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.
Essential proteins play a crucial role in the survival and development process of life, as they provide all available nutrients to maintain life. Therefore, many researchers pay attention to the identification of essential proteins. As experiments methods are usually costly and time-consuming, more and more computational algorithms have been developed to discover essential proteins based on biological...
This paper formulates the protein-protein interaction (PPI) prediction problem as a multi-objective optimization (MOO) problem. The focus here is to jointly maximize i) the number of common neighbors of the proteins predicted to be interacting, ii) their functional similarity, and iii) the ratio between their individual accessible solvent area and that of the corresponding protein-protein complex...
This paper provides a novel characterization of nested complexes in protein interaction networks, stressing definition and representation issues, quantification, biological validation, network metrics, motifs, modularity and gene ontology (GO) terms. This characterization can be used in the design of a nested protein complex prediction algorithm. We introduce the "nested group" concept as...
Protein complexes are important entities to organize various biological systems. However, they are still limited in availability. Thus, it is a challenging problem to predict protein complexes computationally from existing genome-wide data sets, like protein-protein interaction (PPI) networks. In this paper, we propose an efficient algorithm for predicting protein complexes by random walking on a...
Identifying modules in protein-protein interaction (PPI) networks is important to understand the organization of the cellular processes. In this paper, an improved algorithm based on affinity propagation (AP) is proposed. We embed AP in our algorithm by utilizing AP to find the candidate overlapping vertices and keep those satisfying our filter condition. We apply our algorithm to S. cerevisiae PPI...
In this paper, we propose an average-degree based cluster mining algorithm (ACM) for complexes detection in PPI networks. ACM method contains of three stages. Firstly, we make use of PPI network topology, i.e., average degree, to present a new quantitative function and then present a hierarchical algorithm to identify protein complexes. Finally, post-processing is applied to the predicted results...
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.