Browse our latest Computational and Systems Biology articles

Two theoretical studies reveal how networks of neurons may behave during reward-based learning.

A biologically plausible learning rule allows recurrent neural networks to learn nontrivial tasks, using only sparse, delayed rewards, and the neural dynamics of trained networks exhibit complex dynamics observed in animal frontal cortices.

Motor neurons adjust their sensitivity to direction of movement in a manner analogous to how neurons in the visual system adjust their sensitivity to light.

A synthetic quadrastable gene network provides a synthetic biology framework to study cell fate determination.

Gene function can be revealed based on characteristic phenotypes using a Cell Painting microscopy assay.

A combination of single-cell techniques and computational analysis enables the simultaneous discovery of cell states, lineage relationships and the genes that control developmental decisions.

A computational model reveals how response properties of category-selective regions in the visual cortex reflect both bottom-up stimulus-driven signals and top-down attentional signals from the parietal cortex.

Mammalian germ layer differentiation is characterized by transitions through discrete cell states, which are transcriptionally as well as functionally distinct.

Sparse patterns in gene expression allow simultaneous discovery of cell states, lineage relationships and key genes controlling developmental decisions.

Cognate site identification uncovers the impact of combinatorial dimerization in specifying new DNA binding sites for human bZIP transcription factors and comprehensive specificity landscapes predict the impact of SNPs on bZIP binding at previously unannotated regulatory loci.