The research of malignant tumors has been refined to the molecular level, and multi-disciplinary technologies have been integrated to carry out omics research, including genomics, transcriptomics, proteomics, and microbiome. Besides, with the rapid development of artificial intelligence, the investment in machine learning algorithms provides new ideas for the exploration and application of tumor molecular targets. Tumor clinical molecular biology is an important issue in the field of contemporary medicine, using molecular biology techniques to understand the occurrence, development, and metastasis of tumors, as well as the interaction between tumors and the body. Research in this field not only helps to reveal the nature of tumors but also provides a scientific basis for early diagnosis, prevention, and treatment of tumors.
We expect this Research Topic to be clinically focused, and all papers must include clinical samples or clinical data. To create high-quality content, we welcome case reports, original research articles, and reviews that meet the following requirements.
The following topics can be selected, including but not limited to:
• Analysis of tumor-related molecular data from public databases.
• Clinical data analysis based on machine learning algorithm.
• Molecular classification of tumors, molecular targeted therapy, etc., and need to be verified by clinical samples.
• Study on tumor microbiome based on genome sequencing technology to explore the relationship between tumors and microbes.
• Immunoomics study based on tumor genome sequencing technology.
Topic editor Wei Mingxing is employed by Cellvax. The other Topic Editors declare no potential conflicts of interest with regards to the Research Topic subject.
Keywords:
malignant tumor, molecular biology, molecular pathology, microbiology, genome sequencing, immunoomics, clinical samples, clinical data
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The research of malignant tumors has been refined to the molecular level, and multi-disciplinary technologies have been integrated to carry out omics research, including genomics, transcriptomics, proteomics, and microbiome. Besides, with the rapid development of artificial intelligence, the investment in machine learning algorithms provides new ideas for the exploration and application of tumor molecular targets. Tumor clinical molecular biology is an important issue in the field of contemporary medicine, using molecular biology techniques to understand the occurrence, development, and metastasis of tumors, as well as the interaction between tumors and the body. Research in this field not only helps to reveal the nature of tumors but also provides a scientific basis for early diagnosis, prevention, and treatment of tumors.
We expect this Research Topic to be clinically focused, and all papers must include clinical samples or clinical data. To create high-quality content, we welcome case reports, original research articles, and reviews that meet the following requirements.
The following topics can be selected, including but not limited to:
• Analysis of tumor-related molecular data from public databases.
• Clinical data analysis based on machine learning algorithm.
• Molecular classification of tumors, molecular targeted therapy, etc., and need to be verified by clinical samples.
• Study on tumor microbiome based on genome sequencing technology to explore the relationship between tumors and microbes.
• Immunoomics study based on tumor genome sequencing technology.
Topic editor Wei Mingxing is employed by Cellvax. The other Topic Editors declare no potential conflicts of interest with regards to the Research Topic subject.
Keywords:
malignant tumor, molecular biology, molecular pathology, microbiology, genome sequencing, immunoomics, clinical samples, clinical data
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.