首页> 外文会议>IEEE International Workshop on Genomic Signal Processing and Statistics >HOW EFFECTIVE IS THE DATA ON CO-OCCURRENCE OF DOMAINS IN MULTI-DOMAIN PROTEINS IN PREDICTION OF PROTEIN-PROTEIN INTERACTIONS?
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HOW EFFECTIVE IS THE DATA ON CO-OCCURRENCE OF DOMAINS IN MULTI-DOMAIN PROTEINS IN PREDICTION OF PROTEIN-PROTEIN INTERACTIONS?

机译:在预测蛋白质 - 蛋白质相互作用中,多域蛋白在多域蛋白中的共同发生数据有何有效性?

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We explore the use of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template data-set of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.
机译:我们探讨了在预测蛋白质 - 蛋白质相互作用中的多域蛋白质中域中的域的共发域的使用。我们作品的基本前提是假设在多肽链中发生的结构域在它们之间进行结构或功能性相互作用。在这项研究中,我们使用多域蛋白质中的模板数据组,并预测靶生物体中的蛋白质 - 蛋白质相互作用。我们注意到,当使用密切相关的生物体的数据集作为模板时,在S.酿酒酵母中制备相互作用蛋白质结构域系(158)的最大数量。随后是细菌蛋白(48)的更多样化的数据集和数据集随机选择的蛋白质(23)。我们得出结论,使用与目标密切相关的生物体的多领域信息可以帮助预测相互作用的蛋白质。

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