Lecture
This lecture explores the concept of Big Data in neuroscience, focusing on the analysis of extremely large datasets generated through high-throughput methods to extract biological meaning. It delves into the challenges of finding, organizing, standardizing, and integrating data, as well as building models and visualizing information. The presentation covers the different types of molecules, cellular and tissue properties, and experimental contexts involved in Big Data analysis, emphasizing the importance of tools like text mining, metadata, knowledge graphs, ontologies, and atlases.