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The alignment of protein-protein interaction (PPI) networks is an effective approach to uncover the functionally conserved sub-structure between networks. A wealth of approaches have been developed for global PPI network alignment in recent years. However, due to the computational intractability caused by its NP-completeness, global PPI network alignment remains challenging in finding large conserved...
Prediction the interactions between proteins (targets) and small molecules (ligands) is a critical task for the drug discovery in silico. In this work, we consider the target binding site instead of the whole target and propose a pairwise input neural network (PINN) for constructing the site-ligand interaction prediction model. Different with the ordinary artificial neural network (ANN) with one vector...
Protein-DNA interactions play a critical role in many biological processes. However, the structural mechanisms underlying these interactions are not fully understood. DNA binding proteins can be classified into double-stranded DNA binding proteins (DSBs) and single-stranded DNA binding proteins (SSBs). Understanding the binding specificity of a DNA binding protein is helpful for the research of protein...
The prediction of T-cell epitopes is of great help for facilitating vaccine design and understanding the immune system. In the bioinformatics, the MHC-binding peptides are defined as the T-cell epitopes, which will trigger the immune response to the antigens. However, binding peptides cannot necessarily activate the immune response, namely non-immunogenic. Until now, little attention has been paid...
The prediction of B-cell epitopes is of great importance for computer acid vaccine design and immunodiagnostic test. Although it is said that a large majority of B-cell epitopes are conformational, experimental epitope identification has focused primarily on linear B-cell epitopes. A number of computational methods have been developed for the prediction of linear B-cell epitopes, but few of them can...
Finding a maximal biclique in a graph is an NPC problem. We developed a new, efficient method to search maximal quasi-bicliques from protein interaction network. At first, we divided the protein- protein interaction network into vertex's distance-2-subgraphs. Next, combining top down and branch and bound methods, we sought quasi-biclique from every vertex's Distance-2-Subgraph. At last, we merged...
Proteins are usually grouped into complexes to perform functional tasks in organisms. So discovery of protein complexes is critical to understand principles of cellular organization and function. Recently high-throughput techniques have produced large amount of protein-protein interaction (PPI) data, which make it possible to detect protein complexes automatically from PPI data by using computational...
Finding protein pathways in protein interaction network is a computationally intricate and tough work. In this paper we approach this problem with double direction enumeration method combined with the distance constraints, which greatly increases the speed of the algorithm. The application of the method on the known yeast MAPK pathways verifies our algorithm. Paths with length 8 can be found in 5...
Protein domain-domain interaction pairs supply functional information about the interacting proteins; and finding interaction motif pairs in protein-protein interaction database can deeply disclose the essence of the protein interaction. Up to now, there is little research work on prediction of interaction motif pairs within domain-domain interaction pairs. In this paper, we propose a new method to...
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