Project description

Following infection, bunyaviruses initiate a cascade of events that convert the host cell into a virion production line, historically termed a viral factory (VF), where transcription, translation, replication, and virion assembly drive infectivity and disease, yet key spatio-temporal and structural information about VF formation and host factor involvement remains incomplete or inaccurate. To address this, we aim to determine how the bunyavirus VF is built by identifying where and when functional stages of the viral life cycle occur and uncovering host factors involved in VF formation and activity. For this we use genome-wide, machine learning approaches, and correlative light and cryo-EM methods.

Principal Investigator Name John Barr

Start date 2026

End date 2031

Funded under: Wellcome Trust Discovery Award

Grant agreement ID: 336056/Z/25/Z

Project description

Despite advances in cancer therapy, there is still no reliable way to predict which treatment will work best for each patient, leading to trial-and-error approaches. To address this, we developed zAvatars—zebrafish-based patient-derived xenografts that enable real-time testing of multiple therapies at single-cell resolution, achieving ~90% predictive accuracy in clinical studies.
However, the analysis of the large imaging datasets generated is currently manual, limiting scalability and consistency. We propose to develop an AI-powered pipeline to automate tumor quantification and apoptotic cell detection using advanced deep learning, enabling fast, reproducible analysis and accelerating the clinical adoption of this precision oncology platform.

Principal Investigator Name Rita Fior

Start date 2025

End date 2027

Funded under: Bolsa Liga Portuguesa Contra o Cancro, Oeiras Valley

Group Leader

Estibaliz Gómez-de-Mariscal is a Principal Investigator at NIMSB. Her work lies at the interface of artificial intelligence, microscopy, and biology, aiming to answer biomedical questions in a data-driven manner. She is a mathematician by training and earned her PhD in Mathematical Engineering from Universidad Carlos III de Madrid (Spain) in 2021, supervised by Prof. Arrate Muñoz Barrutia and Prof. Denis Wirtz (Johns Hopkins University), and with research stays at the University of Freiburg (Prof. T Brox) and EPFL (Prof. M Unser). Prior to starting her group, she was a postdoctoral researcher in Prof. Ricardo Henriques’ lab in Portugal working in smart-microscopy and microbiology, supported by an EMBO Postdoctoral Fellowship and an FCT CEEC Fellowship. Estibaliz contributed new AI-driven methods for bioimage analysis across applications including cancer cell migration, phototoxicity, and microbiology, as well as novel statistical approaches to analyse big data. She has also co-developed widely adopted open-source tools such as deepImageJ, the BioImage Model Zoo, and DL4MicEverywhere. Her contributions have been recognised with several awards, including the SBI2 President’s Award and a Wellcome Trust Discovery Award. Beyond her research, Estibaliz has played a key role in advancing the bioimage analysis community through collaborative and infrastructure initiatives. She is a founding member of the AI4LIFE EU consortium, contributing to the development of standards, training, and accessible resources for the application of AI in life sciences. Her work emphasises openness, reproducibility, and usability, with the goal of lowering barriers to advanced computational methods in biomedical research.