Navigating the Global Protein-Protein Interaction Landscape Using iRefWeb.

iRefWeb is a resource that provides web interface to a large collection of protein-protein interactions aggregated from major primary databases. The underlying data-consolidation process, called iRefIndex, implements a rigorous methodology of identifying redundant protein sequences and integrating disparate data records that reference the same peptide sequences, despite many potential differences in data identifiers across various source databases. iRefWeb offers a unified user interface to all interaction records and associated information collected by iRefIndex, in addition to a number of data filters and visual features that present the supporting evidence.

The eGenVar data management system--cataloguing and sharing sensitive data and metadata for the life sciences.

Systematic data management and controlled data sharing aim at increasing reproducibility, reducing redundancy in work, and providing a way to efficiently locate complementing or contradicting information. One method of achieving this is collecting data in a central repository or in a location that is part of a federated system and providing interfaces to the data. However, certain data, such as data from biobanks or clinical studies, may, for legal and privacy reasons, often not be stored in public repositories.

Navigating the global protein-protein interaction landscape using iRefWeb.

iRefWeb is a bioinformatics resource that offers access to a large collection of data on protein-protein interactions in over a thousand organisms. This collection is consolidated from 14 major public databases that curate the scientific literature. The collection is enhanced with a range of versatile data filters and search options that categorize various types of protein-protein interactions and protein complexes.

iRefScape. A Cytoscape plug-in for visualization and data mining of protein interaction data from iRefIndex.

Background: The iRefIndex consolidates protein interaction data from ten databases in a rigorous manner using sequence-based hash keys. Working with consolidated interaction data comes with distinct challenges: data are redundant, overlapping, highly interconnected and may be collected and represented using different curation practices. These phenomena were quantified in our previous studies.

Literature curation of protein interactions: measuring agreement across major public databases.

Literature curation of protein interaction data faces a number of challenges. Although curators increasingly adhere to standard data representations, the data that various databases actually record from the same published information may differ significantly. Some of the reasons underlying these differences are well known, but their global impact on the interactions collectively curated by major public databases has not been evaluated.

iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence.

We present iRefWeb, a web interface to protein interaction data consolidated from 10 public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb enables users to examine aggregated interactions for a protein of interest, and presents various statistical summaries of the data across databases, such as the number of organism-specific interactions, proteins and cited publications. Through links to source databases and supporting evidence, researchers may gauge the reliability of an interaction using simple criteria, such as the detection methods, the scale of the study (high- or low-throughput) or the number of cited publications.

iRefIndex: a consolidated protein interaction database with provenance.

Background: Interaction data for a given protein may be spread across multiple databases. We set out to create a unifying index that would facilitate searching for these data and that would group together redundant interaction data while recording the methods used to perform this grouping.

Results: We present a method to generate a key for a protein interaction record and a key for each participant protein.