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Bacteriome.org--an integrated protein interaction database for E. coli.

Su C, Peregrin-Alvarez JM, Butland G, Phanse S, Fong V, Emili A, Parkinson J - Nucleic Acids Res. (2007)

Bottom Line: Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways.Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest.Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a 'core' high quality experimental dataset of 4863 interactions between 1100 proteins and an 'extended' experimental dataset of 9860 interactions between 2131 proteins.

View Article: PubMed Central - PubMed

Affiliation: Molecular Structure and Function, Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada.

ABSTRACT
High throughput methods are increasingly being used to examine the functions and interactions of gene products on a genome-scale. These include systematic large-scale proteomic studies of protein complexes and protein-protein interaction networks, functional genomic studies examining patterns of gene expression and comparative genomics studies examining patterns of conservation. Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways. Here we present Bacteriome.org, a resource that combines locally generated interaction and evolutionary datasets with a previously generated knowledgebase, to provide an integrated view of the Escherichia coli interactome. Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest. Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a 'core' high quality experimental dataset of 4863 interactions between 1100 proteins and an 'extended' experimental dataset of 9860 interactions between 2131 proteins. Bacteriome.org is available online at http://www.bacteriome.org.

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Related in: MedlinePlus

Typical screenshots from Bacteriome.org. (A) Summary page of a typical search. Here we have identified 155 genes associated with the word ‘kinase’ that was entered in the wild search box on the home page. The user may select one of the three datasets to view interactions associated with these 155 genes. (B) Search results pages. These pages provide summary information on each gene identified by a search. One or more genes may be selected for either a more detailed view of each gene or for viewing within the context of an interaction network. An additional button is provided to view the network of all identified genes. (C) Network view. The embedded java applet provides an interactive view of the interactions associated with 100 selected genes (large nodes). In addition to switching between different settings such as the interaction dataset and layers of neighbors to view, the Java applet features a graphical user interface to manipulate the network view. For example, the user could zoom into a section of the network, select and move groups or individual proteins and choose to view the nodes in terms of their PFAM domain architecture. (D) Alternatively, the user could also view the nodes in terms of their phylogenetic profiles. (E) The presented example shows the profiles for a group of chemotaxis related proteins that appear to form a functional module (left). Note how many of the proteins in this module appear to have homologs in a few restricted taxonomic groups including the various proteobacteria groups (different shades of blue), spirochaetes (purple), firmicutes (green), cyanobacteria (yellow) and archaea (red) suggesting a degree of evolutionary modularity. (F) In addition to visualizing interactions between individual proteins, the Java applet has also been adapted to provide a view of predicted protein complexes/functional modules. This view shows a section of the interactions between the functional modules predicted for the functional interaction network. Each pie chart shows the proportion of proteins associated with each COG functional category. The size of the pie indicates the number of proteins associated with each complex/module. Placing the mouse over the pie provides details of constituent proteins which can be selected for a more detailed view.
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Figure 1: Typical screenshots from Bacteriome.org. (A) Summary page of a typical search. Here we have identified 155 genes associated with the word ‘kinase’ that was entered in the wild search box on the home page. The user may select one of the three datasets to view interactions associated with these 155 genes. (B) Search results pages. These pages provide summary information on each gene identified by a search. One or more genes may be selected for either a more detailed view of each gene or for viewing within the context of an interaction network. An additional button is provided to view the network of all identified genes. (C) Network view. The embedded java applet provides an interactive view of the interactions associated with 100 selected genes (large nodes). In addition to switching between different settings such as the interaction dataset and layers of neighbors to view, the Java applet features a graphical user interface to manipulate the network view. For example, the user could zoom into a section of the network, select and move groups or individual proteins and choose to view the nodes in terms of their PFAM domain architecture. (D) Alternatively, the user could also view the nodes in terms of their phylogenetic profiles. (E) The presented example shows the profiles for a group of chemotaxis related proteins that appear to form a functional module (left). Note how many of the proteins in this module appear to have homologs in a few restricted taxonomic groups including the various proteobacteria groups (different shades of blue), spirochaetes (purple), firmicutes (green), cyanobacteria (yellow) and archaea (red) suggesting a degree of evolutionary modularity. (F) In addition to visualizing interactions between individual proteins, the Java applet has also been adapted to provide a view of predicted protein complexes/functional modules. This view shows a section of the interactions between the functional modules predicted for the functional interaction network. Each pie chart shows the proportion of proteins associated with each COG functional category. The size of the pie indicates the number of proteins associated with each complex/module. Placing the mouse over the pie provides details of constituent proteins which can be selected for a more detailed view.

