【24h】

Regularizing predicted complexes by mutually exclusive protein-protein interactions

机译:通过互斥的蛋白质-蛋白质相互作用使预测的复合物正规化

获取原文

摘要

Protein complexes are key entities in the cell responsible for various cellular mechanisms and biological processes. We propose here a method for predicting protein complexes from a protein-protein interaction (PPI) network, using information on mutually exclusive PPIs. If two interactions are mutually exclusive, they are not allowed to exist simultaneously in the same predicted complex. We introduce a new regularization term which checks whether predicted complexes are connected by mutually exclusive PPIs. This regularization term is added into the scoring function of our earlier protein complex prediction tool, PPSampler2. We show that PPSampler2 with mutually exclusive PPIs outperforms the original one. Furthermore, the performance is superior to well-known representative conventional protein complex prediction methods. Thus, it is is effective to use mutual exclusiveness of PPIs in protein complex prediction.
机译:蛋白质复合物是细胞中负责各种细胞机制和生物学过程的关键实体。我们在这里提出一种使用互斥PPI信息从蛋白质-蛋白质相互作用(PPI)网络预测蛋白质复合物的方法。如果两个相互作用是互斥的,则不允许它们同时存在于同一预测的复合物中。我们引入一个新的正则化术语,该术语检查预测的复合物是否通过互斥的PPI连接。该正则项已添加到我们较早的蛋白质复合物预测工具PPSampler2的评分功能中。我们显示具有互斥PPI的PPSampler2优于原始PPI。此外,该性能优于众所周知的代表性常规蛋白质复合物预测方法。因此,在蛋白质复合物预测中使用PPI的互斥是有效的。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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