Proposed changes to the National Institutes of Health’s $48 billion budget would risk jobs, threaten state economies, and hamper progress toward prevention and treatment of diseases such as cancer.

In the 1970’s I was probably one of the last American high school students who was told that if you wanted to go to medical school, you should learn to speak German. This was because in the late 19th ...

We are delighted to share a recap of the YERUN Open Science Awards Ceremony which was just concluded! The event was a resounding success, bringing together YERUN members, esteemed guests, and stakehol...

Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent experimental and computational advances — from single-cell and spatial profiling to CRISPR genome editing and machine learning — have raised the exciting possibility of leveraging such strategies to prevent, diagnose and treat human diseases. However, adapting systems-inspired approaches to dissect human disease complexity is challenging, given that discrepancies between the biological features of human tissues and the experimental models typically used to probe function (which we term ‘translational distance’) can confound insight. Here we review how samples, measurements and analyses can be contextualized within overall multiscale human disease processes to mitigate data and representation gaps. We then examine ways to

Here we summarise some of the more interesting changes that have been introduced in R 4.5.0.