Mathematical Oncology
Mathematical Oncology is a scholarly work by Alexander Anderson and Philip Maini, published in 2018 in ''Bulletin of Mathematical Biology''. The main subjects of the publication include mathematics, oncology, oncogenomics, medicine, biology, microtubule, internal medicine, and Mathematical oncology. Despite a huge amount of research effort, cancer continues to be a major killer.One of the main reasons for this is the immense complexity of the disease.Cancer is a multiscale process in which genetic mutations occurring at a subcellular level manifest themselves as functional changes at the cellular and tissue scale.Conversely, tissue level properties, such as blood flow, produce Darwinian selection forces that govern the local distribution of cellular phenotypes and genotypes.Changes in tissue lead to a disruption of organ form and function that can ultimately lead to failure and death (Fig. 1).This multiscale aspect of cancer has largely been neglected in the reductionist paradigm, which typically views cancer as "a disease of the genes".The reason for this is clear as the remarkable advances in molecular technology have greatly enhanced quantitative measurements at the genetic scale, while cellular-or tissue-scale properties remain the province of pathology and radiology, which generally lack such tools.The genomic revolution has led to the development of an extensive set of tools to measure and analyze gene expression and mutation.However, the mapping of these changes to in vivo structure and function of cancer cells and tissue remains limited.Furthermore, while tumor evolution is often viewed as a mutation-driven process, it is.