The collaboration applies Mavatar Discovery to support the group’s research program in acute myeloid leukemia (AML). Specifically, the work explores whether differentially expressed genes identified in clinical cohorts can be confirmed and contextualized in large-scale transcriptomic datasets – and how network-based analysis can reveal the biological relationships between candidate markers and other genes relevant in AML. This network layer adds a further dimension to the validation of candidate biomarkers, strengthening confidence in their biological role.

“Some of the most important biological questions are sitting in data that already exists. We want to give researchers the tools to find those answers, without needing a bioinformatics team to do it. We are delighted to welcome Bruno Paiva and his team to our growing network of university and industry collaborators,” says Danuta Gawel, Chief R&D Officer at Mavatar

The current collaboration focuses on AML, with both parties expressing interest in extending the work into multiple myeloma – a field in which Bruno Paiva is internationally recognized as one of the leading researchers.

“Mavatar Discovery changes how we approach the early stages of a research question. Instead of relying solely on what we can generate in our own cohort, we can immediately explore how our findings relate to the broader biological landscape – across diseases, tissues and datasets. For a research group working across multiple hematologic malignancies, that kind of systems-level context is genuinely valuable,” says Bruno Paiva, PhD, Principal Investigator, Clínica Universidad de Navarra.