The development of new molecular and cell technologies is having a significant impact on
the quantity of data generated nowadays. The growth of omics databases is creating a …

Pattern recognition is concerned with the development of systems that learn to solve a given
problem using a set of example instances, each represented by a number of features. These …

Background Principal component analysis (PCA) is frequently used in genomics
applications for quality assessment and exploratory analysis in high-dimensional data, such …

High-throughput RNA sequencing (RNA-Seq) has transformed the ecophysiological
assessment of individual plankton species and communities. However, the technology …

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules
induces the prolongation of the QT interval which leads to fatal cardiotoxicity and accounts …

Sparse principal component analysis (SPCA) has emerged as a powerful technique for
modern data analysis, providing improved interpretation of low-rank structures by identifying …

Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells,
which has given us insights into cell–cell communication, cell differentiation, and differential …

In this work, uniform manifold approximation and projection (UMAP) is applied for nonlinear
dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We …

Ethnopharmacological relevance Alzheimer's disease (AD), as the most common type of
dementia, has brought a heavy economic burden to healthcare system around the world …

Protein crystallization is crucial for biology, but the steps involved are complex and
demanding in terms of external factors and internal structure. To save on experimental costs …