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Proteins control and mediate many biological activities via interactions with other protein partners. Information of protein networks derived from protein interactions can serve as a good starting point for understanding the molecular machinery. Besides, elucidating protein interacting partnerships may help annotate unknown proteins and provide further insight into biological networks.
Various experimental strategies are available for identifying protein interactions. While the conducive for high-throughput technology on the yeast two-hybrid system, performed in bacteria, yeast, worms, flies and more recently, mice and humans 1—4 , enable us to characterize physical protein—protein interactions in the genome-wide scale 5 , 6.
Besides, some interesting interactomes of host—pathogens 4 , 13 , 14 and carcinogenesis 2 , were also published recently. A protein interaction network is naturally complicate and far from a random network.
Using the network characters, such as the degree distribution, clustering, diameter and relative graphlet frequency distribution, information can be extracted from a protein—protein network Combining the gene-expression data with a high-quality yeast protein—protein interaction dataset, Han et al. One of them is more likely to be the module organizers and the other to be the module connectors For example, CFinder is a tool for predicting the function of a single protein and for discovering novel protein modules Hubba is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory.
In this website, we explore the essential nodes by six characteristic analysis methods on protein—protein interaction network, including Degree, BottleNeck BN , Edge Percolation Component EPC , Subgraph Centrality SC and two characteristic analysis algorithms developed by us: Hubba result includes a rank given by a composite index in DSS, a manifest graph of network to show the relationship amid these hubs via SVG viewer http: The clues revealed from network topological analysis will provide a new sight to experimental biologists.
The Hubba system is built in an open-source structure: The framework of whole system is depicted in Figure 1. After the calculation, user will receive the notification to views the result on the result display page. The result will be included general properties of submitted network, list of hub proteins with the graph of interaction among them, Cytoscape's format output and lists of protein ranking scores by several algorithms.
Hubba explores the possibly essential proteins in the interaction network by six topology-based scoring methods and a DSS. Each scoring method catches certain postulated topological characteristic of essential proteins. Therefore, a DSS is proposed. That is to say, two scoring methods A and B, are used to extract mixed characteristic of essential proteins.
For n , most possible essential proteins are expected in the output, the 2 n top ranked proteins by method A are selected firstly. The selected 2 n proteins are further ranked by method B and the n top ranked proteins are output.
The number 2 n is an empirical value for this double screening method. The list of yeast essential protein was integrated with the dataset from functional characterization of the Saccharomyces cerevisiae genome by gene deletion 27 and updated information from SGD http: Three types of data format are accepted: The dataset may be submitted by pasting the interaction data in the query form directly, or uploading a file from the local computer.
An email address is suggested to provide for those jobs may be time consuming; the Hubba daemon will notify the job completion by email. All input data in a query are parsed and stored in a temporary database for the following analysis. Hubba will conduct six topological methods and the double screening scheme to submitted dataset and acquire ranking score for each node in the submitted network. In this way, the connectivity among hubs can be easy identified. We also provide the output in gml and EPS format, which can be open in Cytoscape http: Normally, an analysis job is completed within a few minutes and the result is pushed back to the same web browser window automatically.
If a job takes longer than expected, the user can save the link as a bookmark and revisits Hubba later, or follows the link provided in the notice mail to retrieve the analysis results.
The main ideas of the double screening scheme are to select methods catching diverse characters and to include most essential proteins. Firstly, the overlapping of n top lists from different methods is studied. For all the six methods applied to the protein—protein interaction dataset yeast Among all methods, DMNC are found to be the one that shares the least proteins with the others.
Accordingly, the topological characters extracted by DMNC may differ from those by the other methods. Second, we evaluate the performance of the six scoring method by the coverage of yeast essential proteins. The second method of the double screen scheme is chosen on the same criteria.
The scheme improves the hit rate Table 1 , last column. The percentage of top n ranked proteins, identified from the yeast protein interaction dataset yeast Hubba is constructed as a user-friendly interface for dataset uploading and result displaying. We utilize a coloring scheme, from red to green, as a cue of the ranking score and a line pattern to discriminate direct interaction solid line from indirect interaction dotted line. Furthermore, the advanced options of browsing the neighborhood of these hubs and the shortest path distance between hub nodes.
The more precalculated results are available in our help page http: The top10 nodes of the dataset yeast A coloring scheme is used to display the ranking score of each node. When the node is redder, the ranking of it will be higher. Solid lines indicate the connected nodes interact to each other direct connections , while dotted lines with a number indicate the shortest path distance between two linking nodes indirect connections.
Identifying hubs or fragile motifs are very important in network biology. For example, based on the overview of the interaction among human proteins and proteins from pathogen stains is revealed that both viral and bacterial pathogens tend to interact with hub and bottlenecks in the human PPI network Feldman and his co-workers 30 conclude some network properties of human inheritable diseases. They found that genes and proteins harboring variation causing the same disease phenotype tend to form directly connected clusters.
A similar purpose for identifying disease-associated proteins can be found in Hubba , which accepts a query of an interested list on a user-defined network and provides output for the shortest path among them. In this way, nodes in the paths may serve as candidates related to the disorder the query list involved. And if you want to know what "he's" so often up to in the bathroom, then Hubba Hubba Bubba!! As for what has been lyrically done to the classic, toe tapping rocker, Wear My Ring Around Your Neck , fathers lock up your daughters now!!!
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Hubba (software company)
Published December 6, Updated April 8, Hubba says more than 40, companies use its platform, including consumer products. Jul 1; 36(Web Server issue): W–W . This article has been cited by other articles in PMC. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast. This is how Zifkin came to design Hubba around his original concept and take the site live in To date, the site has connected with more.