Abstract
Protein interactions are fundamental to the molecular processes occurring within an organism and can be utilized in network biology to help organize, simplify, and understand biological complexity. Currently, there are more than 10 publicly available Arabidopsis (Arabidopsis thaliana) protein interaction databases. However, there are limitations with these databases, including different types of interaction evidence, a lack of defined standards for protein identifiers, differing levels of information, and, critically, a lack of integration between them. In this paper, we present an interactive bioinformatics Web tool, ANAP (Arabidopsis Network Analysis Pipeline), which serves to effectively integrate the different data sets and maximize access to available data. ANAP has been developed for Arabidopsis protein interaction integration and network-based study to facilitate functional protein network analysis. ANAP integrates 11 Arabidopsis protein interaction databases, comprising 201,699 unique protein interaction pairs, 15,208 identifiers (including 11,931 The Arabidopsis Information Resource Arabidopsis Genome Initiative codes), 89 interaction detection methods, 73 species that interact with Arabidopsis, and 6,161 references. ANAP can be used as a knowledge base for constructing protein interaction networks based on user input and supports both direct and indirect interaction analysis. It has an intuitive graphical interface allowing easy network visualization and provides extensive detailed evidence for each interaction. In addition, ANAP displays the gene and protein annotation in the generated interactive network with links to The Arabidopsis Information Resource, the AtGenExpress Visualization Tool, the Arabidopsis 1,001 Genomes GBrowse, the Protein Knowledgebase, the Kyoto Encyclopedia of Genes and Genomes, and the Ensembl Genome Browser to significantly aid functional network analysis. The tool is available open access at http://gmdd.shgmo.org/Computational-Biology/ANAP.
Highlights
Protein interactions are fundamental to the molecular processes occurring within an organism and can be utilized in network biology to help organize, simplify, and understand biological complexity
These data sets are stored in a variety of databases, including Agile Protein Interaction DataAnalyzer (APID; Prieto and De Las Rivas, 2006), Arabidopsis thaliana Protein Interactome Database (AtPID; Cui et al, 2008), Arabidopsis thaliana Protein Interaction Network (AtPIN; Brandao et al, 2009), the Biomolecular Interaction Network Database (BIND; Bader et al, 2003), Biological General Repository for Interaction Datasets (BioGRID; Stark et al, 2006, 2011), ChEMBL (Overington, 2009), The Database of Interacting Proteins (DIP; Xenarios et al, 2000, 2001, 2002), IntAct (Aranda et al, 2010), InteroPORC (Michaut et al, 2008), iRefIndex (Razick et al, 2008), The Molecular INTeraction database (MINT; Ceol et al, 2010), MolCon, and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; Jensen et al, 2009; Szklarczyk et al, 2011)
The Analysis Pipeline (ANAP) tool has been developed to integrate the available Arabidopsis protein interaction data that have been generated from different sources by a variety of approaches
Summary
Protein interactions are fundamental to the molecular processes occurring within an organism and can be utilized in network biology to help organize, simplify, and understand biological complexity. There have been a number of model organisms for which large-scale protein interaction data sets have been generated, which include Saccharomyces cerevisiae (Schwikowski et al, 2000; Uetz et al, 2000), Drosophilia melanogaster (Giot et al, 2003), Caenorhabditis elegans (Li et al, 2004), and the human protein interactome (Rual et al, 2005). These data sets, and many others, have increased the amount of available protein interaction data hugely over the past 10 years, but currently, they are all collated into different protein interaction databases (Arabidopsis Interactome Mapping Consortium, 2011). The main goal of the PSICQUIC project is to provide a common query interface and implement data quality assessment from these disparate databases; this is being successfully used for many projects, including Cytoscape, IntAct, and Reactome (http://code.google.com/p/psicquic/wiki/ WhoUsesPsicquic)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
