A common feature of refractory complex diseases is tissue heterogeneity. When exposed to the adverse stimulus, different types of somatic cells have different manifestations. The heterogeneity of the microenvironment is closely associated with disease progression and therapeutic responsiveness. With the progression of high-throughput techniques, the application of single-cell sequencing and spatial sequencing techniques facilitated the distinction of the cellular composition of tissues and gene expression in certain cell types. The integration of Multi-Dimension is helpful to comprehensively identify disease heterogeneity, reveal the molecular mechanism of complex diseases, and identify potential therapeutic targets. For better use of Multi-Dimension data, more algorithms and validations are still needed. These studies will provide an important scientific basis for the diagnosis, prognosis, and treatment of complex diseases.
This Research Topic aims to provide new insights into the application of Multi-Dimension data such as Single cell analysis and Multi-omics Data techniques in the identification of heterogeneity for complex diseases. Original research articles, methods, reviews, and mini-reviews are welcome. Specific areas of interest for the Topic include but are not limited to the following:
1. Tissue Heterogeneity of Complex Diseases
2. Single-cell analysis for Complex Diseases
3. The association between microenvironment heterogeneity and therapeutic sensitivity
4. Discovery of multiple biomarkers for Complex Diseases
5. Multi-omics-based network analysis in the subtype classification of complex diseases
6. The heterogeneity and crosstalk of different cell types in complex diseases
A common feature of refractory complex diseases is tissue heterogeneity. When exposed to the adverse stimulus, different types of somatic cells have different manifestations. The heterogeneity of the microenvironment is closely associated with disease progression and therapeutic responsiveness. With the progression of high-throughput techniques, the application of single-cell sequencing and spatial sequencing techniques facilitated the distinction of the cellular composition of tissues and gene expression in certain cell types. The integration of Multi-Dimension is helpful to comprehensively identify disease heterogeneity, reveal the molecular mechanism of complex diseases, and identify potential therapeutic targets. For better use of Multi-Dimension data, more algorithms and validations are still needed. These studies will provide an important scientific basis for the diagnosis, prognosis, and treatment of complex diseases.
This Research Topic aims to provide new insights into the application of Multi-Dimension data such as Single cell analysis and Multi-omics Data techniques in the identification of heterogeneity for complex diseases. Original research articles, methods, reviews, and mini-reviews are welcome. Specific areas of interest for the Topic include but are not limited to the following:
1. Tissue Heterogeneity of Complex Diseases
2. Single-cell analysis for Complex Diseases
3. The association between microenvironment heterogeneity and therapeutic sensitivity
4. Discovery of multiple biomarkers for Complex Diseases
5. Multi-omics-based network analysis in the subtype classification of complex diseases
6. The heterogeneity and crosstalk of different cell types in complex diseases
