SoftwareX (May 2024)
GIN: A web-application for constructing synthetic datasets of interconnected networks in bioinformatics
Abstract
Networks are crucial in structuring biological systems in terms of interactions, to investigate the related properties and dynamics. Network analysis plays a relevant role in knowledge extraction from complex biological data, where biological objects and their own interactions (or relationships) can be modelled as nodes and edges, respectively. In this context, data is crucial in testing and evaluating process, for designing effective methods and software tools. For instance, network alignment requires many samples to evaluate the performance in node mappings, as well as in contexts where the aim is to reconstruct a missing or perturbed topology. It is common in scientific literature to report a lack of datasets related to interconnected biological networks. Usually, a research group has to design its own dataset for testing a novel method or software tool. This work addressed this issue, presenting a web-based Generator of synthetic Interconnected Networks (GIN). Our contribution has the primary aim of supporting the provision of synthetic data, via a user-friendly and effective tool. GIN allows for the generation of ad-hoc datasets that are particularly suitable for bioinformatics applications. Furthermore, the possibility of defining the network generation parameters allows a scientist to model (ad-hoc) interconnected networks for reproducing the topological and dynamical properties of a real biological network of interest.
