?? 98-Page Landmark Review! Single-Cell Omics Technologies, Data Analysis, and Applications. ??
SeekGene Biosciences
Decoding Unknown of Life with Novel Single-cell Technology
Over the past decade, single-cell omics has revolutionized our understanding of complex biological systems and diseases. This recent review comprehensively summarizes the latest advancements in single-cell technologies, data analysis methods, and their extensive applications in the biomedical field.
Since the inception of single-cell RNA sequencing (scRNA-seq) in 2009, we’ve witnessed remarkable progress in both horizontal and vertical dimensions—spanning single-cell genomics, epigenomics, proteomics, and metabolomics—while also delving into cutting-edge areas such as multimodal single-cell analyses, spatial transcriptomics, and CRISPR screening technologies.
?? Key Highlights:
1. Single-cell Transcriptome Sequencing: Explore the journey of scRNA-seq, current methodologies, and its applications across multiple areas, including embryonic development, tumor biology, and immune response.
2. Single-cell Spatial Transcriptomics: This section dives into the latest advancements in spatial transcriptomics, demonstrating how spatial information can be preserved during gene expression analysis—offering profound insights into cellular interactions and microenvironments in health and disease.
3. Single-cell CRISPR Screening: Here outline the integration of CRISPR technology with single-cell sequencing. This pioneering approach enables large-scale genome editing and functional screenings at unprecedented resolution, paving the way for breakthroughs in understanding gene-phenotype associations.
Looking ahead, the authors anticipate that ongoing innovations in single-cell technologies will play an ever-increasing role in biomedical research, providing precise solutions for disease treatment and health management.
Read the full review to dive deeper into the future of single-cell genomics and its implications for biomedical advancements! ??
Link：
Single-cell omics: experimental workflow, data analyses and applications