Speaker
Description
The rapid evolution of human viruses poses a significant challenge to researchers developing strategies to prevent viral disease. Understanding the impact of viral protein mutations plays a key role in everything from vaccine design to antiviral drug development. Deep mutational scanning (DMS) is an indispensable high-throughput technique for determining the consequences of mutations across entire proteins. However, the large and complex datasets generated by DMS are often underutilized due to the lack of accessible and integrated tools for analysis and visualization. To address this gap, we have developed interconnected web-based platforms designed to facilitate the exploration, analysis, and sharing of DMS data within the scientific community. We aim to provide an interactive and user-friendly interface to make complex mutation-function relationships accessible to a broad range of researchers. We hope that by democratizing the use of deep mutational scanning data, we can support the scientific community in advancing our understanding of viral evolution and inform the development of therapeutic and preventive measures against viral diseases.
