Why we should use topological data analysis in ageing: Towards defining the "topological shape of ageing". (December 2020) - Fülöp, Tamàs; Desroches, Mathieu; A Cohen, Alan; Santos, Fernando Antônio Nóbrega; Rodrigues, Serafim
Highlights: Aging is a complex system to understand even by the use of modern computational tools. Topological data analysis (TDA) extracts knowledge from data in a holistic approach via topological considerations. TDA will help to create an ageing map that predicts the biological mechanisms underpinning pathological vs healthy ageing. TDA will unravel the causal relationships of the complex, hierarchical, heterogenic and emergent nature of ageing. Abstract: Living systems are subject to the arrow of time; from birth, they undergo complex transformations (self-organization) in a constant battle for survival, but inevitably ageing and disease trap them to death. Can ageing be understood and eventually reversed? What tools can be employed to further our understanding of ageing? The present article is an invitation for biologists and clinicians to consider key conceptual ideas and computational tools (known to mathematicians and physicists), which potentially may help dissect some of the underlying processes of ageing and disease. Specifically, we first discuss how to classify and analyse complex systems, as well as highlight critical theoretical difficulties that make complex systems hard to study. Subsequently, we introduce Topological Data Analysis - a novel Big Data tool – which may help in the study of complex systems since it extracts knowledge from data in a holistic approach via topological considerations. These conceptual ideas and tools are discussed in a relatively informal way to pave future discussions and collaborations between mathematicians and biologists studying ageing.