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 ...

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 ...

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 ...

Abstract: A large number of processes nowadays are complex and characterized by the presence of several quality variables. In most cases these variables are interrelated and therefore the need arises ...

Prerequisite: Introduction to Python for Absolute Beginners or some experience using Python. You’ve cleaned and analyzed your data, now learn how to visualize it. Visualizing data is critical for both ...

1 University of Dallas, Computer Science Department, Irving, TX, United States 2 University of Dallas, Biology Department, Irving, TX, United States T-cell receptor (TCR) sequencing has emerged as a ...

FORMIDABLE. Johnny Arcilla prepares to serve against Miguel Iglupas in the 42nd Philippine Columbian Association (PCA) Tennis Championships Tuesday (Sept. 30, 2025) at the PCA indoor shell court in ...

This is the final installment of a three-part series marking the 10th anniversary of the historic sentencing in the Peanut Corporation of America (PCA) case. To read Part 1, click here. To read Part 2 ...