This important study, which tackles the challenge of analyzing genome integrity and instability in unicellular pathogens by introducing a novel single-cell genomics approach, presents compelling ...

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and ...

Multi-electrode arrays (MEAs) provide a noninvasive interface with sub-millisecond temporal resolution and long-term, multi-site recordings, enabling mechanistic investigations of in vitro human brain ...

A sketch of the whole methodology for the continuous monitoring of the organoid synaptic activity through the analysis of neural activity from hFOs using MEA and a GDN model. Neural signals are ...

Public trust in the media and in data has been undercut by information overload, relentless social media cycles, and targeted influence campaigns. Whether driven by politics, social movements, or ...

Hyperspectral imaging (HSI) captures rich spectral data across hundreds of contiguous bands for diverse applications. Dimension reduction (DR) techniques are commonly used to map the first three ...

The world of data visualization can leave you to choose between expensive software or difficult-to-learn software. lessR simplifies the process of obtaining professional-quality data visualizations at ...

Packaging Corporation of America announced a partial shutdown of its Wallula containerboard plant that will cut production by nearly half. Officials said in a Dec. 4 announcement via Business Wire ...

Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

This important work significantly advances our understanding of the role of human hippocampal theta oscillations in memory encoding and retrieval. The evidence supporting the conclusions is solid, ...