Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …

Metabolic reprogramming in cancer and immune cells occurs to support their increasing
energy needs in biological tissues. Here we propose Single Cell Spatially resolved …

Almost all biomedical research to date has relied upon mean measurements from cell
populations, however it is well established that what it is observed at this macroscopic level …

Single-cell RNA sequencing provides high-throughput gene expression information to
explore cellular heterogeneity at the individual cell level. A major challenge in characterizing …

Single-cell RNA sequencing (scRNA-seq) provides high-throughput information about the
genome-wide gene expression levels at the single-cell resolution, bringing a precise …

Nanomaterials (NMs) have developed quickly and cover various fields, but research on
nanotechnology and NMs largely relies on costly experiments or complex calculations (eg …

This paper presents a new nonlinear non‐intrusive reduced‐order model (NL‐NIROM) that
outperforms traditional proper orthogonal decomposition (POD)‐based reduced order model …

The advances in single-cell ribonucleic acid sequencing (scRNA-seq) allow researchers to
explore cellular heterogeneity and human diseases at cell resolution. Cell clustering is a …

Single-cell omics technologies have made it possible to analyze the individual cells within a
biological sample, providing a more detailed understanding of biological systems …