The rapidly evolving realm of single-cell transcriptomics offers vital new perspectives into the
understanding of intra-and inter-cellular molecular dynamics governing development …

Traditional bulk sequencing methods are limited to measuring the average signal in a group
of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution …

Recent advances in single-cell sequencing technologies enable the characterization of
cellular heterogeneity and biological processes in complex diseases. This provides …

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into
complex tissues, with the latest techniques capable of processing tens of thousands of cells …

Deep learning has tremendous potential in single-cell data analyses, but numerous
challenges and possible new developments remain to be explored. In this commentary, we …

Single-cell transcriptomics (SCT) is a tour de force in the era of big omics data that has led to
the accumulation of massive cellular transcription data at an astounding resolution of single …

There is a growing need for integration of “Big Data” into undergraduate biology curricula.
Transcriptomics is one venue to examine biology from an informatics perspective. RNA …

Single-cell technology offers unprecedented insight into the molecular landscape of
individual cell and is transforming precision medicine. Key to the effective use of single-cell …

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic
analysis of an individual cell. Through the combination of high-throughput sequencing and …

Since its selection as the method of the year in 2013, single-cell technologies have become
mature enough to provide answers to complex research questions. With the growth of single …