As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, we will show how to apply biclustering methods to find local patterns in a big data matrix.
The talk presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies illustrate the use of several biclustering methods. The mathematical theory of one or two methods will be shown in detail and references to technical details of the methods are provided.