Cranial nerves distribute in the head and face. Twelve pairs of cranial nerves lead to essential physiological processes such as vision, olfaction, and gustation, which afford more than 90% of external information in human beings. Nowadays, limited by confined analytical methods, the adoption of unitary modal data is prevalent in research on cranial nerve-associated diseases. Traditional measurements and single-omics analysis often produce unstable results with poor repeatability and low credibility in revealing pathogenesis and novel clinical biomarkers.
Multi-omics analysis simultaneously incorporates multiple dimensions, such as genomes, epigenomics, transcriptomics, proteomics, and metabolomics. Single-cell sequencing has led omics research to a higher stage with more specific information. High throughput data in macroscopical scale represented by radiomics (e.g., first-order statistics: semantic features and histograms; second-order statistics: textures; higher-order statistics: wavelet) also enriches conventional research. The novel biomarkers from multi-omics research validate on more dimensions and have more precise mechanisms, more accurate diagnosis, and prognosis detection.
This Research Topic aims to find novel biomarkers of cranial nerve-associated diseases based on multi-omics methods, provide more comprehensive evidence for pathogenesis, and lay a theoretical foundation for clinical application. The Research Topic contents mainly include, but are not limited to:
- Multi-omics analysis revealing novel targets of cranial nerve-associated diseases
- Single-cell sequencing for novel biomarkers in cranial nerve-associated diseases
- Multi-omics and multi-modal analysis of diseases of the visual system and ocular diseases
- Strategy for data dimension reduction for high throughput data of cranial nerve-associated diseases
- Neoteric multi-model data fusion research for cranial nerve-associated diseases
Cranial nerves distribute in the head and face. Twelve pairs of cranial nerves lead to essential physiological processes such as vision, olfaction, and gustation, which afford more than 90% of external information in human beings. Nowadays, limited by confined analytical methods, the adoption of unitary modal data is prevalent in research on cranial nerve-associated diseases. Traditional measurements and single-omics analysis often produce unstable results with poor repeatability and low credibility in revealing pathogenesis and novel clinical biomarkers.
Multi-omics analysis simultaneously incorporates multiple dimensions, such as genomes, epigenomics, transcriptomics, proteomics, and metabolomics. Single-cell sequencing has led omics research to a higher stage with more specific information. High throughput data in macroscopical scale represented by radiomics (e.g., first-order statistics: semantic features and histograms; second-order statistics: textures; higher-order statistics: wavelet) also enriches conventional research. The novel biomarkers from multi-omics research validate on more dimensions and have more precise mechanisms, more accurate diagnosis, and prognosis detection.
This Research Topic aims to find novel biomarkers of cranial nerve-associated diseases based on multi-omics methods, provide more comprehensive evidence for pathogenesis, and lay a theoretical foundation for clinical application. The Research Topic contents mainly include, but are not limited to:
- Multi-omics analysis revealing novel targets of cranial nerve-associated diseases
- Single-cell sequencing for novel biomarkers in cranial nerve-associated diseases
- Multi-omics and multi-modal analysis of diseases of the visual system and ocular diseases
- Strategy for data dimension reduction for high throughput data of cranial nerve-associated diseases
- Neoteric multi-model data fusion research for cranial nerve-associated diseases
