β-Barrel Transmembrane Protein Predicting Using Support Vector Machine

Membrane protein is a kind of protein with unique transmembrane structure, which is the material basis for cells to perform various functions. It is an important biological signal molecule to assume the information transmission between the cell and the external environment. It is a precursor step to predict the classification of β-barrel transmembrane protein according to the protein sequence information for 3D structure modeling and function analysis. We firstly use the method of compromising features consist of the position information in sequence and the physiochemical properties of amino acid residues. Then a model by support vector machine algorithm (SVM) is built to predict the β-barrel transmembrane protein. The experimental results presented that transmembrane protein structure prediction based on SVM can provide valid enhancement to transmembrane protein 3D structure prediction and function analysis.

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