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PRED-TMBB: a web server for predicting the topology of ?barrel outer membrane proteins
The beta-barrel outer membrane proteins constitute one of the two known structural classes of membrane proteins. Whereas there are several different web-based predictors for alpha-helical membraneExpand
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A Hidden Markov Model method, capable of predicting and discriminating β-barrel outer membrane proteins
BackgroundIntegral membrane proteins constitute about 20–30% of all proteins in the fully sequenced genomes. They come in two structural classes, the α-helical and the β-barrel membrane proteins,Expand
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PredSL: A Tool for the N-terminal Sequence-based Prediction of Protein Subcellular Localization
The ability to predict the subcellular localization of a protein from its sequence is of great importance, as it provides information about the protein’s function. We present a computational tool,Expand
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Cytokine gene polymorphisms in periodontal disease: a meta-analysis of 53 studies including 4178 cases and 4590 controls.
AIM We conducted a systematic review and a meta-analysis, in order to investigate the potential association of cytokine gene polymorphisms with either aggressive or chronic periodontal disease. Expand
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A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins
The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the differentExpand
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TMRPres2D: high quality visual representation of transmembrane protein models
The 'TransMembrane protein Re-Presentation in 2-Dimensions' (TMRPres2D) tool, automates the creation of uniform, two-dimensional, high analysis graphical images/models of alpha-helical or beta-barrelExpand
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A novel method for predicting transmembrane segments in proteins based on a statistical analysis of the SwissProt database: the PRED-TMR algorithm.
We present a novel method that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The PRED-TMR algorithm described, refines a standardExpand
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Prediction of lipoprotein signal peptides in Gram-positive bacteria with a Hidden Markov Model.
We present a Hidden Markov Model method for the prediction of lipoprotein signal peptides of Gram-positive bacteria, trained on a set of 67 experimentally verified lipoproteins. The methodExpand
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Prediction of signal peptides in archaea.
Computational prediction of signal peptides (SPs) and their cleavage sites is of great importance in computational biology; however, currently there is no available method capable of predictingExpand
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CAST: an iterative algorithm for the complexity analysis of sequence tracts
MOTIVATION Sensitive detection and masking of low-complexity regions in protein sequences. Filtered sequences can be used in sequence comparison without the risk of matching compositionally biasedExpand
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