stringgaussnet is a toolbox for a construction of protein-protein interaction networks through the ‘STRING’ application programming interface, and an inference of Gaussian networks through ‘SIMoNe’ and ‘WGCNA’ approach, from DE genes analysis results and expression data. Additional functions are provided to import automatically networks into an active ‘Cytoscape’ session.
Emmanuel Chaplais <emmanuel.chaplais at inserm.fr>, Henri-Jean Garchon
The web-server PPI is used to predict the protein-protein interaction.The protein sequence are represented by chaos game representation and wavelets transform. The chaos game representation encodes the amino acid position of the proteion and then two discrete series are gotten. The wavelets transform is used to analyse the two series. Finally the random forests algorithm is used for PPIs prediction.
The web-server PPI_RF is used to predict the protein-protein interaction. Based on the physicochemical descriptors, a protein could be converted into several digital signals and then wavelet transform was used to analyze them. With such a formulation frame to represent the samples of protein sequences, the random forests algorithm was adopted to conduct prediction.
MDCinfer aims to infer protein-protein interaction by considering cooperative domain interactions. Unlike most existing methods, it assumes cooperative-domain pairs but not only single-domain pairs as the basic units of a protein interaction. The interaction probabilities of single-domain pairs and cooperative-domain pairs are computed by a linear programming algorithm and a fast association probabilistic method. Novel protein interactions can be predicted by an extended probabilities model which can accommodate cooperative-domain pairs.