A new data analysis tool provides a concise way of visualizing neural data that summarizes all the relevant features of the population response in a single figure.

Computational modeling of the brain’s navigation system reveals that place cells can drive the formation of hexagonal patterns experimentally observed in grid cells activity.

The development of the electrical phenotype of neurons can be precisely quantified and dissected using a combination of multi-variate statistical analyses and a systematic electrophysiological characterization of electrical properties.

A tutorial and open-source software to aid in reproducible disease pattern detection using principal component analysis.

HS-AFM and Principal Component Analysis provide experimental evidence to substantiate the 'proof of principle' regarding the flexible helical twists of actin filaments that regulate the functions of actin-binding proteins.

The variability of the pupil–fMRI relationship was characterized through a combination of clustering and prediction methods, which revealed brain state-specific subcortical and neuromodulatory activation patterns reflected in pupil dynamics.

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

Applied and computational results show how dimensionality reduction approaches can help in grouping correlated genetic variant-exposure associations and improve causal inference in the Mendelian randomisation framework.