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By applying advanced multivariate methods, the researchers were able to identify common genetic factors and explore their biological and evolutionary significance.

Their current focus is on developing innovative segmentation and clustering techniques for multivariate time series data tailored to uncover more granular patterns and handle the challenges posed by AID data.

Researchers found that certain cell-type distributions align with specific networks in the brain's cortex, both at the level of individual cell types and multivariate cellular profiles, or fingerprints.

Furthermore, they conducted a continuous observation of renal vascular changes in an animal model induced with renal failure, performing multivariate analysis using hemodynamic and vascular morphological indicators.

Key to the experiment were algorithms called multivariate pattern decoders, which could predict which image a participant was viewing at a given time based on their brain signals.