4.8 Article

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

期刊

CELL REPORTS
卷 24, 期 13, 页码 3607-3618

出版社

CELL PRESS
DOI: 10.1016/j.celrep.2018.08.085

关键词

-

资金

  1. Microsoft Research
  2. NSF [DBI-1553206, CCF-1139138, CCF-1337415, ACI-1535191]
  3. NIH [U54-AI117924, T32-HL007312, T32-HG002760, U01-CA184898, U54-NS091046]
  4. DOE [FOA-0000619]
  5. DARPA [FA8750-14-C-0011, FA8750-16-2-0032]
  6. Office of Advanced Cyberinfrastructure (OAC)
  7. Direct For Computer & Info Scie & Enginr [1535191] Funding Source: National Science Foundation

向作者/读者索取更多资源

We present a method for automatically discovering signaling pathways from time-resolved phosphoproteomic data. The Temporal Pathway Synthesizer (TPS) algorithm uses constraint-solving techniques first developed in the context of formal verification to explore paths in an interaction network. It systematically eliminates all candidate structures for a signaling pathway where a protein is activated or inactivated before its upstream regulators. The algorithm can model more than one hundred thousand dynamic phosphosites and can discover pathway members that are not differentially phosphorylated. By analyzing temporal data, TPS defines signaling cascades without needing to experimentally perturb individual proteins. It recovers known pathways and proposes pathway connections when applied to the human epidermal growth factor and yeast osmotic stress responses. Independent kinase mutant studies validate predicted substrates in the TPS osmotic stress pathway.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据