From sampling to simulating: Single-cell multiomics in systems pathophysiological modeling
Date
2024-11-16
Journal Title
Journal ISSN
Volume Title
Publisher
iScience
Abstract
As single-cell omics data sampling and acquisition methods have accumulated at an unprecedented rate, various data analysis pipelines have been developed for the inference of cell types, cell states and their distribution, state transitions, state trajectories, and state interactions. This presents a new opportunity in which single-cell omics data can be utilized to generate high-resolution, high-fidelity computational models. In this review, we discuss how single-cell omics data can be used to build computational models to simulate biological systems at various scales. We propose that single-cell data can be integrated with physiological information to generate organ-specific models, which can then be assembled to generate multi-organ systems pathophysiological models. Finally, we discuss how generic multi-organ models can be brought to the patient-specific level thus permitting their use in the clinical setting.
Graphical abstract available at: https://doi.org/10.1016/j.isci.2024.111322
Description
This article was originally published in iScience. The version of record is available at: https://doi.org/10.1016/j.isci.2024.111322.
© 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords
systems biology, data processing in systems biology, in silico biology, biological constraints, omics
Citation
Manchel, Alexandra, Michelle Gee, and Rajanikanth Vadigepalli. “From Sampling to Simulating: Single-Cell Multiomics in Systems Pathophysiological Modeling.” iScience 27, no. 12 (December 2024): 111322. https://doi.org/10.1016/j.isci.2024.111322.