Message-passing algorithms for the prediction of protein domain interactions from protein-protein interaction data.
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Inferring the Brassica rapa Interactome Using Protein-Protein Interaction Data from Arabidopsis thaliana.Triangle network motifs predict complexes by complementing high-error interactomes with structural information.Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels.Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methodsCritical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences.
P2860
Message-passing algorithms for the prediction of protein domain interactions from protein-protein interaction data.
description
2008 nî lūn-bûn
@nan
2008 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Message-passing algorithms for ...... tein-protein interaction data.
@ast
Message-passing algorithms for ...... tein-protein interaction data.
@en
type
label
Message-passing algorithms for ...... tein-protein interaction data.
@ast
Message-passing algorithms for ...... tein-protein interaction data.
@en
prefLabel
Message-passing algorithms for ...... tein-protein interaction data.
@ast
Message-passing algorithms for ...... tein-protein interaction data.
@en
P356
P1433
P1476
Message-passing algorithms for ...... otein-protein interaction data
@en
P2093
Colin G Johnson
Massimo Vergassola
P304
P356
10.1093/BIOINFORMATICS/BTN366
P407
P577
2008-07-17T00:00:00Z