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Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes
Anthony J. Cesnik, Leah V. Schaffer, Ishan Gaur, Mayank Jain, Trey Ideker, Emma K. Lundberg
Annual Review of Biomedical Data Science · 2024 · ▲ 9 citations
Abstract
While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.
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- OpenAlex
- DOI
- 10.1146/annurev-biodatasci-102423-113534
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- 2026-10-14 MST
Cite this
APA
Cesnik, A.J., Schaffer, L.V., Gaur, I., Jain, M., Ideker, T., & Lundberg, E.K. (2024). Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes. <em>Annual Review of Biomedical Data Science</em>. https://doi.org/10.1146/annurev-biodatasci-102423-113534
Vancouver
Cesnik AJ, Schaffer LV, Gaur I, Jain M, Ideker T, Lundberg EK. Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes. Annual Review of Biomedical Data Science. 2024. doi:10.1146/annurev-biodatasci-102423-113534.
BibTeX
@article{anthony2024Mappin,
title = {Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes},
author = {Anthony J. Cesnik and Leah V. Schaffer and Ishan Gaur and Mayank Jain and Trey Ideker and Emma K. Lundberg},
journal = {Annual Review of Biomedical Data Science},
year = {2024},
doi = {10.1146/annurev-biodatasci-102423-113534},
}
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