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We introduce a technique that is capable to filter out information fromcomplex systems, by mapping them to networks, and extracting a subgraph withthe strongest links. This idea is based on the Minimum Spanning Tree, and itcan be applied to sets of graphs that have as links different sets ofinteractions among the system's elements, which are described as network nodes.It can also be applied to correlation-based graphs, where the links areweighted and represent the correlation strength between all pairs of nodes. Weapplied this method to the European scientific collaboration network, which iscomposed of all the projects supported by the European Framework Program FP6,and also to the correlation-based network of the 100 highest capitalized stockstraded in the NYSE. For both cases we identified meaningful structures, such asa strongly interconnected community of countries that play important role inthe collaboration network, and clusters of stocks belonging to differentsectors of economic activity, which gives significant information about theinvestigated systems.

Filtering of complex systems using overlapping tree networks