Multiplying insights from perturbation experiments: predicting new perturbation combinations.

IF 8.5 1区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Molecular Systems Biology Pub Date : 2023-06-12 DOI:10.15252/msb.202311667

Joshua Welch

引用次数: 0

Abstract

Experimentally exploring the effect of all perturbation combinations is not feasible. In their recent study, Theis and colleagues (Lotfollahi et al, 2023) present an approach that uses deep generative models to predict the effects of new perturbations from high-throughput single perturbation experiments.

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从摄动实验中倍增的见解:预测新的摄动组合。

通过实验探索所有扰动组合的影响是不可行的。在他们最近的研究中，Theis及其同事(Lotfollahi et al, 2023)提出了一种方法，该方法使用深度生成模型来预测高通量单扰动实验中新扰动的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Molecular Systems Biology 生物-生化与分子生物学

CiteScore

18.50

自引率

1.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Systems biology is a field that aims to understand complex biological systems by studying their components and how they interact. It is an integrative discipline that seeks to explain the properties and behavior of these systems. Molecular Systems Biology is a scholarly journal that publishes top-notch research in the areas of systems biology, synthetic biology, and systems medicine. It is an open access journal, meaning that its content is freely available to readers, and it is peer-reviewed to ensure the quality of the published work.