From genes, gene expression products, metabolites and biological macromolecules to digitized medical image, the development of omics technologies makes it possible for clinicians to study oncology systematically. The members of the omics families, including genomics and epigenomics, transcriptomics and ribotranscriptomics, proteomics, many types of metabolomics, immunomics, and radiomics, together constitute a critical part of clinical oncology research. The integration of different data set from omics families has a profound implications for understanding causative relationships of multiomics data, how cell functions and how cancer develops. Thus, multiomics technology represents a vital methodology for translational and clinical research, leading to accurate diagnosis and treatment of tumors.
These methods basically rely on next-generation sequencing and high-resolution mass spectrometry technologies which offer high throughput and precise. Furthermore, modern developments in technology have added single-cell resolution and spatial dimension to these multiomics approaches.
Unprecedented amount of Big molecular data has been generated already and continues to growth exponentially in both academic and industrial domains. This underlines the importance of bioinformatics, a field that became dominating and has a potential to combine multiomics molecular data in a synergistic way to achieve better results in molecular medicine, pharmacology, and fundamental research. Whether we are ready to integrate all types of multiomics cancer molecular data remains questionable, but the unparallelled potential of this direction is highly appreciated nowadays.
As the Volume II of the topic "Application and Innovation of Multiomics Technologies in Clinical Oncology" published in 2023, in this research topic we will focus on the application and innovation of multiomics technologies in clinical oncology.
We welcome submissions of Original Research papers and Reviews focusing on but not limited to:
- Clinical oncology research and development of tumor diagnosis technology based on multiomics. - Precision clinical oncology research based on multiomics. - Application research of clinical oncology based on multiomics. - Innovation of new omics technology or improvement of original technology. - Multiomics approach in oncology with single-cell resolution - Spatial multiomics in cancer research and molecular diagnostics - Better bioinformatic solutions for modern cancer multiomics - Systematic integration of molecular data and clinical phenotypes - Application of artificial intelligence in multiomics data interpretation - Multiomics of liquid and breath biopsy in oncology We also invite submissions that integrate bulk sequencing with single-cell and spatial transcriptomics to fill the gap of limited spatial data, driving progress in integrated oncology signature identification, multi-level molecular interaction analysis, and AI-based model development
Please note: manuscripts consisting solely of bioinformatics or computational analysis of sole public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
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