image: Screenshot of the CellWhisperer AI for chat-based analysis of single-cell data
Credit: (© Moritz Schäfer)
(Vienna, 11 November 2025) Using sophisticated RNA sequencing technology, biomedical researchers can measure the activity of our genes across millions of single cells, creating detailed maps of tissues, organs, and diseases. Analysing these datasets requires a rare combination of skills: deep understanding of the biology, and the ability to develop computer code that turns data into insights. What if we could equip biomedical researchers with an AI assistant that sees the data, supports the analysis, knows about the biology, and is easy to talk to? This could give scientists a virtual, AI-based colleague with both biological and bioinformatics expertise to support them in their research.
Toward this goal, researchers led by Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences and Professor at the Medical University of Vienna, have developed CellWhisperer. CellWhisperer is an AI method and software tool that links gene expression with descriptive text across more than a million biological samples. It provides an AI chat box to investigate complex biology in English language, unburdened by the complexities of computer code. This study, published in Nature Biotechnology, demonstrates how AI creates a new way for scientists to interact with their data when studying the biological foundations of diseases.
From genes to text – and vice versa
CellWhisperer uses multimodal deep learning on gene activity profiles and matched biological text, which the authors curated from public databases with the help of AI models. Combining these two data modalities, it becomes possible to search massive datasets with text-based queries such as “Show me immune cells from the inflamed colon of patients with autoimmune diseases”.
The CellWhisperer multimodal AI further integrates a large language model that was trained to emulate discussions between biologists and bioinformaticians when analysing data. Chatting with CellWhisperer thus sounds a bit like talking to a bioinformatics colleague, relying on CellWhisperer’s view of the biological data and the biological knowledge of the large language model. For example, users can ask CellWhisperer about genes that are active in cells of interest, and let the model comment on potential biological implications. CellWhisperer is built into a user-friendly web frontend based on the popular CELLxGENE browser and freely accessible online: https://cellwhisperer.bocklab.org.
“By training on experimental data of 20,000 studies from the last two decades, CellWhisperer learned about the biological roles of genes and cells,” explains co-first author Moritz Schaefer, a former Postdoctoral Researcher in Christoph Bock’s research group at CeMM and now at Stanford University. “This way, CellWhisperer is prepared to analyse new single-cell RNA sequencing data from many areas, making biomedical data exploration easier and more exciting.”
A step toward AI research agents
To illustrate CellWhisperer’s potential for biological discovery, the team applied it to single-cell RNA sequencing data of human embryonic development. With basic queries such as “heart” or “brain”, the model identified developmental time points, cell populations, and marker genes associated with human organ formation. Many of these markers matched known developmental genes, while others pointed to previously overlooked candidates.
“CellWhisperer is not just making biomedical research easier, it helps me understand what is going on in the cells that I am studying,” says Peter Peneder, co-first author at the St. Anna Children’s Cancer Research Institute.
“Science is teamwork, and with CellWhisperer, an AI research assistant has joined our team. CellWhisperer really helps with exploratory research – getting a first impression of a new dataset and figuring out where to dig deeper. It supports and empowers us as human scientists,” emphasizes Christoph Bock.
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The study “Multimodal learning enables chat-based exploration of single-cell data” was published in Nature Biotechnology on 11 November 2025. DOI:10.1038/s41587-025-02857-9
Funding: This work was supported by the European Research Council (ERC), the Austrian Science Fund (FWF), the Vienna Science and Technology Fund (WWTF), and the Austrian Academy of Sciences.
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The CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences is an international, independent and interdisciplinary research institution for molecular medicine under the scientific direction of Giulio Superti-Furga. CeMM is oriented towards medical needs and integrates basic research and clinical expertise to develop innovative diagnostic and therapeutic approaches for precision medicine. Research focuses on cancer, inflammation, metabolic and immune disorders, rare diseases and aging. The Institute’s research building is located on the campus of the Medical University and the Vienna General Hospital.
The St. Anna Children’s Cancer Research Institute (St. Anna Kinderkrebsforschung, St. Anna CCRI) is an international and interdisciplinary research institution dedicated to developing innovative diagnostic, prognostic, and therapeutic strategies for the treatment of children and adolescents with cancer. Taking into account the specific features of childhood tumors, dedicated research groups in tumor genomics and epigenomics, immunology, molecular and cell biology, bioinformatics, and clinical research work together to align the latest scientific findings with clinical needs and sustainably improve the well-being of young patients.
www.ccri.at | www.kinderkrebsforschung.at
The Medical University of Vienna (MedUni Vienna) is one of the longest-established medical education and research facilities in Europe. With almost 8,600 students, it is currently the largest medical training center in the German-speaking countries. With more than 6,500 employees, 30 departments and two clinical institutes, twelve medical theory centers and numerous highly specialized laboratories, it is one of Europe's leading research establishments in the biomedical sector. MedUni Vienna also has a medical history museum, the Josephinum.
For further information please contact:
Wolfgang Däuble
Media Relations Manager / Science Writer
Phone +43-1/40160-70092
wdaeuble@cemm.at
CeMM
Research Center for Molecular Medicine
of the Austrian Academy of Sciences
Lazarettgasse 14, AKH BT 25.3
1090 Vienna, Austria
www.cemm.at
Journal
Nature Biotechnology
Method of Research
Computational simulation/modeling
Subject of Research
Cells
Article Title
Multimodal learning enables chat-based exploration of single-cell data
Article Publication Date
11-Nov-2025