Researchers Unveil AI Tool to Revolutionize Single-Cell Analysis

Biomedical researchers have gained a powerful new tool for single-cell data analysis with the introduction of CellWhisperer, an artificial intelligence method developed by a team led by Christoph Bock at the CeMM Research Center for Molecular Medicine in Vienna. This innovative software allows scientists to explore complex biological data using natural language, effectively bridging the gap between advanced computational techniques and biological insights.

Leveraging cutting-edge RNA sequencing technology, researchers can now analyze gene activity across millions of single cells. This creates intricate maps of tissues, organs, and diseases. However, the analysis of such vast datasets typically demands a rare skill set, combining deep biological knowledge with expertise in computer programming. Recognizing this challenge, Bock and his team designed CellWhisperer to serve as a virtual assistant, simplifying the data exploration process.

Transforming Data Interaction

CellWhisperer employs multimodal deep learning, integrating gene expression profiles with curated biological text sourced from public databases. This allows users to conduct text-based queries, such as, “Show me immune cells from the inflamed colon of patients with autoimmune diseases.” The software’s AI capabilities include a large language model trained on interactions between biologists and bioinformaticians, enhancing the user experience by facilitating dialogue that reflects real-world scientific collaboration.

The AI methodology enables researchers to ask CellWhisperer about specific genes and their biological implications in an accessible manner. Co-first author Moritz Schaefer, who previously worked as a Postdoctoral Researcher in Bock’s group and is now at Stanford University, noted the significance of this approach. “By training on experimental data from 20,000 studies over the past two decades, CellWhisperer has learned about the roles of genes and cells, making biomedical data exploration easier and more engaging,” he stated.

Applications and Discoveries

To showcase CellWhisperer’s capabilities, the research team applied it to single-cell RNA sequencing data related to human embryonic development. Through basic queries such as “heart” or “brain,” the AI identified developmental time points, specific cell populations, and marker genes associated with organ formation. Notably, many of these markers aligned with established developmental genes, while others hinted at previously unnoticed candidates.

Co-first author Peter Peneder from the St. Anna Children’s Cancer Research Institute emphasized the collaborative nature of scientific discovery. He remarked, “CellWhisperer is not just making biomedical research easier; it helps me understand what is happening in the cells I study. With this AI research assistant on our team, we can conduct exploratory research more effectively, gaining initial insights from new datasets and directing our focus where it is most needed.”

The research findings were published in Nature Biotechnology on November 11, 2025. Bock highlighted the tool’s potential to enhance scientific inquiry, stating, “CellWhisperer empowers us as human scientists by providing immediate support in understanding complex biological data.”

As AI continues to reshape various fields, CellWhisperer exemplifies how technology can facilitate groundbreaking discoveries in biomedical research. By enabling researchers to engage with complex data through natural language, this innovative tool marks a significant advancement in the exploration of the biological foundations of diseases.