The main idea of this work is to test directly whether PPI networks are geometric by embedding them into a low-dimensional Euclidean space. We developed an ...
Apr 15, 2008 · We develop an algorithm that takes PPI interaction data and embeds proteins into a low-dimensional Euclidean space, under the premise that connectivity ...
An algorithm is developed that takes PPI interaction data and embeds proteins into a low-dimensional Euclidean space, under the premise that connectivity ...
To this end, we develop an algorithm that takes PPI interaction data and embeds proteins into a low-dimensional Euclidean space, under the premise that ...
To this end, we develop an algorithm that takes PPI interaction data and embeds proteins into a low-dimensional Euclidean space, under the premise that ...
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This technique is the first to utilize currently the best fitting network model for PPI networks, geometric graphs. Our approach achieves specificity of 85% and ...
Dec 3, 2022 · In this study, we develop a hypergraph model of the protein interaction network based on a 2-dimensional simplicial complex, in which we extend ...
Oct 27, 2004 · Can we represent the given PPI network as a geometric graph by embedding the proteins in R2, R3 or R4 and finding an such that proteins are ...
May 19, 2022 · We use graph convolutional network (GCN) and graph attention network (GAT) to predict the interaction between proteins by utilizing protein's structural ...
To assess the optimal geometric scale for the PPI network, we propose a novel algorithm based the motif ''thinking globally and fit locally'' in machine ...
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