Transcriptional regulation is a key component in the downstream response to neuronal stimulation.

Although several techniques exist to identify active neurons, however, there is currently no method available to estimate neuronal activity from whole transcriptome gene expression data.

A recent study introduces NEUROeSTIMator, a powerful and broadly applicable bioinformatics tool that quantifies neuronal activation.

This team of researchers trained deep learning algorithms on single cell analysis datasets to estimate neuronal activation in a way that demonstrates is associated with Patch-seq electrophysiological features and that is robust against differences in species, cell type, and brain region.

Furthermore, embodying a knowledge-sharing attitude, a corner stone of the scientific spirit, this group of researchers have made this tool available to everyone as a free R package with installation instructions and a tutorial.

Altogether, NEUROeSTIMator is a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

This study exemplifies the merge between the worlds of medicine and computer science.

Thanks to single cell analysis techniques, we are able to extract millions of accurate and reliable data points from samples that previously, with bulk analysis, we were only able to extract a few.

Instead of a handful of aggregate measurements, we now have rich per-cell data matrices that can be directly ingested by algorithms, enabling advanced statistics, machine learning, and AI to uncover patterns, predict outcomes, and guide decision‑making in ways that were simply not possible before.

BonsaiLab: Your 10x Genomics Partner in Spain and Portugal

As the official 10x Genomics distributors in Spain and Portugal, don't hesitate to get in touch with our experts to explore single cell analysis and spatial transcriptomics can be implemented in your projects.