Proteomics

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Employing Expression-Matched Controls Enables High Confidence Proximity-Based Interactome Classification (Dataset 4)


ABSTRACT: Proximity labeling approaches have been widely utilized to define protein interactomes. Due to the inherent promiscuity of proximity labeling using TurboID-based approaches, identification and adoption of appropriate labeling controls is a pivotal step to mitigate background interference and enhance interactome assignment accuracy. Here, we evaluate the effectiveness of both expression controls and data normalization strategies in generating high confidence interactome maps. This dataset contains proximity labeling proteomics results, including the proximity labeling section of TurboID-RNF10 based on the Flp-IN system. It serves as the raw data for Figure 3 and Supplementary Figure 3 in the article.

INSTRUMENT(S): timsTOF Pro 2

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Fulin Jiang  

LAB HEAD: Eric Bennett

PROVIDER: PXD061566 | Pride | 2025-07-14

REPOSITORIES: Pride

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Employing Expression-Matched Controls Enables High-Confidence Proximity-Based Interactome Classification.

Jiang Fulin F   Ge Xuezhen X   Bennett Eric J EJ  

Molecular & cellular proteomics : MCP 20250527 7


Proximity labeling approaches have been widely utilized to define protein interactomes. Due to the inherent promiscuity of proximity labeling using TurboID-based approaches, identification and adoption of appropriate labeling controls is a pivotal step to mitigate background interference and enhance interactome assignment accuracy. Here, we evaluate the effectiveness of both expression controls and data normalization strategies in generating high-confidence interactome maps. We demonstrate that  ...[more]

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