RESUMO
BACKGROUND: A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs. RESULTS: GenoLink provides a generic framework for representing and querying data graphs. This framework provides a graph data structure, a graph query engine, allowing to retrieve sub-graphs from the entire data graph, and several graphical interfaces to express such queries and to further explore their results. A query consists in a graph pattern with constraints attached to the vertices and edges. A query result is the set of all sub-graphs of the entire data graph that are isomorphic to the pattern and satisfy the constraints. The graph data structure does not rely upon any particular data model but can dynamically accommodate for any user-supplied data model. However, for genomic and post-genomic applications, we provide a default data model and several parsers for the most popular data sources. GenoLink does not require any programming skill since all operations on graphs and the analysis of the results can be carried out graphically through several dedicated graphical interfaces. CONCLUSION: GenoLink is a generic and interactive tool allowing biologists to graphically explore various sources of information. GenoLink is distributed either as a standalone application or as a component of the Genostar/Iogma platform. Both distributions are free for academic research and teaching purposes and can be requested at academy@genostar.com. A commercial licence form can be obtained for profit company at info@genostar.com. See also http://www.genostar.org.
Assuntos
Gráficos por Computador , Bases de Dados Genéticas , Expressão Gênica/fisiologia , Genes/fisiologia , Proteínas/fisiologia , Transdução de Sinais/fisiologia , Interface Usuário-Computador , Simulação por Computador , Sistemas de Gerenciamento de Base de DadosRESUMO
UNLABELLED: This article reports on PIMWalker, a free and interactive tool for visualising protein interaction networks. PIMWalker handles the unified molecular interaction (MI) format defined by members of the Proteomics Standards Initiative (the PSI MI format), and it is thus directly and easily usable by bench biologists. PIMWalker also comes with a documented, open-source Javatrade mark application programming interface allowing the bioinformatic programmer to easily extend the functions. AVAILABILITY: PIMWalker is available under a free license from http://pim.hybrigenics.com/pimwalker.
Assuntos
Bases de Dados de Proteínas , Armazenamento e Recuperação da Informação/métodos , Mapeamento de Interação de Proteínas/métodos , Proteoma/metabolismo , Transdução de Sinais/fisiologia , Software , Interface Usuário-Computador , Gráficos por Computador , Sistemas de Gerenciamento de Base de Dados/normas , Armazenamento e Recuperação da Informação/normas , Mapeamento de Interação de Proteínas/normasRESUMO
The Drosophila (fruit fly) model system has been instrumental in our current understanding of human biology, development, and diseases. Here, we used a high-throughput yeast two-hybrid (Y2H)-based technology to screen 102 bait proteins from Drosophila melanogaster, most of them orthologous to human cancer-related and/or signaling proteins, against high-complexity fly cDNA libraries. More than 2300 protein-protein interactions (PPI) were identified, of which 710 are of high confidence. The computation of a reliability score for each protein-protein interaction and the systematic identification of the interacting domain combined with a prediction of structural/functional motifs allow the elaboration of known complexes and the identification of new ones. The full data set can be visualized using a graphical Web interface, the PIMRider (http://pim.hybrigenics.com), and is also accessible in the PSI standard Molecular Interaction data format. Our fly Protein Interaction Map (PIM) is surprisingly different from the one recently proposed by Giot et al. with little overlap between the two data sets. Analysis of the differences in data sets and methods suggests alternative strategies to enhance the accuracy and comprehensiveness of the post-genomic generation of broad-scale protein interaction maps.
Assuntos
Proteínas de Drosophila/genética , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/genética , Drosophila melanogaster/metabolismo , Animais , Sequência de Bases , DNA Complementar/genética , Proteínas de Drosophila/química , Biblioteca Gênica , Genes de Insetos , Genes ras , Humanos , Ligação Proteica , Estrutura Terciária de Proteína , Especificidade da Espécie , Técnicas do Sistema de Duplo-HíbridoRESUMO
Access to the human genome facilitates extensive functional proteomics studies. Here, we present an integrated approach combining large-scale protein interaction mapping, exploration of the interaction network, and cellular functional assays performed on newly identified proteins involved in a human signaling pathway. As a proof of principle, we studied the Smad signaling system, which is regulated by members of the transforming growth factor beta (TGFbeta) superfamily. We used two-hybrid screening to map Smad signaling protein-protein interactions and to establish a network of 755 interactions, involving 591 proteins, 179 of which were poorly or not annotated. The exploration of such complex interaction databases is improved by the use of PIMRider, a dedicated navigation tool accessible through the Web. The biological meaning of this network is illustrated by the presence of 18 known Smad-associated proteins. Functional assays performed in mammalian cells including siRNA knock-down experiments identified eight novel proteins involved in Smad signaling, thus validating this integrated functional proteomics approach.
