In Silico Neuroscience: Data Reproducibility and Reusability

Related lectures (32)

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Explores text mining in neuroinformatics to extract brain connectivity data and annotate model parameters from scientific literature.

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Introduces modern neuroscience approaches and applications, emphasizing computational modeling and its importance in understanding the brain.

Explores assembling in silico neuroscience networks, defining space, and dealing with sparse data to reconstruct brain regions.

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Covers the fundamentals of computational neuroscience, focusing on biophysics and modeling.

Covers the modeling of hydrological systems, focusing on the retention of floods and the example of the Routing System.

Explores neural network simulation, activity dynamics, and validation processes to ensure accurate predictions.

Introduces data warehousing fundamentals, challenges, and the innovative concept of a 'lakehouse'.