A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
about
OMPdb: a database of {beta}-barrel outer membrane proteins from Gram-negative bacteriaAll-atom 3D structure prediction of transmembrane β-barrel proteins from sequencesPredicting Beta Barrel Transmembrane Proteins Using HMMs.PRED-TMBB2: improved topology prediction and detection of beta-barrel outer membrane proteins.Weakly stable regions and protein-protein interactions in beta-barrel membrane proteinsBETAWARE: a machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotes.TMBB-DB: a transmembrane β-barrel proteome database.Ranking models of transmembrane β-barrel proteins using Z-coordinate predictions.Predicting the outer membrane proteome of Pasteurella multocida based on consensus prediction enhanced by results integration and manual confirmationA graph-theoretic approach for classification and structure prediction of transmembrane β-barrel proteinsBOCTOPUS: improved topology prediction of transmembrane β barrel proteins.The prediction and characterization of YshA, an unknown outer-membrane protein from Salmonella typhimurium.Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase.A folding pathway-dependent score to recognize membrane proteins.Outer membrane proteins can be simply identified using secondary structure element alignment.Structural plasticity in self-assembling transmembrane β-sheets.Structural plasticity in the topology of the membrane-interacting domain of HIV-1 gp41A look at arginine in membranes.Computational studies of membrane proteins: models and predictions for biological understanding.Inclusion of dyad-repeat pattern improves topology prediction of transmembrane β-barrel proteins.High-resolution structure prediction of β-barrel membrane proteins.OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method.Cell Surface Exposure.Model for coupled insertion and folding of membrane-spanning proteins.Discriminating membrane proteins using the joint distribution of length sums of success and failure runs
P2860
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P2860
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
description
2010 nî lūn-bûn
@nan
2010 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@ast
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@en
type
label
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@ast
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@en
prefLabel
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@ast
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@en
P2860
P921
P356
P1433
P1476
A highly accurate statistical approach for the prediction of transmembrane beta-barrels.
@en
P2093
Thomas C Freeman
William C Wimley
P2860
P304
P356
10.1093/BIOINFORMATICS/BTQ308
P407
P577
2010-06-10T00:00:00Z