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.

WaveMAP is a novel approach that combines nonlinear dimensionality reduction with graph clustering on extracellular waveforms to reveal previously obscured cell type diversity in monkey cortex.

Analysis of protein–protein encounter complexes shows that proteins associate along preferred pathways, similar to the sliding of a protein along DNA.

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.

Dimensionality reduction techniques reveal how the organization of neurotransmitter receptor and transporter co-expression in the human brain may bridge the gap between brain structure and function.

A data-reduced neuro-behavioral geometry in psychosis spectrum disorders mapped symptoms stably on to distinct functional brain regions and offers a framework for informing personalized treatment selection decisions.

Tetrode recordings show that the amplitude of gamma oscillations encodes for information on contextual odorant identity when observed at the peak phase of the theta oscillation in the olfactory bulb.

Ligands with different efficacy profiles shift the free energy landscape of the beta2 adrenergic receptor activation and stabilize diverse active-like states via the switch of microswitches lining an allosteric pathway.

A novel methodological framework for cross-frequency coupling and spike-field coherence in multichannel (LFP, EEG, MEG) electrophysiology data reveals new manifestations of coupling dynamics.

A decoding-based, state-space reconstruction reveals that neurons in macaque IT cortex change the structure of their collective attractor dynamics depending on task contexts.