Browse our latest Computational and Systems Biology articles

The person-specific adjusted HbA_1c addresses non-glycaemic variation in laboratory HbA_1c due to red blood cell lifespan differences, potentially providing a better marker to predict diabetes complications and guide glycaemic management.

Minimal modifications of common regulatory circuits can allow bacteria to learn from the past to better predict the future, on a physiological, rather than evolutionary, timescale.

The factors which drive and control disease progression can be inferred from mathematical models that integrate measures of immune responses, data from tissue sampling and markers of infection dynamics.

Invasive electrophysiological recording measures neuronal transmembrane current timescales across human cortex, which lengthens from sensory to association regions, follows variations in ion channel expressions, and alters with behavior and aging.

Cell assemblies can use environmental cues created by their own respiration, such as oxygen gradients, to collectively guide themselves to more favorable locations in a remarkably robust and long-lasting way.

Yeast cells can tune the modality of a nutrient response on physiological and evolutionary timescales by adapting the expression and sequence of a sensor protein.

Important nonlinear links between infection, inflammation, and disease severity were revealed using experimentally validated mathematical models.

Rare, virus-specific immune cells in human blood are automatically identified by machine learning algorithm T-REX and characterized for signature features needed for tracking and isolation.

ERK activation during induction of long-term synaptic plasticity is enhanced by synergistic interactions among signaling pathways mediated by the synaptically located GTPase-activating protein, and each pathway contributes to different ERK temporal dynamics.

Ubiquitous transcriptional factor-CBP/p300 interaction induces epigenetic and transcriptional bimodality, which can be utilized to tune mean gene expression and noise independently.