[HTML][HTML] Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data
Highlights•Large multiparametric flow cytometry data sets are ideal for machine learning.•
Unsupervised clustering methods highlight microbial community changes.•Supervised …
Unsupervised clustering methods highlight microbial community changes.•Supervised …
Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data
The study of complex microbial communities typically entails high-throughput sequencing
and downstream bioinformatics analyses. Here we expand and accelerate microbiota …
and downstream bioinformatics analyses. Here we expand and accelerate microbiota …
Metal Mixture Toxicity of Ni, Cu, and Zn in Freshwater Algal Communities and the Correlation of Single‐Species Sensitivities Among Single Metals: A Comparative …
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 …
thereby not accounting for effects of metal mixtures or effects of species interactions. Both of …
Extended live-cell barcoding approach for multiplexed mass cytometry
Sample barcoding is essential in mass cytometry analysis, since it can eliminate potential
procedural variations, enhance throughput, and allow simultaneous sample processing and …
procedural variations, enhance throughput, and allow simultaneous sample processing and …
On Selecting Distance Metrics in -Dimensional Normed Vector Spaces of Cells: A Novel Criterion and Similarity Measure Towards Efficient and Accurate Omics …
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 …
features, to be quantified. Cluster analysis, a dimensionality reduction process, is used to …
Ecotoxicity of metal mixtures to freshwater planktonic communities: the something-from-nothing effect
Toxic trace metals are persistent pollutants in the environment that can considerably affect
the structure and functioning of aquatic and terrestrial ecosystems. Despite reduced metal …
the structure and functioning of aquatic and terrestrial ecosystems. Despite reduced metal …
Supervised distance metric learning for pattern recognition
B Nguyen Cong - 2019 - biblio.ugent.be
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 …
dissimilarity) play an important role in the growing field of machine learning. Often …