Animal Model

Animal models are crucial for biomedical research, serving as surrogates for human systems to study disease mechanisms and test therapies. Current research emphasizes developing and refining these models, focusing on improved data analysis techniques such as machine learning (including neural networks, random forests, and generative models) to extract meaningful insights from complex datasets (e.g., genomic, imaging, behavioral). This includes efforts to enhance the translation of findings from animal models to human applications, particularly by leveraging advanced image analysis and developing methods to better match animal model characteristics to human disease states. Ultimately, these advancements aim to improve the efficiency and reliability of preclinical research, accelerating the development of new diagnostics and treatments.