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

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.

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Fig. 1: Tapioca enables systems level dynamics and biological discovery.


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This is a summary of: Reed, T. J., Tyl, M. D., Tadych, A., Troyanskaya, O. G. & Cristea, I. M. Tapioca: a platform for predicting de novo protein–protein interactions in dynamic contexts. Nat. Methods (2024).

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Deciphering protein interaction network dynamics with a machine learning-based framework. Nat Methods 21, 387–388 (2024).

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