Deciphering protein interaction network dynamics with a machine learning-based framework

被引：1

作者：

Reed, Tavis J. ^{[1
]}

Criste, Ileana M. ^{[1
]}

机构：

[1] Princeton Univ, Princeton, NJ 08544 USA

来源：

NATURE METHODS | 2024年 / 21卷 / 03期

关键词：

D O I：

10.1038/s41592-024-02180-2

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

We developed Tapioca, an integrative ensemble machine learning-based framework, to accurately predict global protein-protein interaction network dynamics. Tapioca enabled the characterization of host regulation during reactivation from latency of an oncogenic virus. Introducing an interactome homology analysis method, we identified a proviral host factor with broad relevance for herpesviruses.

引用

页码：387 / 388

页数：2

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