Data overload refers to the phenomenon where the volume of data generated exceeds the capacity to analyze and interpret it meaningfully. In cancer research, this challenge is particularly pronounced due to the vast amounts of genomics, proteomics, and clinical data being produced. With advancements in next-generation sequencing and other high-throughput technologies, researchers are inundated with a plethora of information that can be difficult to manage and utilize effectively.
