Research Highlight: PSIPRED Workbench: A User-Friendly Platform for Protein Structure Prediction
This talk will introduce the PSIPRED Workbench, a widely used, open-access platform for protein structure prediction and analysis. Designed to be both powerful and accessible, the workbench integrates a range of computational tools for predicting secondary structure, disorder, and other key protein features from sequence data.
Dr Buchan will provide an overview of the platform, demonstrating how it can be used to support protein engineering and structural biology workflows. The session will highlight practical applications of PSIPRED, from initial sequence analysis to guiding experimental design.
This talk is particularly suited for students and researchers interested in computational tools for protein analysis, offering a clear introduction to one of the field’s most widely adopted resources.
About the speaker
Daniel is a Senior Research Software Engineer at University College London, where he develops tools for data science and machine learning in multidisciplinary research environments. His work focuses on building platforms that transform statistical and machine learning models into scalable web services and practical research tools.
With more than a decade of experience at the intersection of machine learning, bioinformatics, and large-scale data analysis, Daniel has contributed to several major biological data projects, including CATH, Gene3D, and the Tomato Genome Project. His expertise spans research software engineering, computational statistics, and the development of platforms for high-throughput biological data analysis.
Before his current role, Daniel worked as a data scientist and analytics manager in industry, applying machine learning to large datasets in sectors such as insurance and housing economics.