Browse our latest Computational and Systems Biology articles

Human cells decode dynamics Wnt signals using an anti-resonant filter that suppresses intermediate-frequency inputs and is capable of redirecting developmental fate outcomes, including germ-layer specification.

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of decision-making patterns across distinct task conditions.

Multi area RNN models fitted to in-vivo cortical activity predict behavioral changes induced by optogenetic perturbations, if biologically informed connectivity constraints on the optogenetically targeted inhibitory neurons are applied.

Targeted computational redesign of an IL-7 superkine with enhanced folding efficiency and receptor affinity demonstrates superior immune-stimulatory and antitumor activity over wild-type IL-7.

A simple statistical model captures the essential features of object motion in a large database of natural scenes, helping to shed light on the challenges posed to sensory and motor systems.

A new CRISPR-based approach for tuning gene expression up and down allowed identification of how other genes' expression responds to changes of transcription factors.

Machine learning models reveal that histone marks are predictive of gene expression across human cell types and highlight important nuances between natural control and the effects of CRISPR-Cas9-based epigenome editing.

A low-dimensional voice latent space derived from deep learning captures speaker-identity representations in the temporal voice areas and supports reconstruction of voices preserving identity information.