Structure-based alignment of TRP channels enables comparison of structural changes, ion permeation pathways and ligand-binding sites and reveals over-representation of structures that represent non-conducting states.

A new machine-learning toolbox unveils coevolutionary protein motifs related to structure, function, and phylogeny from sequence information only.

Alternative conformations of membrane protein structures can be predicted to high accuracy with AlphaFold2 by reducing the depth of the multiple sequence alignments used for modeling.

A novel methodological strategy based on machine learning has been developed to study brain evolution across species.

A landmark-based cross-modality alignment method robust to variation in landmark sets is applied to annotate an EM time series of Caenorhabditis elegans embryonic development as a community resource.

Wing transparency in mimetic butterflies and moths is achieved by an unexpected diversity of structural features, and both structures and light transmission properties of wings are under selection for convergence.

During learning, human neural codes for experienced reward probability map onto the same mental number line for symbolic numbers.

Joint sequence, structure, and phylogenetic analyses identify highly conserved features in transmembrane domains of transient receptor potential (TRP) ion channel proteins that offer a novel explanation for how TRPs could integrate stimuli into cellular signals.

The glideosome-associated connector protein transitions between open and closed states, and this regulates its assembly and function during apicomplexan parasite motility.

The prolactin receptor, Janus kinase 2, and PI(4,5)P₂ form a co-structure with the membrane resulting in orientations with different accessibility fixing the disordered juxtamembrane domain of the receptor in an extended structure.