Mentions: After performing a typical search (e.g. entering the term ‘kinase’ in the ‘Wild Search’ box on the left menu), the user is first presented with a summary page detailing the number of proteins matching the search (Figure 1A). In addition to formatting options, the user may select one of the three interaction datasets for subsequent network visualization. The following results page then provides the user with a list of proteins and brief descriptions (Figure 1B) from which individual, groups or even the entire dataset of proteins may be selected for either a detailed view of each protein (providing access to functional data, gene ontology terms, protein domains, sequence data and so forth) or a view of the network in which the selected protein(s) operate. The network view features a purpose built interactive Java applet in which proteins are represented by nodes in a graph (Figure 1C). The applet provides the user with a range of different layout settings and options for visualization of the network. These include the ability to navigate and zoom in on parts of the network, identifying nodes and visualizing the weights of interactions (which provide a measure of confidence). Placing the mouse over individual nodes provides details of individual proteins while a select function allows users to obtain a more detailed view of one or more nodes. The initial view of the network colors each protein (node) according to its COG functional category (16) and also displays proteins that directly interact with the initially selected proteins (the size of each node represents the distance from the initially selected proteins). However, uniquely, the applet also features the ability to change the node representations to show either the domain architecture of each protein (Figure 1D) or the phylogenetic profile of each protein (Figure 1E). Other features provided in the network view include the ability to alter the layer of neighbors presented in the network (e.g. nearest neighbors to the selected proteins, next nearest neighbors to the selected proteins) and the ability to choose which interaction dataset to visualize.Figure 1.


Bacteriome.org--an integrated protein interaction database for E. coli.

Su C, Peregrin-Alvarez JM, Butland G, Phanse S, Fong V, Emili A, Parkinson J - Nucleic Acids Res. (2007)

Typical screenshots from Bacteriome.org. (A) Summary page of a typical search. Here we have identified 155 genes associated with the word ‘kinase’ that was entered in the wild search box on the home page. The user may select one of the three datasets to view interactions associated with these 155 genes. (B) Search results pages. These pages provide summary information on each gene identified by a search. One or more genes may be selected for either a more detailed view of each gene or for viewing within the context of an interaction network. An additional button is provided to view the network of all identified genes. (C) Network view. The embedded java applet provides an interactive view of the interactions associated with 100 selected genes (large nodes). In addition to switching between different settings such as the interaction dataset and layers of neighbors to view, the Java applet features a graphical user interface to manipulate the network view. For example, the user could zoom into a section of the network, select and move groups or individual proteins and choose to view the nodes in terms of their PFAM domain architecture. (D) Alternatively, the user could also view the nodes in terms of their phylogenetic profiles. (E) The presented example shows the profiles for a group of chemotaxis related proteins that appear to form a functional module (left). Note how many of the proteins in this module appear to have homologs in a few restricted taxonomic groups including the various proteobacteria groups (different shades of blue), spirochaetes (purple), firmicutes (green), cyanobacteria (yellow) and archaea (red) suggesting a degree of evolutionary modularity. (F) In addition to visualizing interactions between individual proteins, the Java applet has also been adapted to provide a view of predicted protein complexes/functional modules. This view shows a section of the interactions between the functional modules predicted for the functional interaction network. Each pie chart shows the proportion of proteins associated with each COG functional category. The size of the pie indicates the number of proteins associated with each complex/module. Placing the mouse over the pie provides details of constituent proteins which can be selected for a more detailed view.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238847&req=5

