Matteo Manica, Roland Mathis, et al.
Nature Machine Intelligence
This perspective article gathers the latest developments in mathematical and computational oncology tools that exploit network approaches for the mathematical modelling, analysis, and simulation of cancer development and therapy design. It instigates the community to explore new paths and synergies under the umbrella of the Special Issue “Networks in Cancer: From Symmetry Breaking to Targeted Therapy”. The focus of the perspective is to demonstrate how networks can model the physics, analyse the interactions, and predict the evolution of the multiple processes behind tumour-host encounters across multiple scales. From agent-based modelling and mechano-biology to machine learning and predictive modelling, the perspective motivates a methodology well suited to mathematical and computational oncology and suggests approaches that mark a viable path towards adoption in the clinic.
Matteo Manica, Roland Mathis, et al.
Nature Machine Intelligence
Hua-Sheng Chiu, María Rodríguez Martínez, et al.
Nucleic acids research
Matteo Manica, Charlotte Bunne, et al.
Bioinformatics
Hua-Sheng Chiu, María Rodríguez Martínez, et al.
BMC Genomics