Differences in how users gate populations within experiments are major sources of variability in flow cytometry data analysis. Incorporating automated image analysis can substantially reduce user bias ...

Subjectivity in flow-cytometry data analysis has long been a challenge. Recent advancements in high-speed camera capabilities have led to the integration of morphological features with traditional ...

PARIS & PHILADELPHIA--(BUSINESS WIRE)--METAFORA biosystems, a company that’s leveraging its AI-powered flow cytometry platform to generate improved IVDs and more effective cell therapies, today ...

The quality of reference controls is critical for generating accurate compensation or unmixing matrices and correctly interpreting conventional or spectral flow cytometry data, respectively. Follow ...

The UAB Flow Cytometry Lab is home to a staff of medical laboratory professionals who perform complex testing using state-of-the-art flow cytometry equipment. This testing, through research, education ...

How do we “name” a cell and assign its identity? How do we know that we are all talking about the same cells? How do we agree on what it takes to confidently correlate previous with current research ...

Flow cytometry remains a critical technology for the high-throughput analysis of single cells in complex populations. Attention to good analysis practices is more important than ever due to the recent ...

Immunophenotyping is the identification and quantitation of heterogeneous populations of cells by multi-parameter flow cytometry using a panel of fluorescently-labelled antibodies that recognize ...

In the near future, clinical trials will use machine learning routinely to analyze data. Today, however, machine learning is still at an adoption midpoint—no longer pioneering, but not yet ubiquitous.

PARIS & CHICAGO--(BUSINESS WIRE)--METAFORA biosystems, today announces the launch of METAflow, its digital flow cytometry platform, into the RUO market. METAflow offers the power of a highly advanced ...