SIGNOR: a new SIGnaling network open resource

Standardization and analysis of large datasets have played, in recent decades, a key role in many fields of knowledge including biology. Biological information, starting from the sequence of a protein to its function, are increasingly being analyzed and made accessible to the scientific community through the use of web-services and databases. In particular the protein-protein interaction network has proved a crucial resource to promote the advancement of systems biology and facilitate the understanding of events occurring in biological systems. Despite the many insights we gained from the analysis of this information, currently available interactomes have several shortcomings. One of the most important limitations is the lack of information on protein regulation and on the direction of the information flow that from the sense of a stimulus leads to the cellular response. In addition, in the available picture, information about the participation of other important biological entities (e.g., small molecule, transcription factors and genes) is still missing. To this purpose, in recent years, different signalling resources have been created, with the aim of capturing all the signal transduction information reported in the scientific literature, organizing it in a structured format and offering it to the community in a user friendly way. Our group decided to create a new resource to "fill the gap" between protein-protein interactions and signalling networks and at the same time, to provide researchers with a tool to support experimental approaches based on multi-parametric analysis of cell systems. SIGNOR (http://signor.uniroma2.it), the Signalling Network Open Resource is a new database-centered application specifically designed to facilitate the storage and analysis of directed molecular interaction and regulation. An ongoing curation effort aims at making SIGNOR a prominent resource in the biological community by offering a comprehensive network of experimentally validated functional relationships between signalling proteins that can be used as an a priori model for optimization strategies. At the time of writing, the core of SIGNOR is a collection of approximately 7400 manually-annotated logic relationships between proteins and other biological entities that participate in signal transduction. Each relationship is linked to the literature reporting the experimental evidence and is assigned a score. These numbers are expected to increase thanks to the manual annotation of further publications carried out by our expert curators. Scientists from various branches of biology may find SIGNOR a precious resource to foster their own research.