version - nixtlar!
nixtla.github.io/nixtlar/inde...
#rstats #machinelearning #timeseries
👋
📣 Calling experienced binifies & biostatisticians
⏰ Just under a week left to apply!
Applications Close Monday 19th February 2024, 11:00 pm AEDT.
We're hiring!
Cotton bioinformatics/biostatistics
3 year position
jobs.csiro.au/job/Canberra...
🧬 Opening for a postdoc in our vibrant team at NCMM, University of Oslo, to generate deep learning models to enhance JASPAR & UniBind, boosting gene regulation research. The project is in collab with @anshulkundaje.bsky.social and @wywywa.bsky.social. Plz share.
www.jobbnorge.no/en/available...
Screenshot from the linked webpage
Giving Tuesday Appeal: Bioinformatics for Ukraine
Empowering Ukraine’s Bioinformatics community through education and collaboration
www.huber.embl.de/group/posts/...
bioinformaticsforukraine.com
