
AbstractWithin the last decade, the science of molecular testing has evolved from single gene and single protein analysis to broad molecular profiling as a standard of care, quickly transitioning from research to practice. Terms such as genomics, transcriptomics, proteomics, circulating omics, and artificial intelligence are now commonplace, and this rapid evolution has left us with a significant knowledge gap within the medical community. In this paper, we attempt to bridge that gap and prepare the physician in oncology for multiomics, a group of technologies that have gone from looming on the horizon to become a clinical reality. The era of multiomics is here, and we must prepare ourselves for this exciting new age of cancer medicine.
Proteomics, Neoplasms* / genetics, Cancer Diagnostics and Molecular Pathology, Medicina, 610, Genomics, Neoplasms* / therapy, artificial intelligence, Medical Oncology, transcriptomics, proteomics, machine learning, Artificial Intelligence, Neoplasms, 616, genomics, Artificial Intelligence*, cancer, Humans, digital pathology, Settore BIO/10 - BIOCHIMICA, multiomics
Proteomics, Neoplasms* / genetics, Cancer Diagnostics and Molecular Pathology, Medicina, 610, Genomics, Neoplasms* / therapy, artificial intelligence, Medical Oncology, transcriptomics, proteomics, machine learning, Artificial Intelligence, Neoplasms, 616, genomics, Artificial Intelligence*, cancer, Humans, digital pathology, Settore BIO/10 - BIOCHIMICA, multiomics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 24 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
