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Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

DOI: 10.1186/1751-0473-5-8

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Abstract:

Here we report the development of a simple open source program module (OpenPPI_predictor) that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism.Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans.The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/ webcite.The cell is the structural and functional unit of living organisms. Cells carry out numerous functions, from DNA replication, cell replication, protein synthesis, and energy production to molecule transport, to various inter- and intra-cellular signaling. Many of these fundamental processes require cascades of biochemical reactions that are catalyzed by interacting protein enzymes. Other interacting proteins provide structural support for the cells, form scaffolds for intracellular localization, and serve as chaperones or as transporters. The large-scale study of all cellular proteins is known as proteomics [1,2]. Since aspects of protein function can be inferred from the protein's complex interactions, from its position in interaction networks, one of the main goals of proteomics is to map the interactions of proteins. Uncovering protein-protein interaction information is a major undertaking in basic biological research, helps in the discovery of novel drug targets for the treatment of various diseases. Interaction networks (interactomes) for many model organisms have been established experimentally. Experimental probing of protein-protein interactions requires labor-intensive techniques, such as co-immunoprecipitation, or affinity chromatography [3]. High-throughp

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