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POINeT: protein interactome with sub-network analysis and hub prioritization.

Lee SA, Chan CH, Chen TC, Yang CY, Huang KC, Tsai CH, Lai JM, Wang FS, Kao CY, Huang CY - BMC Bioinformatics (2009)

Bottom Line: Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration.Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge.The functionalities provided by POINeT are highly improved compared to previous version of POINT.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan, ROC. d93922005@ntu.edu.tw

ABSTRACT

Background: Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools.

Results: We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles.

Conclusion: The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at (http://poinet.bioinformatics.tw/).

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Related in: MedlinePlus

The analysis results and downloadable items provided by POINeT. In downloadable items, (A) attr-Query has the record of the input query of genes. The table ppi-AllPPI contains all the PPIs resulting from the query. The nodes involved in ppi-AllPPI will be identified and recorded in the attr-Interactor table. The nodes with degree >= 2 are defined as mediators and recorded in the attr-Hub table. The nodes of the attr-Hub table form a network, which is denoted as ppi-Degree2. If two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into the ppi-FilteredPPI. This network contains PPIs with higher reliabilities and certain biological significances. (B) A simple PPI network is provided to illustrate the components of the network. Query nodes are marked with red circles; mediators (nodes connecting more than two nodes) other than query nodes are marked with blue circles. QQPPI are shown in black lines. GOPPI are shown in red lines. InterologousPPI are shown in green lines.
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Figure 2: The analysis results and downloadable items provided by POINeT. In downloadable items, (A) attr-Query has the record of the input query of genes. The table ppi-AllPPI contains all the PPIs resulting from the query. The nodes involved in ppi-AllPPI will be identified and recorded in the attr-Interactor table. The nodes with degree >= 2 are defined as mediators and recorded in the attr-Hub table. The nodes of the attr-Hub table form a network, which is denoted as ppi-Degree2. If two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into the ppi-FilteredPPI. This network contains PPIs with higher reliabilities and certain biological significances. (B) A simple PPI network is provided to illustrate the components of the network. Query nodes are marked with red circles; mediators (nodes connecting more than two nodes) other than query nodes are marked with blue circles. QQPPI are shown in black lines. GOPPI are shown in red lines. InterologousPPI are shown in green lines.

Mentions: The workflow for querying, filtering and downloading PPIs is depicted in Figure 2A. Briefly, the user inputs the query terms (genes or proteins), which will be recorded as attr-Query, into POINeT to search for all available PPIs, referred to as ppi-AllPPI. If a query has no available PPI, POINeT stores it as attr-noInteractionQuery. If certain filtering criteria are set in the query page, such as 'Number of iterations' or 'Number of literature references', the number of PPIs included in ppi-AllPPI will change accordingly. Subsequently, the nodes involved in ppi-AllPPI will be in the attr-Interactor table and the degrees of these nodes will be calculated. Since the proteins outside of the query protein set could serve as a mediator in PPI network, such as a regulator or an adapter protein, nodes with a degree >= 2 are defined as mediator and recorded in the attr-Mediator table. The mediators are nodes (query and/or non-query) connecting any two query proteins. This will form another network, which removes all nodes with a degree = 1 and is denoted as ppi-Degree2. This network can reduce the complexity of network visualization and illustrate how queries are connected through these mediators. These mediators may be an important member of the sub-network around the query proteins. If a query node interacts with itself and forms a homodimer, this node will be recorded in the attr-HomoDimer table. Furthermore, if two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. Figure 2B illustrates various components in a PPI network. Interologs in different species can be inferred systematically using the NCBI HomoloGene database. These interologs' PPI will be recorded in the ppi-InterologsPPI table. Using the gene2go mapping table provided by NCBI, whether two interactors of one PPI share the same GO annotation will be noted, resulting in the ppi-GOPPI network. Finally, if interactors of ppi-QQPPI are present in the attr-Hub table, these interactors will be placed in the attr-QH table, which denotes that a node exhibits both a query and a hub in the network. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into ppi-FilteredPPI. This network contains PPIs with relatively reliable and certain biological significances. This network, which is smaller than ppi-AllPPI, can be visualized and analyzed with ease and extended with other selected features. These described tables can be downloaded in multiple formats.


POINeT: protein interactome with sub-network analysis and hub prioritization.

