Browse our latest Computational and Systems Biology articles

Modeling the dynamics of immunological synapses informs pharmacodynamics and treatment resistance to bispecific T cell engagers.

Proteins locked into the immature HIV lattice can exploit its incomplete structure to form the essential protease dimer needed for viral maturation.

To isolate and study proprioception, hierarchical deep neural networks paired with biomechanical models provide a normative approach to test the role of task effects on neural representations, such as the emergence of kinematic tuning and higher-level abstractions of actions.

The regulation of gene expression can be either binary (on/off digital regulation) or graded (analog regulation) and these fundamentally different regulatory modes can be integrated to control the expression of the same gene.

Investigating microbial communities in a spatial environment in silico suggests that spatial structure promotes higher coexistence by allowing spatial self-organization, but can hinder coexistence by weakening interactions mediated through diffusible metabolites.

Among European children, shorter telomere length and older DNA methylation age relative to chronological age were associated with poorer behaviors, while older age, as predicted by a novel immunometabolic clock relative to chronological age, was associated with greater cognitive maturity.

Mathematical methods reveal common underlying principles in diverse models of intracellular actin waves.

Local disinhibition provides a biologically plausible mechanism for flexible top-down control of network states that integrates normalized value coding, winner-take-all choice, and persistent activity in a single circuit of decision-making.

Model identification of neural encoding is an accessible system for the analysis of neural data that allows identifying and characterizing arbitrary relationships between neural activity and task-related variables such as behavior, stimuli, or internal states.