Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Recent advances in flow cytometry allow scientists to measure an increasing number of
parameters per cell, generating huge and high-dimensional datasets. To analyse, visualize …

Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …

The number of markers measured in both flow and mass cytometry keeps increasing
steadily. Although this provides a wealth of information, it becomes infeasible to analyze …

Unmasking the subtleties of the immune system requires both a comprehensive knowledge
base and the ability to interrogate that system with intimate sensitivity. That task, to a …

The ability to analyze multiple single-cell parameters is critical for understanding cellular
heterogeneity. Despite recent advances in measurement technology, methods for analyzing …

Elucidation and examination of cellular subpopulations that display condition-specific
behavior can play a critical contributory role in understanding disease mechanism, as well …

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual
gating. Recently, several groups have developed computational methods for identifying cell …

Advances in flow cytometry and other single-cell technologies have enabled high-
dimensional, high-throughput measurements of individual cells as well as the interrogation …

Background Recent advances in automation technologies have enabled the use of flow
cytometry for high throughput screening, generating large complex data sets often in clinical …