首页> 美国卫生研究院文献>Proteome Science >Accuracy improvement in protein complex prediction from protein interaction networks by refining cluster overlaps
【2h】

Accuracy improvement in protein complex prediction from protein interaction networks by refining cluster overlaps

机译:通过精炼簇重叠从蛋白质相互作用网络预测蛋白质复合物的准确性提高

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

BackgroundRecent computational techniques have facilitated analyzing genome-wide protein-protein interaction data for several model organisms. Various graph-clustering algorithms have been applied to protein interaction networks on the genomic scale for predicting the entire set of potential protein complexes. In particular, the density-based clustering algorithms which are able to generate overlapping clusters, i.e. the clusters sharing a set of nodes, are well-suited to protein complex detection because each protein could be a member of multiple complexes. However, their accuracy is still limited because of complex overlap patterns of their output clusters.
机译:背景技术最近的计算技术已经促进了对几种模型生物的全基因组蛋白质-蛋白质相互作用数据的分析。各种图聚类算法已应用于基因组规模的蛋白质相互作用网络,以预测整套潜在的蛋白质复合物。特别地,能够产生重叠簇(即,共享一组节点的簇)的基于密度的聚类算法非常适合蛋白质复合物检测,因为每种蛋白质可以是多个复合物的成员。但是,由于其输出集群的复杂重叠模式,其准确性仍然受到限制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号