scTrends: A living review of commercial single-cell and spatial 'omic technologies
Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research and drug development. We provide a living review of both mature and emerging commercial platforms, highlighting key methodologies and trends shaping the field. This...
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Veröffentlicht in: | Cell genomics 2024-12, Vol.4 (12), p.100723, Article 100723 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Understanding the rapidly evolving landscape of single-cell and spatial omic technologies is crucial for advancing biomedical research and drug development. We provide a living review of both mature and emerging commercial platforms, highlighting key methodologies and trends shaping the field. This review spans from foundational single-cell technologies such as microfluidics and plate-based methods to newer approaches like combinatorial indexing; on the spatial side, we consider next-generation sequencing and imaging-based spatial transcriptomics. Finally, we highlight emerging methodologies that may fundamentally expand the scope for data generation within pharmaceutical research, creating opportunities to discover and validate novel drug mechanisms. Overall, this review serves as a critical resource for navigating the commercialization and application of single-cell and spatial omic technologies in pharmaceutical and academic research.
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De Jonghe et al. present a comprehensive review of current commercial single-cell and spatial omic technologies, outlining key platforms, methodologies, and trends shaping the field—from microfluidics and plate-based approaches to combinatorial indexing, highlighting their applications in drug discovery. The authors discuss emerging engineering and computational advancements that are enabling more efficient data generation and interpretation. Finally, they explore new tools and techniques that promise to expand the scope of omic analyses, driving innovation and understanding in biomedical research. |
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ISSN: | 2666-979X 2666-979X |
DOI: | 10.1016/j.xgen.2024.100723 |