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"Bullying is a means for mediocre scientists to rise to the top. Some star academics reached their position because they are bullies, not in spite of it." - Excellent piece about bullying in academia (and really any other professional environment). nature.com/articles/s4156…

"Protein structure alignment by Reseek improves sensitivity to remote homologs" published in Bioinformatics academic.oup.com/bioinformatics…

research.csiro.au/iphd-opportuni…

CSIRO Industry PhD program: Prediction of molecular interactions with RNA using AI

Still available: CSIRO industry PhD project to work on Prediction of molecular interactions with RNA using AI for basic research and therapeutic discovery in collaboration with RNAfold.ai and CSIRO science.anu.edu.au/study/research…

SWARM (Single-molecule Workflow for Analysing RNA Modifications) detects pseudouridine, m6A, and m5C on individual molecules from direct RNA nanopore signals (in both chemistries RNA002 and RNA004) github.com/comprna/SWARM see more on poster P2-396 at #rna2025 #RNA25 #RNAmods

Don't miss AJ's talk (T-93) on dFORCE this afternoon in the RNA processing session (Ballroom A) #RNA2025 #RNA25

CSIRO Industry PhD position available in my group: Prediction of molecular interactions with RNA using AI research.csiro.au/iphd-opportuni… #RNA #molecularinteractions #AI #academicjobs

Free online event about CSIRO Industry PhD (iPhD) program. You will also hear from current iPhD students who will share their experiences and advice events.csiro.au/Events/2025/Ap…

🌟We are hiring! Seeking a postdoc to use molecular dynamics and AI to understand how ion channels are regulated by membrane lipids🌟 Join us at ourANU with amazing collaborators and great working conditions! Apply: tiny.cc/corry. Us: karri.anu.edu.au

🌟 Apply now for the EMBL Australia #PhD Course! This year's program includes two exciting workshops from Australian BioCommons: 💻 Machine Learning in the Life Sciences 📊 Mastering Data Visualisation Design 🔗 Applications close 27 July - don't miss out! bit.ly/4kljhsO

Our ex-zd compression is now published in Genome Research. ex-zd lossy mode can reduce 30-40% of the Oxford Nanopore signal data size, and the basecalling accuracy scatter is at a similar level to running the original data on two different GPUs - V100 vs A100. genome.cshlp.org/content/35/7/1…

For many of those who were asking on BLOW5 vs POD5 for nanopore signal data, here is a finally detailed benchmark we did: biorxiv.org/content/10.110… Summary: performance of BLOW5 is >= POD5 (from ~= to 100X, see below), with benefit of having ~3 dependencies instead of >50.