Browse our latest Computational and Systems Biology articles

A new way of measuring sociality in human and animal contact networks reveals the link between social behavior, population density, and disease transmission.

Emergent property inference, a novel machine learning methodology, learns distributions of neural circuit model parameters that produce computational properties and provides novel scientific insight through the quantification of the rich parametric structure it captures.

Computational methods reveal how mutations affect the conformational landscape of the kinase domain of EGFR resulting in abnormal signaling and provide a structural framework for ongoing drug discovery efforts on mutant-specific EGFR inhibition.

A structure-based model of the chromosomal cohesin complex, accompanied by molecular-mechanistic simulations, explains cohesin's key role in topologically entrapping DNA, as well as its ability to alternatively extrude DNA loops.

DNA loops can be formed by a mechanism in which the cohesin complex pulls DNA strands through its ring structure using biased Brownian motion.

The fast spreading of neural activity across the brain has a complex structure, imposed by the white-matter bundles.

Mice exploring a labyrinth freely for the first time learn a complex action sequence after a handful of rewards, exhibiting a learning rate 1000-fold higher than in commonly-used paradigms.

A very large number of place-field maps can be robustly learned by association of external cues with the grid-driven response, however plasticity in the grid-cell inputs renders the place-cell responses volatile.

The mechanism triggering HBV membrane fusion involves ERp57, a cellular protein disulfide isomerase, and ultimately leads to the exposition of a fusion peptide that was identified in the pre-S1 determinant.

A deep learning network can classify cardiac myocytes into drug-free and drugged categories and predict the impact of electrophysiological perturbation across the continuum of aging.