The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Identification of essential proteins is very important for understanding the minimal requirements for cellular life and also necessary for a series of practical applications, such as drug design. With the advances in high throughput technologies, a large number of protein–protein interactions are available, which makes it possible to detect proteins’ essentialities from the network level. Considering...
As advances in the technologies of predicting protein interactions, huge data sets portrayed as networks have been available. Identification of functional modules from such networks is crucial for understanding principles of cellular organization and functions. However, protein interaction data produced by high-throughput experiments are generally associated with high false positives, which makes...
Dense subgraphs of protein interaction networks are believed to be potential protein complexes and play an important role in analyzing cellular organization and predicting functions of proteins. In this paper, we present a new algorithm LD-Miner for mining l-dense subgraphs in protein interaction networks. We apply algorithm LD-Miner to the protein interaction network of Saccharomyces cerevisiae collected...
The datasets identified by large-scale, high- throughput methods typically suffer from a relatively high level of noise. Combining the distribution characteristics of noise data and topological properties in the protein interaction network, we described a novel method to improve the reliability of those datasets by predicting missed interactions. The main idea of the method is to predict the interactions...
As advanced in the technologies of predicting protein-protein interactions, huge data sets portrayed as networks have been generated. Identification of functional modules from such networks is crucial for understanding principles of cellular organization and functions. In this paper, we presented a new fast agglomerate algorithm of identifying functional modules based on the edge clustering coefficients,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.