title: Cancer modeling and network biology: accelerating toward personalized medicine.
abstract: The complexity of cancer progression can manifests itself on at least three scales that can be described using mathematical models, namely microscopic, mesoscopic and macroscopic scales. Multiscale cancer models have proven to be advantageous in this context because they can simultaneously incorporate the many different characteristics and scales of complex diseases such as cancer. This has driven the expansion of more predictive data-driven models, coupled to experimental and clinical data. These models are defining the foundations that facilitate the forthcoming design of patient specific cancer therapy. This should be considered as a great leap toward the era of personalized medicine. Consequently, further improvements in mathematical modeling of cancer will lead to the design of more sophisticated cancer therapy approaches.
authors: Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. Electronic address: amasoudin@ibb.ut.ac.ir.
authors: Ali
authors: A
authors: Masoudi-Nejad
authors: National Research Council Canada, Montreal, QC H4P 2R2, Canada; Center for Bioinformatics, McGill University, Montreal, QC H3G 0B1, Canada. Electronic address: edwin@mgcill.ca.
authors: Edwin
authors: E
authors: Wang
mesh_terms: D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D057285:Precision Medicine / Q000639:trends*; D049490:Systems Biology / Q000379:methods* / Q000639:trends*
keywords: Cancer modeling; Multiscale model; Network reconstruction; Personalized medicine