In [this article about human physiology as a complex network][1] the authors say that:

> "Lacking adequate analytic tools and a theoretical framework to probe
> interactions within and among diverse physiological systems, current
> approaches focus on inferring properties of time-varying
> interactions—namely strength, direction, and functional form—from
> time-locked recordings of physiological observables."

and further:

> The characterization of interactions between physiological systems
> faces several challenges: 
>
> • We often do not know exactly the systems’
> equations of motion; 
>
> • We lack knowledge as to how to merge/combine
> these equations (e.g., due to the issue of time-scale matching); 
>
> • We may have insufficient knowledge about relevant structural connections;
> • We may not have direct access to interactions between systems (e.g.,
> via probing).

Image taken from the above article, where each node corresponds to a human organ and connections between organs represent time varying "connections":

[![Image taken from the above article, where each node corresponds to a human organ and connections between organs represent time varying "connections"][2]][2]

Are there tools of complex networks from mathematical point of view which might be suited for the case written above?


  [1]: https://www.frontiersin.org/articles/10.3389/fphys.2020.598694/full
  [2]: https://i.sstatic.net/5Brxx.jpg