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Related Experiment Video

Updated: Sep 11, 2025

Multimodal Optical Imaging Platform for Studying Cellular Metabolism
04:47

Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Published on: June 6, 2025

632

Single-cell technologies for multimodal omics measurements.

Dongsheng Bai1, Chenxu Zhu1,2

  • 1New York Genome Center, New York, NY, United States.

Frontiers in Systems Biology
|August 14, 2025
PubMed
Summary
This summary is machine-generated.

Single-cell multiomics offers a comprehensive view of cellular networks by measuring multiple molecular types simultaneously. This approach overcomes limitations of single-cell transcriptome analysis for deeper biological insights.

Keywords:
chromatin statesgenomicsmulti-omicssingle-celltranscriptome

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Area of Science:

  • Genomics
  • Molecular Biology
  • Biotechnology

Background:

  • Single-cell genomics provides high-resolution insights into cellular complexity during development and disease.
  • Single-cell transcriptome analysis reveals cellular heterogeneity but may capture only a partial molecular picture.
  • Existing methods risk overlooking interactions between different molecular layers within cells.

Purpose of the Study:

  • To review recent advances in multimodal single-cell technologies.
  • To discuss the challenges and opportunities in the field of single-cell multiomics.
  • To highlight the potential of multiomics for a holistic understanding of cellular functions.

Main Methods:

  • Review of current experimental and computational approaches in single-cell multiomics.
  • Simultaneous measurement of multiple molecular types from individual cells.
  • Analysis of integrated data from diverse single-cell omics.

Main Results:

  • Single-cell multiomics enables a more complete view of cellular molecular networks.
  • These technologies provide insights into interactions across multiple regulatory layers.
  • The field is advancing towards a holistic understanding of cellular states.

Conclusions:

  • Multimodal single-cell technologies are crucial for bridging gaps in current single-cell analysis.
  • They offer unprecedented resolution for studying cellular heterogeneity and function.
  • Addressing current challenges will unlock further potential in developmental and disease research.