Posttranslational modifications are a class of important cellular activities in various bio-chemical processes including signalling trans-duction, gene/metabolite networks, and disease development. It has been found t...Posttranslational modifications are a class of important cellular activities in various bio-chemical processes including signalling trans-duction, gene/metabolite networks, and disease development. It has been found that multiple posttranslational modifications with the same or different modification residues can co-exist in the same protein and this co-occurrence is critical to signalling networks in cells. Although some biological studies have spotted this phe-nomenon, little bioinformatics study has been carried out for understanding its mechanism. Four data sets were downloaded from NCBI for the study. The joint probabilities of any two neighbouring posttranslational modification sites of different modification residues were analyzed. The Bayesian probabilistic network was derived for visualizing the relationship be-tween a target modification and the contributing modifications as the predictive factors.展开更多
文摘Posttranslational modifications are a class of important cellular activities in various bio-chemical processes including signalling trans-duction, gene/metabolite networks, and disease development. It has been found that multiple posttranslational modifications with the same or different modification residues can co-exist in the same protein and this co-occurrence is critical to signalling networks in cells. Although some biological studies have spotted this phe-nomenon, little bioinformatics study has been carried out for understanding its mechanism. Four data sets were downloaded from NCBI for the study. The joint probabilities of any two neighbouring posttranslational modification sites of different modification residues were analyzed. The Bayesian probabilistic network was derived for visualizing the relationship be-tween a target modification and the contributing modifications as the predictive factors.
