Natasha S. Barteneva

This study uses deep learning with label-free imaging flow cytometry to automate bovine sperm morphology classification, achieving high accuracy and highlighting the need for standardized datasets.

The paper uses full-spectrum cytometry to analyze microalgae and bacteria by their autofluorescence, revealing taxonomic differences and interactions affecting pigment signatures.

This study assesses how ionic composition affects microbial diversity in inland saline aquatic habitats, finding it explains more variability than salinity or geographic location.

This paper introduces a spectral fingerprinting method using full-spectrum cytometry to analyze synthetic algal-microbial communities, showing improved accuracy in species identification and community tracking.

The paper examines how salinity fluctuations in the Aral Sea's residual lakes affect phytoplankton communities using microscopy and FlowCam imaging.

The paper develops a spectral flow cytometry approach with virtual filtering to differentiate microalgae taxa by analyzing spectral emission regions and light scattering parameters.