Highlights•Large multiparametric flow cytometry data sets are ideal for machine learning.•
Unsupervised clustering methods highlight microbial community changes.•Supervised …

The study of complex microbial communities typically entails high-throughput sequencing
and downstream bioinformatics analyses. Here we expand and accelerate microbiota …

The effects assessment of metals is mainly based on data of single metals on single species,
thereby not accounting for effects of metal mixtures or effects of species interactions. Both of …

Sample barcoding is essential in mass cytometry analysis, since it can eliminate potential
procedural variations, enhance throughput, and allow simultaneous sample processing and …

Single-cell omics enable the profiles of cells, which contain large numbers of biological
features, to be quantified. Cluster analysis, a dimensionality reduction process, is used to …

Much like in other modeling disciplines does the distance metric used (a measure for
dissimilarity) play an important role in the growing field of machine learning. Often …