Below is a press release about the Methods paper ‘BiMat: a MATLAB package to facilitate the analysis of bipartite networks‘ taken from the Pompeu Fabra University.

The Georgia Institute of Technology has created, together with the Pompeu Fabra University and the University of Canterbury, a new open-access and open-source tool for the study of bipartite networks

The team led by Joshua S. Weitz, Associate Professor at the School of Biology from the Georgia Institute of Technology, has developed BiMat: an open source MATLAB® package for the study of the structure of bipartite ecological networks inspired by real problems in microbiology and with broader applications. Cesar O. Flores, researcher at the School of Physics of the same institute, describes this new tool in an article published in the journal Methods in Ecology and Evolution. Sergi Valverde, Visiting Professor at the Complex Systems Lab from the Pompeu Fabra University, and Timothée Poisot, from the School of Biological Sciences of the University of Canterbury, are involved in the project.

The study of ecological networks helps to understand the biodiversity of our environment and to predict possible extinctions.  Bipartite networks are a special type of ecological network where individuals of a certain species interact with individuals of different species. Bipartite networks are ubiquitous in community ecology, such as the relation between phages (viruses that infect bacteria) and their bacterial hosts.

As Valverde comments “complex networks show common patterns, like nestedness and modularity, and their ecological and evolutionary effects can be studied using theoretical and computational methods”.

A number of tools have been developed to analyze bipartite networks, but BiMat includes new features available for the first time in a single package. Apart from enabling the identification of the key patterns and the evaluation of their statistical significance, this new tool is also capable of performing the multi-scale and meta-analysis of the structure of multiple networks. Furthermore, BiMat includes several visualization tools to explore bipartite networks in either matrix or graph layouts.

Although BiMat was inspired by real problems in microbiology context, is applicable generally for the analysis of systems represented by bipartite networks.  Prominent examples of bipartite networks include mutualistic networks (e.g., plant-pollinator interactions) and antagonistic networks (e.g., virus-plant infection networks).

BiMat has been developed in an object-oriented environment for both MATLAB and Octave platforms. This design enables easy access to all methods and allows for future extensions by the research community. In addition, the companion website provides strong help and a free tutorial.

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Carolina Pozo (UPF Media Room)
Email: carolina.pozo [at]