Browse our latest Computational and Systems Biology articles

Evolutionary graph theory solves the longstanding puzzle of why diverse infectious diseases and cancers show similar (approximately lognormal) distributions of their incubation periods.

T2N, a novel interface between Matlab, TREES toolbox and NEURON, was used to generate compartmental models that reproduce the electrophysiology of dentate granule cells over a multitude of species, experimental conditions and developmental stages.

A new mathematical approach can infer higher order genetic interactions from pairwise fitness comparisons between genotypes.

The motor protein kinesin utilizes its fuel molecule by active and concerted motions of its subdomains, while it rapidly interacts with the microtubule track by forming a wet and dynamic interface.

A novel method predicts cancer and immune cell types from bulk tumor gene expression data with the ability to consider uncharacterized and possibly highly variable cell types, which is validated in human genome.

What can artificial intelligence learn from neuroscience, and vice versa?.

A multi-compartment spiking neural network model demonstrates that biologically feasible deep learning can be achieved if sensory inputs and higher-order feedback are received by different dendritic compartments.

Single-molecule measurement of conformational dynamics using a genetically encoded fluorescent probe suggests that the selectivity filter region of TRPV1 channels undergoes dynamic motion during agonist activation.

Computational modeling and theoretical analysis reveal how disordered linkers determine whether linear multivalent proteins undergo gelation with or without phase separation.

Conventional annotations of coding sequences have missed thousands of short open-reading frames encoding proteins that are conserved and with specific functions.