Lee SA, Chan CH, Chen TC, Yang CY, Huang KC, Tsai CH, Lai JM, Wang FS, Kao CY, Huang CY - BMC Bioinformatics (2009)

The analysis results and downloadable items provided by POINeT. In downloadable items, (A) attr-Query has the record of the input query of genes. The table ppi-AllPPI contains all the PPIs resulting from the query. The nodes involved in ppi-AllPPI will be identified and recorded in the attr-Interactor table. The nodes with degree >= 2 are defined as mediators and recorded in the attr-Hub table. The nodes of the attr-Hub table form a network, which is denoted as ppi-Degree2. If two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into the ppi-FilteredPPI. This network contains PPIs with higher reliabilities and certain biological significances. (B) A simple PPI network is provided to illustrate the components of the network. Query nodes are marked with red circles; mediators (nodes connecting more than two nodes) other than query nodes are marked with blue circles. QQPPI are shown in black lines. GOPPI are shown in red lines. InterologousPPI are shown in green lines.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2683814&req=5

Figure 2: The analysis results and downloadable items provided by POINeT. In downloadable items, (A) attr-Query has the record of the input query of genes. The table ppi-AllPPI contains all the PPIs resulting from the query. The nodes involved in ppi-AllPPI will be identified and recorded in the attr-Interactor table. The nodes with degree >= 2 are defined as mediators and recorded in the attr-Hub table. The nodes of the attr-Hub table form a network, which is denoted as ppi-Degree2. If two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into the ppi-FilteredPPI. This network contains PPIs with higher reliabilities and certain biological significances. (B) A simple PPI network is provided to illustrate the components of the network. Query nodes are marked with red circles; mediators (nodes connecting more than two nodes) other than query nodes are marked with blue circles. QQPPI are shown in black lines. GOPPI are shown in red lines. InterologousPPI are shown in green lines.
Mentions: The workflow for querying, filtering and downloading PPIs is depicted in Figure 2A. Briefly, the user inputs the query terms (genes or proteins), which will be recorded as attr-Query, into POINeT to search for all available PPIs, referred to as ppi-AllPPI. If a query has no available PPI, POINeT stores it as attr-noInteractionQuery. If certain filtering criteria are set in the query page, such as 'Number of iterations' or 'Number of literature references', the number of PPIs included in ppi-AllPPI will change accordingly. Subsequently, the nodes involved in ppi-AllPPI will be in the attr-Interactor table and the degrees of these nodes will be calculated. Since the proteins outside of the query protein set could serve as a mediator in PPI network, such as a regulator or an adapter protein, nodes with a degree >= 2 are defined as mediator and recorded in the attr-Mediator table. The mediators are nodes (query and/or non-query) connecting any two query proteins. This will form another network, which removes all nodes with a degree = 1 and is denoted as ppi-Degree2. This network can reduce the complexity of network visualization and illustrate how queries are connected through these mediators. These mediators may be an important member of the sub-network around the query proteins. If a query node interacts with itself and forms a homodimer, this node will be recorded in the attr-HomoDimer table. Furthermore, if two interactors of one interaction were both present in the attr-Query table, this interaction will be documented in ppi-QQPPI. Interactors in the ppi-QQPPI network will be recorded in the attr-QQ table. Figure 2B illustrates various components in a PPI network. Interologs in different species can be inferred systematically using the NCBI HomoloGene database. These interologs' PPI will be recorded in the ppi-InterologsPPI table. Using the gene2go mapping table provided by NCBI, whether two interactors of one PPI share the same GO annotation will be noted, resulting in the ppi-GOPPI network. Finally, if interactors of ppi-QQPPI are present in the attr-Hub table, these interactors will be placed in the attr-QH table, which denotes that a node exhibits both a query and a hub in the network. POINeT will merge ppi-QQPPI, ppi-GOPPI, and ppi-InterologsPPI into ppi-FilteredPPI. This network contains PPIs with relatively reliable and certain biological significances. This network, which is smaller than ppi-AllPPI, can be visualized and analyzed with ease and extended with other selected features. These described tables can be downloaded in multiple formats.

Bottom Line: Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration.Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge.The functionalities provided by POINeT are highly improved compared to previous version of POINT.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan, ROC. d93922005@ntu.edu.tw

ABSTRACT

Background: Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools.

Results: We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles.

Conclusion: The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at (http://poinet.bioinformatics.tw/).

Show MeSH
Related in: MedlinePlus