GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

GRIP (Gold Reference dataset constructor from Information on Protein complexes) is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae.GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/ webcite.A fundamental problem in the post-genomic era is the determination of protein-protein interactions (PPI). Efforts have been made to map interactions on a proteomic-wide scale. Several large-scale protein-protein interaction maps have been produced for Saccharomyces cerevisiae (S. cerevisiae) and other organisms, such as Drosophila melanogaster and Homo sapiens from experimental high-throughput methods. However, even the best studied model organisms contain a large number of proteins whose interactions and functions are currently unknown [1]. This highlights the continued need for computational methods to help to direct experimentalists in the search for novel protein interactions. To validate PPI computational predictions it is essential to have a reference dataset that contains validated interactions (positive cases) and non-interacting (negative) cases. Such a knowledge reference is known as a Gold Standard and is used for prediction model construction