Correlation is not causation: defining and applying causality in biomedical research has posed challenges. This perspective attempts to connect the partly disparate fields of systems biology, causal reasoning and machine learning, to inform future approaches in systems biology and molecular medicine.

A proximity proteomics pipeline is developed for mapping subcellular proteomes and characterizing spatiotemporally resolved proximal interaction networks, ensuring improved throughput and reproducible quantification.

The study introduces µPhos, an accessible, plate-based workflow for low-input mass spectrometry-based phosphoproteomics. µPhos greatly facilitates high-dimensional experimental designs, as demonstrated by a 96-well drug response screen and analysis of small anatomical regions in the mouse brain.

Susceptibility to a mucosal pathogen is both microbiome- and diet-dependent, with mucin specialist Akkermansia muciniphila increasing susceptibility on a fiber-free diet, whereas a fiber-rich diet allows the same commensal to confer resistance.

Several approaches have been designed to tackle the size and inherent noise of single-cell genomics data. This Review discusses the metacell concept, provides recommendations on when and how to use them and includes a tutorial and an integrated pipeline for building and analyzing metacells.

Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated.

This Review discusses recent insights into the emergence and stability of coexistence in microbial communities.

A structural proteomics approach for identifying candidate interactors of any protein within a complex lysate is presented. It is applied to identify conformation-specific interactors of Rab GTPases and of the monomeric and fibrillar forms of the disease-associated protein alpha-synuclein.