ABSTRACT
Phosphorylation is an important part of post-translational modifications of proteins, and is essential for many biological activities. Phosphorylation and dephosphorylation can regulate signal transduction, gene expression, and cell cycle regulation in many cellular processes. Phosphorylation is extremely important for both basic research and drug discovery to rapidly and correctly identify the attributes of a new protein phosphorylation sites. Moreover, abnormal phosphorylation can be used as a key medical feature related to a disease in some cases. The using of computational methods could improve the accuracy of detection of phosphorylation sites, which can provide predictive guidance for the prevention of the occurrence and/or the best course of treatment for certain diseases. Furthermore, this approach can effectively reduce the costs of biological experiments. In this study, a flexible neural tree (FNT), particle swarm optimization, and support vector machine algorithms were used to classify data with secondary encoding according to the physical and chemical properties of amino acids for feature extraction. Comparison of the classification results obtained from the three classifiers showed that the classification of the FNT was the best. The three classifiers were then integrated in the form of a minority subordinate to the majority vote to obtain the results. The performance of the integrated model showed improvement in sensitivity (87.41%), specificity (87.60%), and accuracy (87.50%).
Subject(s)
Algorithms , Computational Biology/methods , Models, Theoretical , Proteins/metabolism , Amino Acid Sequence , Amino Acids/chemistry , Amino Acids/genetics , Amino Acids/metabolism , Animals , Binding Sites/genetics , Databases, Protein , Humans , Hydrophobic and Hydrophilic Interactions , Neural Networks, Computer , Phosphorylation , Proteins/chemistry , Proteins/genetics , Reproducibility of Results , Support Vector MachineABSTRACT
Twenty cases of human squamous cell carcinomas of larynx were processed with an improved direct chromosome preparations. Metaphases were obtained from 5 cases and detailed G-banding analyses were completed in 3 cases. In addition, a cell line of squamous cell carcinomas of larynx (HEP-2) was analyzed with high resolution banding technique. Three generations were cytogenetically analyzed (365, 375, 395). DM, which indicate gene amplification was found in case 4 and the cell line. 6q- and i (8q) appeared in both primary tumors and the cell line, and thus could be considered as characteristic changes in human squamous cell carcinomas of larynx.
