115 citations · 370 across the 6 of their papers we have counts for
6 papers
SurpriseMe: an integrated tool for network community structure characterization using Surprise maximization
Rodrigo Aldecoa, Ignacio Marín
Detecting communities, densely connected groups may contribute to unravel the underlying relationships among the units present in diverse biological networks (e.g., interactome, co…
Exploring the limits of community detection strategies in complex networks
Rodrigo Aldecoa, Ignacio Marín
The characterization of network community structure has profound implications in several scientific areas. Therefore, testing the algorithms developed to establish the optimal divi…
Surprise maximization reveals the community structure of complex networks
Rodrigo Aldecoa, Ignacio Marín
How to determine the community structure of complex networks is an open question. It is critical to establish the best strategies for community detection in networks of unknown str…
Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering
Rodrigo Aldecoa, Ignacio Marín
Background: How to extract useful information from complex biological networks is a major goal in many fields, especially in genomics and proteomics. We have shown in several works…
Closed benchmarks for network community structure characterization
Rodrigo Aldecoa, Ignacio Marín
Characterizing the community structure of complex networks is a key challenge in many scientific fields. Very diverse algorithms and methods have been proposed to this end, many wo…
Deciphering Network Community Structure by Surprise
Rodrigo Aldecoa, Ignacio Marín
The analysis of complex networks permeates all sciences, from biology to sociology. A fundamental, unsolved problem is how to characterize the community structure of a network. Her…