1/Unlocking the secrets of how the third form of life —archaea— makes energy, with potential applications for transitioning to a green economy. Published in Cell, led by scientists including Monash Biomedicine Discovery Institute's Chris Greening Jill Banfield Bob Leung More bit.ly/4c5KD1w

We want Monash University to be the place to be for microbiology in the post-metagenomics era. So much going on.

It’s a lonely job, leading a research group (professor, principal investigator, group leader – whatever you call it). You talk all day with everyone, but you’re mostly alone with the doubts and risks of the biggest decisions. Doesn’t have to be this way and I’d love to change it.

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects @BriefingBioinfo 1/ This review explores state-of-the-art deep learning methods for predicting the effects of non-coding genetic variants, highlighting their growing

Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures | Nature Methods - Genomics 2 Proteins (G2P) portal, linking 20,076,998 genetic variants to 42,413 protein sequences and 77,923 structures (58,027

Our global analyses find despite a decline in absolute PM2.5 concentrations, suburban and urban areas in very-high-HDI regions experienced a consistent increase in exposure inequality. sciencedirect.com/science/articl… Congrats Alven YU and co-authors!

How to write a grant? 1. Write it for the reviewer, not you, the applicant. 2. Communicate in stories. 3. Make your story cohesive—leave no puzzling gaps. 4. Make your story resonate to keep the reviewer reading. 5. Accept chance and noise in peer-review. pnas.org/doi/epub/10.10…

Self-iterative multiple instance learning enables the prediction of CD4+ T cell immunogenic epitopes 1. ImmuScope is an innovative deep-learning framework designed to predict CD4+ T cell immunogenic epitopes with high accuracy. It integrates multi-allelic and single-allelic data

Excited to share PoET-2, our next breakthrough in protein language modeling. It represents a fundamental shift in how AI learns from evolutionary sequences. 🧵 1/13

Two absolutely fantastic bioimage analysis papers out today offering exceptional, generalizable tools for segmentation--Cellpose3 and Segment Anything for Microscopy. (1/3)

Happy to announce our special issue on "Application of large language models in genome analysis", now live on Genome Biology. Honored to serve as a guest editor alongside Jiangning (John) Song! We welcome your manuscript submissions to this groundbreaking collection.biomedcentral.com/collections/CO…

📢Xiangliang Zhang and colleagues evaluate bias in AI-generated medical text, revealing disparities across race, sex, and age, and propose an optimization method to enhance fairness without compromising performance. nature.com/articles/s4358… 🔓rdcu.be/eiYzT