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This course is to introduce participants to techniques for comprehensive data analysis of big data and to integrate heterogeneous data sets in order to extract relevant information for elucidating the living system. The course is modular and focuses on data generation, mining, analysis, data integration, and visualization.
Technological and scientific advances have pushed the Life sciences into the BIG data era. The increased volume and heterogeneity of available data challenges scientists to master techniques for comprehensive data analysis. Extracting meaningful (biological) information from large datasets is increasingly becoming a challenge in all fields of life sciences. Thus, the ability to select and deploy analysis tools and algorithms has become an indispensable skill for all researchers. In this course, we aim to introduce participants to techniques for comprehensive data analysis of large, heterogeneous datasets and extract relevant information for elucidating biological design principles. The course is modular and focuses on data generation, mining, analysis, data integration, and visualization.
This course is aimed at anyone working with big datasets in the life sciences who has an interest in learning more about tools and possibilities for big data analysis. The course is introductory and no specific prerequisites are asked.
Required knowledge: Basic knowledge of statistics.
Prerequisite: Experience of computer programming would be useful but is not mandatory. Computer practicals will require using R. An R tutorial will be sent in advance to ensure that all participants have the required level.
Max. 25 participants. Registrants will be placed on an waiting-list when the maximum is reached.