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Statistics seminar: "Sparse Graphs in Genomics"

Seminario di Statistica

07/11/2013 dalle 11:00 alle 13:00

Dove Dipartimento di Scienze Statistiche - Via Belle Arti 41 - Aula III

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Ernst Wit  - University of Groningen

Abstract: A graph is one possible way to describe complex relationships between many actors, such as for example RNA, proteins and metabolites. In many cases, genomic data comes from large monitoring systems with no prior screening. The combination of such indiscriminate data collection with the structured nature of genomic interactions, the actual set of relationships, therefore, tends to be sparse. When data is obtained from noisy measurements of (some of) the nodes in the graph, then graphical models present an appealing and insightful way to describe graph-based dependencies between the random variables. Although potentially still interesting, the main aim of inference is not the precise estimation of the parameters in the graphical model, but the underlying structure of the graph. Graphical lasso and related methods opened up the field of sparse graphical model inference in high-dimensions. We show how extensions of such methods in more structured settings can improve interpretation. Moreover, in this presentation, we show how novel model selection criteria can deal with determining the underlying graph in an efficient way.