Sharan R, Ulitsky I, Shamir R (2007) Network-based prediction of protein function. Molecular systems biology 3: 88.Petrey D, Chen TS, Deng L, Garzon JI, Hwang H, Lasso G, Lee H, Silkov A, Honig B (2015) Template-based prediction of protein function. Curr Opin Struct Biol 32C:33-...
New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence. Motivation: It has long been hypothesized that incorporating models of network noise as well as edge directions and known pathway information into the repr... Cao,Mengfei,Pietras,... -...
(PPIs). While link prediction methods connect proteins on the basis of biological or network-based similarity, interacting proteins are not necessarily similar and similar proteins do not necessarily interact. Here, we offer structural and evolutionary evidence that proteins interact not if they are ...
Here we show the AUC values for different models that use machine learning techniques (ML), hand-crafted network features (NF) or a combination thereof. The left plot shows results for the prediction of a single new link (that is,w = 1) and the right plot shows the results for the...
Sequence-based prediction of protein-protein interaction sites by simplified long short-term memory networkProtein-protein interaction sitesImbalance classificationDeep learningSimplified long-short term memory networkProteins often interact with each other and form protein complexes to carry out various ...
Protein interactions mediate a wide spectrum of functions in various cellular contexts. Functional versatility of protein complexes is due to a broad range of structural adaptations that determine their binding affinity, the number of interaction sites, and the lifetime. In terms of stability it has...
The study of metabolism has attracted much attention during the last years due to its relevance in various diseases. The advance in metabolomics platforms allows us to detect an increasing number of metabolites in abnormal high/low concentration in a dis
In this work, we propose a novel method called PIKE-R2P (Protein–protein Interaction network-based Knowledge Embedding with graph neural network for single-cell RNA to Protein prediction). Given a sample of scRNA-seq data, the model predicts the abundances of multiple proteins. Our model mainly...
Spatial transcriptomics prediction from histology jointly through transformer and graph neural networks bbac297 Brief Bioinforma, 23 (2022), 10.1093/bib/bbac297 Google Scholar [74] Fey M., Lenssen J.E. Fast Graph Representation Learning with PyTorch Geometric, 2019. Google Scholar [75] Ghosh S....
To exploit the predictive power of this network-based prediction prospectively, we first focus on hydrochlorothiazide, an FDA-approved inhibitor on the sodium-chloride symporter for treatment of hypertension28. Our network-based algorithm offers 30 potentially efficacious combinations involving hydrochlorothiazi...