Figure 1: Typical screenshots from Bacteriome.org. (A) Summary page of a typical search. Here we have identified 155 genes associated with the word ‘kinase’ that was entered in the wild search box on the home page. The user may select one of the three datasets to view interactions associated with these 155 genes. (B) Search results pages. These pages provide summary information on each gene identified by a search. One or more genes may be selected for either a more detailed view of each gene or for viewing within the context of an interaction network. An additional button is provided to view the network of all identified genes. (C) Network view. The embedded java applet provides an interactive view of the interactions associated with 100 selected genes (large nodes). In addition to switching between different settings such as the interaction dataset and layers of neighbors to view, the Java applet features a graphical user interface to manipulate the network view. For example, the user could zoom into a section of the network, select and move groups or individual proteins and choose to view the nodes in terms of their PFAM domain architecture. (D) Alternatively, the user could also view the nodes in terms of their phylogenetic profiles. (E) The presented example shows the profiles for a group of chemotaxis related proteins that appear to form a functional module (left). Note how many of the proteins in this module appear to have homologs in a few restricted taxonomic groups including the various proteobacteria groups (different shades of blue), spirochaetes (purple), firmicutes (green), cyanobacteria (yellow) and archaea (red) suggesting a degree of evolutionary modularity. (F) In addition to visualizing interactions between individual proteins, the Java applet has also been adapted to provide a view of predicted protein complexes/functional modules. This view shows a section of the interactions between the functional modules predicted for the functional interaction network. Each pie chart shows the proportion of proteins associated with each COG functional category. The size of the pie indicates the number of proteins associated with each complex/module. Placing the mouse over the pie provides details of constituent proteins which can be selected for a more detailed view.
Mentions: After performing a typical search (e.g. entering the term ‘kinase’ in the ‘Wild Search’ box on the left menu), the user is first presented with a summary page detailing the number of proteins matching the search (Figure 1A). In addition to formatting options, the user may select one of the three interaction datasets for subsequent network visualization. The following results page then provides the user with a list of proteins and brief descriptions (Figure 1B) from which individual, groups or even the entire dataset of proteins may be selected for either a detailed view of each protein (providing access to functional data, gene ontology terms, protein domains, sequence data and so forth) or a view of the network in which the selected protein(s) operate. The network view features a purpose built interactive Java applet in which proteins are represented by nodes in a graph (Figure 1C). The applet provides the user with a range of different layout settings and options for visualization of the network. These include the ability to navigate and zoom in on parts of the network, identifying nodes and visualizing the weights of interactions (which provide a measure of confidence). Placing the mouse over individual nodes provides details of individual proteins while a select function allows users to obtain a more detailed view of one or more nodes. The initial view of the network colors each protein (node) according to its COG functional category (16) and also displays proteins that directly interact with the initially selected proteins (the size of each node represents the distance from the initially selected proteins). However, uniquely, the applet also features the ability to change the node representations to show either the domain architecture of each protein (Figure 1D) or the phylogenetic profile of each protein (Figure 1E). Other features provided in the network view include the ability to alter the layer of neighbors presented in the network (e.g. nearest neighbors to the selected proteins, next nearest neighbors to the selected proteins) and the ability to choose which interaction dataset to visualize.Figure 1.

Bottom Line: Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways.Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest.Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a 'core' high quality experimental dataset of 4863 interactions between 1100 proteins and an 'extended' experimental dataset of 9860 interactions between 2131 proteins.

View Article: PubMed Central - PubMed

Affiliation: Molecular Structure and Function, Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada.

ABSTRACT
High throughput methods are increasingly being used to examine the functions and interactions of gene products on a genome-scale. These include systematic large-scale proteomic studies of protein complexes and protein-protein interaction networks, functional genomic studies examining patterns of gene expression and comparative genomics studies examining patterns of conservation. Since these datasets offer different yet highly complementary perspectives on cell behavior it is expected that integration of these datasets will lead to conceptual advances in our understanding of the fundamental design and evolutionary principles that underlie the organization and function of proteins within biochemical pathways. Here we present Bacteriome.org, a resource that combines locally generated interaction and evolutionary datasets with a previously generated knowledgebase, to provide an integrated view of the Escherichia coli interactome. Tools are provided which allow the user to select and visualize functional, evolutionary and structural relationships between groups of interacting proteins and to focus on genes of interest. Currently the database contains three interaction datasets: a functional dataset consisting of 3989 interactions between 1927 proteins; a 'core' high quality experimental dataset of 4863 interactions between 1100 proteins and an 'extended' experimental dataset of 9860 interactions between 2131 proteins. Bacteriome.org is available online at http://www.bacteriome.org.

Show MeSH
Related in: MedlinePlus