In 1998, Rogakou, Pilch, Orr, and Bonner discovered that every DNA double-strand break triggers phosphorylation of histone H2AX, creating a visible focus at the damage site. One… See the analysis in action: https://youtube.com/watch?v=MGj7fIstgC4
Cell counting sounds simple, but it isn't. See the analysis in action: https://youtube.com/watch?v=9mB6o2GWqdg
Colocalization analysis has a reputation problem. For years, the standard practice was to merge the red and green channels, look for yellow, and declare colocalization. This… See the analysis in action: https://youtube.com/watch?v=uf0FLNjSNJ8
Bacterial infection is a numbers game played one cell at a time. How many host cells got hit, and how heavily? See the analysis in action: https://youtube.com/watch?v=UEn5mqnrROk
Most researchers take microscopy images and then describe what they see in adjectives: the cells look bigger, they seem more rounded after treatment. See the analysis in action: https://youtube.com/watch?v=3_ZQGB8qcyY
This isn't one assay. It's the capability that powers half of modern cell biology. γH2AX foci. RNAscope dots. PLA puncta. Stress granules. P-bodies. PML bodies. Pathogen cells.… See the analysis in action: https://youtube.com/watch?v=Kdvpba7jLF0
Lysosomes sit at the center of neurodegeneration, lysosomal storage disease, mTOR signaling, and a fast-growing pipeline of autophagy modulators.
The flashy edge of multiplexed imaging gets the headlines. CODEX, MIBI, IMC. 40 plus markers at a time. These are real and important, but they are not how most biology gets done.
Foci counting gets treated as a single-channel problem. One marker, one condition, a count per cell. That answers part of the question.
For most of the 20th century, lipid droplets were treated as inert blobs of stored fat. That view collapsed around the turn of the millennium with the discovery of perilipins and…
Counting parasites inside host cells is a core readout in antiparasitic drug discovery. Percent infected cells, parasites per cell, or parasite signal intensity all reduce to one…
Some of the most important questions in cell biology aren't about cells, but what's inside them. How many mitochondria per cell? How many DNA damage foci per nucleus? How many…
NF-κB moving into the nucleus is one of the most studied events in inflammation biology. YAP/TAZ shuttling is the readout of the Hippo pathway, critical in cancer and…
A drug is useless if it can't get inside the cell. This is the central challenge for lipid nanoparticles, cell-penetrating peptides, antibody-drug conjugates, and RNA…
In 1882, Élie Metchnikoff pushed a rose thorn into a starfish larva and watched cells swarm to engulf it. That observation, cells eating foreign objects, became a foundation of… See the analysis in action: https://youtube.com/watch?v=ezaikU7ix1I
Oncology drug screening is iterative by nature. Compounds get tested, refined, and re-tested. The team that gets proliferation data back the same day runs the next iteration…
Nobody publishes a paper about transfection efficiency. No one wins a grant for it. But every CRISPR experiment, every overexpression study, every viral vector production run…
Analyzing the cell cycle is crucial for understanding proliferation and disease. While high-throughput methods sacrifice spatial information, Cytely enables rapid classification of cell cycle stages using only a nuclear stain and morphological profiling, preserving spatial context and enabling reproducible quantification.
Smart microscopy is transforming life sciences by automating experimental imaging workflows and enabling real-time adaptation based on feedback from images and other data streams. This shift increases throughput, improves reproducibility, and expands the functional capabilities of microscopes
Analyzing cell populations in whole blood is a fundamental yet challenging task. Even after standard preparation steps, samples often contain mixed populations of leukocytes, platelets, and red blood cells (RBCs). Cytely enables researchers to rapidly identify and quantify these populations at the single-cell level. Through scatter plots and intuitive gating, different blood cell types can be distinguished and characterized in an unbiased, interactive workflow. Key features demonstrated in this note: Visualizing heterogeneity across a mixed cell population Identifying populations (neutrophils, platelets, RBCs) using scatter plots Gating to isolate neutrophil subsets
Learn how to analyze phagocytosis experiments with Cytely.
Here we look at a basic blood sample stained for nuclei, cytosol, and membrane. We easily gated out RBCs and platelets by their lack of nuclear signal and smaller size, while neutrophils popped out with their strong nuclear and cytosolic staining. Ordinarily, you’d need multiple antibodies or RBC lysis to achieve this separation, but with Cytely, you can do it in a single workflow, preserving your sample’s spatial context and completing the entire analysis in a matter of minutes.
In microscopy, the transition from qualitative observation to quantitative data is a significant challenge. Manual analysis is susceptible to user bias and is impractical for large datasets, while many automated solutions can obscure the connection between the quantitative data and the original visual context. Cytely is a web-based tool designed to address these challenges by integrating automated image segmentation with interactive data exploration. It provides a structured workflow for deriving quantitative metrics from cell populations and linking those metrics back to their source images in real-time.
Contemporary microscopy platforms generate datasets of substantial scale, routinely capturing 10,000–100,000 cells per experimental condition. However, analytical constraints frequently limit quantification to small subsets, typically 100–1,000 cells, representing less than 1% of available data. This systematic undersampling introduces selection bias, reduces statistical power, and obscures population heterogeneity. We examine the methodological consequences of incomplete data utilization and present automated high-content analysis as a solution to the disparity between data acquisition capacity and analytical throughput.
Contemporary fluorescence microscopy generates high-resolution imaging data that remains largely underutilized due to analytical bottlenecks in quantification workflows. While flow cytometry has established rigorous standards for population-level single-cell analysis, microscopy-based approaches typically rely on manual enumeration of limited sample sizes, constraining statistical power and obscuring population heterogeneity. This perspective argues for the systematic application of cytometric principles to image-based analysis, enabling researchers to leverage the spatial and morphological advantages of microscopy while achieving the statistical rigor characteristic of flow-based methodologies.