Browse our latest Computational and Systems Biology articles

Ants employ a new kind of trail to resolve group-level navigational difficulties in scenarios where the information available to individuals does not suffice.

Six computationally designed and in vitro optimized protein inhibitors serve as molecular probes to reveal BCL2 profiles of different human cancers.

Quantitative dissection of the roles of chaperone binding and phosphorylation in regulating heat shock factor 1 leads to a predictive model of the dynamics of the yeast heat shock response.

The genetic background of a cancer cell and the chromatin organization of the tissue-of-origin impact the amount, length and position of somatic copy number alterations in cancer.

Theoretical models and experimental results reveal how the optimal integration of gravity cues fine tunes movement kinematics so that motor effort is minimized in the ubiquitous gravity field.

Analysis of crawling Drosophila larva and agent based simulations suggest that an intrinsic rhythm rather than distinct actions underlie taxis behaviour, providing a core mechanism on which both sensory and memory pathways can converge.

Extensive benchmarking reveals that errors made when manually building models into near-atomic-resolution cryoEM density may automatically be corrected using an improved Rosetta-based structure refinement method.

A machine-learning approach is used to predict 1.35 million interactions for 85% of the human proteome.

A selective reuptake inhibitor shows a beneficial effect in healthy humans during an effort-benefit tradeoff task, mediated at the computational level by a specific alleviation of effort cost.