Russian scientists have developed a bioinformatics tool, scParadise, which recognizes various cell types with up to 99.9% accuracy based on RNA sequencing data and evaluates their protein composition. This technology could become an important tool for disease diagnostics, helping to distinguish cancer cells from healthy ones, identify rare varieties of immune cells, and in the future, create more personalized treatment methods.

Modern medicine increasingly uses RNA sequencing – a method that allows studying molecules that a cell creates based on its DNA. Each cell type has a different set of such molecules, so it can be used to determine the cell type, including various types of immune cells. However, after RNA decoding, another complex task arises – correctly processing a huge amount of information. Manually, this takes too much time, and existing algorithms often make mistakes, especially when searching for rare or unusual cells.

To solve this problem, scientists from Moscow State University, the National Research Center for Epidemiology and Microbiology named after Honorary Academician N. F. Gamaleya, and the FMBA developed the scParadise system. It uses artificial intelligence technologies and distinguishes different cell types with up to 99.9% accuracy based on RNA sequences, simultaneously evaluating their protein composition.

During tests, researchers analyzed adipose tissue cells from healthy individuals and overweight patients. The system not only correctly recognized all known cell types but also discovered three previously undescribed varieties of immune cells, which, according to the authors, may be involved in the development of chronic inflammation in obesity.

According to the developers, the technology has broad prospects for medicine. It will allow determining the causes of inflammation in overweight patients based on RNA sequencing data, as well as finding single chemotherapy-resistant cells in tumors. This will help doctors select treatment more accurately and increase its effectiveness by targeting specific cells that support disease development.