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首页> 外文期刊>Protein and peptide letters >Protein-protein networks construction and their relevance measurement based on multi-epitope-ligand-kartographie and gene ontology data of T-cell surface proteins for polymyositis
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Protein-protein networks construction and their relevance measurement based on multi-epitope-ligand-kartographie and gene ontology data of T-cell surface proteins for polymyositis

机译:基于多表位-配体-心电图和T细胞表面蛋白的基因本体数据的多发性肌炎蛋白-蛋白网络的构建及其相关性测定

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摘要

Polymyositis is an inflammatory myopathy characterized by muscle invasion of T-cells penetrating the basal lamina and displacing the plasma membrane of normal muscle fibers. In order to understand the different adhesive mechanisms at the T-cell surface, Schubert randomly selected 19 proteins expressed at the T-cell surface and studied them using MELK technique [4], among which 15 proteins are picked up for further study by us. Two types of functional similarity networks are constructed for these proteins. The first type is MELK similarity network, which is constructed based on their MELK data by using the McNemar's test [24]. The second type is GO similarity network, which is constructed based on their GO annotation data by using the RSS method to measuring functional similarity. Then the subset surprisology theory is employed to measure the degree of similarity between two networks. Our computing results show that these two types of networks are high related. This conclusion added new values on MELK technique and expanded its applications greatly.
机译:多发性肌炎是一种炎症性肌病,其特征是肌肉侵袭T细胞,穿透基底层并移位正常肌纤维的质膜。为了了解在T细胞表面的不同粘附机制,舒伯特随机选择了19种在T细胞表面表达的蛋白质,并使用MELK技术对其进行了研究[4],其中有15种蛋白质被我们进一步研究。针对这些蛋白质构建了两种类型的功能相似性网络。第一类是MELK相似性网络,它是通过使用McNemar检验[24]根据其MELK数据构建的。第二类是GO相似度网络,它是基于它们的GO注释数据,通过使用RSS方法来测量功能相似度而构造的。然后采用子集突变学理论来度量两个网络之间的相似度。我们的计算结果表明这两种类型的网络是高度相关的。该结论为MELK技术增加了新的价值,并极大地扩展了其应用。

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