When signals cause transcription factor levels to fluctuate on the same time scale as their binding and unbinding from the DNA, different targets of the same regulator can exhibit highly distinct expression responses to a common signal.

Slowly-evolving ecological communities interacting via consumption of resources with imperfect efficiency, exhibit a dynamical steady state with continual turnover of biodiversity: a Red Queen phase without host–pathogen coevolution.

A systematic comparison of diverse cell packing models reveals shared mechanical rules that govern how tissues stiffen, yield, and reorganize—shedding light on the physical logic behind morphogenesis.

An experimentally tested model explains the paradoxical finding that increased gap-junction connectivity can suppress calcium synchronization to slow signals-while sparse networks synchronize through prolonged entrainment.

Dendritic nonlinearities allow neurons to store more, learn faster, and promote a sparse and robust wiring by increasing the number of silent synapses.

Under geometric constraints, ascidian embryos maximize information transmission to establish the neural cell fate by tuning surface contact areas, enabling distinct neural fates despite uniform signal levels.

Contrastive learning reveals generalizable rules of T cell receptor cospecificity, highlighting a key role for shape complementarity in immune recognition.

When signals cause transcription factor levels to fluctuate on the same time scale as their binding and unbinding from the DNA, different targets of the same regulator can exhibit highly distinct expression responses to a common signal.

Cohesion, residence time, and habitat-choice accuracy emerge as key metrics shaped by social interaction, revealing exploration–exploitation trade-offs in the collective foraging patterns of large egalitarian groups.

Slowly-evolving ecological communities interacting via consumption of resources with imperfect efficiency, exhibit a dynamical steady state with continual turnover of biodiversity: a Red Queen phase without host–pathogen coevolution.

Depleting vimentin compacts microtubule networks and speeds up microtubule motion, while inhibiting actomyosin activity expands the network and slows dynamics—revealing competing, independent roles in sculpting microtubule dynamics.

RNA bridges between charged regions on chromosome surfaces drive long-range attraction and clustering, revealing a condensate-like mechanism tunable by charge patterns.

Enzyme clustering boosts metabolic pathway flux and lowers toxic intermediates by self-assembling only where and when substrate is present, enabling an efficient and adaptive pathway processing.

Despite classical sign rule says noise correlations hurt coding, they can help, when correlations are strong and fine features matter, enhancing discriminability in complex neural codes.

This method adds sequence homology information to protein language models, improving amino acid prediction and enabling efficient, controlled sequence generation and motif scaffolding with minimal extra computation.

A scalable approximation of pseudo-perplexity from language models enables fast, accurate prediction of mutation effects on protein function and stability.

By tuning polarity–polarity interactions, this experiment-derived model unifies contact-interaction mechanisms across diverse cell types, explaining collision behavior of migrating cells.

Environmental fluctuations let biodiversity beat the resource count, with peak diversity at intermediate competition.

A proteome analysis study shows cyanobacteria regulate carbon metabolism and redox homeostasis via fast light-triggered protein changes and slower circadian regulation under changing light conditions.

Stress and group size steer social interactions in fish schools—small groups naturally approach criticality, while large groups need stress to reach it, facilitating rapid adaptation to perturbations.

Active bond remodeling enables collagen IV networks to have a range of responses to strain while maintaining their mechanical integrity.

Moment spectrum functions reveal complex displacement patterns in movements of free-ranging barn owls that traditional mean-squared displacement analyses fail to capture, reflecting age-specific behaviors and ecological constraints on movement.

The network architecture of a brain’s wiring differs from the network architecture of its stimulus evoked responses.

Using contrastive learning on noisy trajectories, this method builds coordinate-invariant maps that reveal dynamical regimes, pinpoint bifurcations, and reconstruct phase diagrams, no equations required.

The historical order in which mutations appear during evolution determine the evolutionary trajectory of gene regulatory networks and influence how developmental patterns change and diversify over time.

This model uses AlphaFold2-like architecture to perform flexible docking of small molecules into protein targets, predicting both structure and affinity.

Using manifold learning, this study shows that CryoSBI representations form smooth low-dimensional manifolds linked to molecular properties, and provide a workflow for interpreting cryo-EM heterogeneity and enhancing simulation-based inference.

When mice correctly detect visual targets, the primary visual cortex shows stronger scale-invariant structure than during passive or non-natural viewing.

By using information-theoretic quantities as cost functions, this study solves nonlinear stochastic control problems efficiently, enabling optimal strategies across a range of biological problems.

Using single-cell sequencing data, cell-cell interactions in ascidian embryonic development are identified, revealing collective gene expression patterns.

This review revisits how physical forces shape collective animal behavior, revealing how individual–environment coupling underlies group dynamics across taxa—from fish schools to ant rafts.

This review traces how ideas from statistical physics evolved into foundational models of neural computation, shaping modern AI and culminating in the 2024 Nobel Prize in Physics.

Living systems are defined by their active acquisition and use of information. This Roadmap surveys current research on life’s information processes and their importance for the search for life beyond Earth.