Cytometry. Part A : the journal of the International Society for Analytical Cytology
May 17, 2019
Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantif...
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through compa...
Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from c...
High-throughput quantification of oligodendrocyte myelination is a challenge that, if addressed, would facilitate the development of therapeutics to promote myelin protection and repair. Here, we established a high-throughput method to assess oligode...
Recent advances in large-scale single-cell RNA-seq enable fine-grained characterization of phenotypically distinct cellular states in heterogeneous tissues. We present scScope, a scalable deep-learning-based approach that can accurately and rapidly i...
UNLABELLED: For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentati...
Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular...
A fluorescent emitter simultaneously transmits its identity, location, and cellular context through its emission pattern. We developed smNet, a deep neural network for multiplexed single-molecule analysis to retrieve such information with high accura...
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...