Brenda Moita
Academic and research departments
School of Veterinary Medicine, Faculty of Health and Medical Sciences, Horse Microbiome Research Group.About
Brenda Moita is a dedicated researcher specialising in Equine Grass Sickness (EGS), a devastating neurodegenerative disease affecting horses. Her PhD focuses on understanding the complex molecular mechanisms of EGS through innovative approaches in proteomics, biomarker discovery, and computational biology. As a Member of the Royal Society of Biology (MRSB), she is committed to advancing equine health through rigorous scientific research.
Her work integrates bottom-up proteomics, machine learning, and proteogenomics to identify diagnostic and prognostic biomarkers for EGS. By employing cutting-edge technologies, including AlphaFold3 and Python-based bioinformatics tools, she bridges computational and experimental techniques to provide novel insights into this poorly understood condition.
Brenda is supervised by Prof. Chris Proudman (Professor of Veterinary Clinical Science) and Dr. Sneha Pinto (Senior Lecturer in Proteomics).
My qualifications
Affiliations and memberships
Membership number: P0154899
Membership number: 8877
ResearchResearch interests
- Machine Learning and Artificial Intelligence in Biology
- Proteomics and Biomarker Discovery
- Computational Biology and Bioinformatics
- Statistical Modeling
Research projects
I am conducting advanced research to identify biomarkers for Equine Grass Sickness (EGS), a serious and often fatal disease in horses. My project employs advanced mass spectrometry-based proteomics, bioinformatics, and artificial intelligence to analyse protein "fingerprints" in biological samples from affected and healthy horses.
This interdisciplinary project brings together expertise from the Moredun Research Institute and the University of Surrey’s Schools of Biosciences and Veterinary Medicine. By identifying proteins with diagnostic potential, the research aims to improve early detection and provide insights into the disease that could shape future treatment approaches.
The project also has a strong focus on science communication and outreach, helping raise awareness of EGS among equine professionals, researchers, and the wider horse-owning community.
Research interests
- Machine Learning and Artificial Intelligence in Biology
- Proteomics and Biomarker Discovery
- Computational Biology and Bioinformatics
- Statistical Modeling
Research projects
I am conducting advanced research to identify biomarkers for Equine Grass Sickness (EGS), a serious and often fatal disease in horses. My project employs advanced mass spectrometry-based proteomics, bioinformatics, and artificial intelligence to analyse protein "fingerprints" in biological samples from affected and healthy horses.
This interdisciplinary project brings together expertise from the Moredun Research Institute and the University of Surrey’s Schools of Biosciences and Veterinary Medicine. By identifying proteins with diagnostic potential, the research aims to improve early detection and provide insights into the disease that could shape future treatment approaches.
The project also has a strong focus on science communication and outreach, helping raise awareness of EGS among equine professionals, researchers, and the wider horse-owning community.
Sustainable development goals
My research interests are related to the following:
