CORNET: a user-friendly tool for data mining and integration.
As an overwhelming amount of functional genomics data have been generated, the retrieval, integration, and interpretation of these data need to be facilitated to enable the advance of (systems) biological research. For example, gathering and processing microarray data that are related to a particular biological process is not straightforward, nor is the compilation of protein-protein interactions from numerous partially overlapping databases identified through diverse approaches. However, these tasks are inevitable to address the following questions. Does a group of differentially expressed genes show similar expression in diverse microarray experiments? Was an identified protein-protein interaction previously detected by other approaches? Are the interacting proteins encoded by genes with similar expression profiles and localization? We developed CORNET (for CORrelation NETworks) as an access point to transcriptome, protein interactome, and localization data and functional information on Arabidopsis (Arabidopsis thaliana). It consists of two flexible and versatile tools, namely the coexpression tool and the protein-protein interaction tool. The ability to browse and search microarray experiments using ontology terms and the incorporation of personal microarray data are distinctive features of the microarray repository. The coexpression tool enables either the alternate or simultaneous use of diverse expression compendia, whereas the protein-protein interaction tool searches experimentally and computationally identified protein-protein interactions. Different search options are implemented to enable the construction of coexpression and/or protein-protein interaction networks centered around multiple input genes or proteins. Moreover, networks and associated evidence are visualized in Cytoscape. Localization is visualized in pie charts, thereby allowing multiple localizations per protein. CORNET is available at http://bioinformatics.psb.ugent.be/cornet.
De Bodt
Stefanie
S
Department of Plant Systems Biology, Flanders Institute for Biotechnology, Ghent University, 9052 Ghent, Belgium. stefanie.debodt@psb.vib-ugent.be
Carvajal
Diana
D
Hollunder
Jens
J
Van den Cruyce
Joost
J
Movahedi
Sara
S
Inzé
Dirk
D
D017360:Arabidopsis / Q000378:metabolism; D029681:Arabidopsis Proteins / Q000378:metabolism; D019295:Computational Biology; D057225:Data Mining; D030562:Databases, Protein; D020869:Gene Expression Profiling; D020411:Oligonucleotide Array Sequence Analysis; D025941:Protein Interaction Mapping; D012984:Software
D029681:Arabidopsis Proteins